Adaptive Control of Differentially Private Linear Quadratic Systems

Chowdhury, SR and Zhou, X and Shroff, N (2021) Adaptive Control of Differentially Private Linear Quadratic Systems. In: 2021 IEEE International Symposium on Information Theory, ISIT 2021, 12-20 Jul 2021, Melbourne, pp. 485-490.

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Abstract

In this paper we study the problem of regret minimization in reinforcement learning (RL) under differential privacy constraints. This work is motivated by the wide range of RL applications for providing personalized service, where privacy concerns are becoming paramount. In contrast to previous works, we take the first step towards non-tabular RL settings, while providing a rigorous privacy guarantee. In particular, we consider the adaptive control of differentially private linear quadratic (LQ) systems. We develop the first private RL algorithm, Private-OFU-RL which is able to attain a sub-linear regret while guaranteeing privacy protection. More importantly, the additional cost due to privacy is only on the order of \fracłn(1/δ)1/4\varepsilon1/2 given privacy parameters \varepsilon, δ > 0. Through this process, we also provide a general procedure for adaptive control of LQ systems under changing regularizers, which not only generalizes previous non-private controls, but also serves as the basis for general private controls. © 2021 IEEE., keywords=Control theory; Information theory; Privacy by design; Reinforcement learning, Adaptive Control; Additional costs; Differential privacies; Linear quadratic; Personalized service; Privacy concerns; Privacy protection; Regret minimization, Adaptive control systems, fundingdetails1=National Science FoundationNational Science Foundation, NSF, CNS-1901057, CNS-2007231, fundingdetails2=Office of Naval ResearchOffice of Naval Research, ONR, N00014-17-1-241, fundingtext1=However, in most practical scenarios, the feedback from the users often encodes their sensitive information. For example, in a personalized healthcare setting, the states of a patient include personal information such as age, gender, height, weight, state of the treatment etc. Similarly, the states of a virtual keyboard user (e.g., â��Equal contribution. This work was funded in part through NSF grants: CNS-1901057 and CNS-2007231, and an Office of Naval Research under Grant N00014-17-1-241 Google GBoard users) are the words and sentences she typed in, which inevitably contain private information about the user. Another intriguing example is the social robot for second language education of children. The states include facial expressions, and the rewards contain whether they have passed the quiz. Users may not want any of this information to be inferred by others. This directly results in an increasing concern about privacy protection in personalized services. To be more specific, although a user might be willing to share her own information to the agent to obtain a better tailored service, she would not like to allow third parties to infer her private information from the output of the learning algorithm. For example, in the healthcare application, we would like to ensure that an adversary with arbitrary side knowledge cannot infer a particular patientâ��s state from the treatments prescribed to her., references=1. Li, L., Chu, W., Langford, J., Schapire, R.E., A contextualbandit approach to personalized news article recommendation (2010) Proceedings of the 19th International Conference on World Wide Web, pp. 661-670; 2. Zhao, Y., Kosorok, M.R., Zeng, D., Reinforcement learning design for cancer clinical trials (2009) Statistics in Medicine, 28 (26), pp. 3294-3315; 3. Sharma, A.R., Kaushik, P., Literature survey of statistical, deep and reinforcement learning in natural language processing (2017) 2017 International Conference on Computing, Communication and Automation (ICCCA, pp. 350-354; 4. Gordon, G., Spaulding, S., Westlund, J.K., Lee, J.J., Plummer, L., Martinez, M., Das, M., Breazeal, C., Affective personalization of a social robot tutor for children's second language skills (2016) Proceedings of the Aaai Conference on Artificial Intelligence, 30 (1); 5. Dwork, C., Differential privacy: A survey of results (2008) International Conference on Theory and Applications of Models of Computation, pp. 1-19. , Springer; 6. Tossou, A., Dimitrakakis, C., Algorithms for differentially private multi-armed bandits (2016) Proceedings of the Aaai Conference on Artificial Intelligence, 30 (1); 7. Achieving privacy in the adversarial multi-armed bandit (2017) Proceedings of the Aaai Conference on Artificial Intelligence, 31 (1); 8. Basu, D., Dimitrakakis, C., Tossou, A., (2019) Differential Privacy for Multi-armed Bandits: What Is It and What Is Its Cost?; 9. Mishra, N., Thakurta, A., (nearly) optimal differentially private stochastic multi-arm bandits (2015) Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, pp. 592-601; 10. Zhou, X., Tan, J., Local Differential Privacy for Bayesian Optimization, p. 2020; 11. Balle, B., Gomrokchi, M., Precup, D., Differentially private policy evaluation (2016) International Conference on Machine Learning. Pmlr, pp. 2130-2138; 12. Vietri, G., Balle, B., Krishnamurthy, A., Wu, S., Private reinforcement learning with pac and regret guarantees (2020) International Conference on Machine Learning. Pmlr, pp. 9754-9764; 13. Garcelon, E., Perchet, V., Pike-Burke, C., Pirotta, M., Local Differentially Private Regret Minimization in Reinforcement Learning, p. 2020; 14. Abbasi-Yadkori, Y., Szepesvári, C., Regret bounds for the adaptive control of linear quadratic systems (2011) Proceedings of the 24th Annual Conference on Learning Theory, pp. 1-26; 15. Osband, I., Roy, B.V., Model-based reinforcement learning and the eluder dimension (2014) Proceedings of the 27th International Conference on Neural Information Processing Systems, 1, pp. 1466-1474; 16. Chowdhury, S.R., Gopalan, A., Online learning in kernelized markov decision processes (2019) The 22nd International Conference on Artificial Intelligence and Statistics. Pmlr, pp. 3197-3205; 17. Wang, T., Yang, L.F., Episodic Linear Quadratic Regulators with Low-rank Transitions, p. 2020; 18. Jin, C., Yang, Z., Wang, Z., Jordan, M.I., Provably efficient reinforcement learning with linear function approximation (2020) Conference on Learning Theory, pp. 2137-2143; 19. Bertsekas, D., Dynamic programming and optimal control (2004) Athena Scientific Belmont, , MA, 3 edition; 20. Dwork, C., Roth, A., (2014) The Algorithmic Foundations of Differential Privacy; 21. Kearns, M., Pai, M., Roth, A., Ullman, J., Mechanism design in large games: Incentives and privacy (2014) Proceedings of the 5th Conference on Innovations in Theoretical Computer Science, pp. 403-410; 22. Bun, M., Steinke, T., Concentrated differential privacy: Simplifications, extensions, and lower bounds (2016) Theory of Cryptography Conference, pp. 635-658. , Springer; 23. Abbasi-Yadkori, Y., Pál, D., Szepesvári, C., Improved algorithms for linear stochastic bandits (2011) Advances in Neural Information Processing Systems, pp. 2312-2320; 24. Chan, T.-H.H., Shi, E., Song, D., Private and continual release of statistics (2011) Acm Transactions on Information and System Security (TISSEC, 14 (3), pp. 1-24; 25. Hsu, J., Huang, Z., Roth, A., Roughgarden, T., Wu, Z.S., Private matchings and allocations (2016) Siam Journal on Computing, 45 (6), pp. 1953-1984; 26. Vershynin, R., (2018) High-dimensional Probability: An Introduction with Applications in Data Science, 47. , Cambridge university press; 27. Laurent, B., Massart, P., Adaptive estimation of a quadratic functional by model selection (2000) Annals of Statistics, pp. 1302-1338, sponsors=IEEE Information Theory Society; The Institute of Electrical and Electronics Engineers, publisher=Institute of Electrical and Electronics Engineers Inc., issn=21578095, isbn=9781538682098, coden=PISTF, language=English, abbrevsourcetitle=IEEE Int Symp Inf Theor Proc, documenttype=Conference Paper, source=Scopus, @CONFERENCEVippathalla20211624, author=Vippathalla, PK and Chan, C and Kashyap, N and Zhou, Q, title=Secret Key Agreement and Secure Omniscience of Tree-PIN Source with Linear Wiretapper, journal=IEEE International Symposium on Information Theory - Proceedings, year=2021, volume=2021-July, pages=1624-1629, doi=https://doi.org/10.1109/ISIT45174.2021.9518075, note=The copyright for this article belongs to , url=https://www.scopus.com/inward/record.uri?eid=2-s2.0-85115053045&doi=10.11092fISIT45174.2021.9518075&partnerID=40&md5=76cafccf7a606fd4fc82a6b0c54bf9f7, affiliation=Indian Institute of Science, Department of Electrical Communication Engineering, Bangalore, 560012, India, abstract=In this paper, we obtain a single-letter characterization of the wiretap secret key capacity for a large class of multiterminal source models (namely, tree-PIN models) with a linear wiretapper that can observe arbitrary linear combinations of the source. For this class of sources, we also show a duality between the problems of wiretap secret key agreement and secure omniscience, which suggests that such duality potentially holds for more general sources. © 2021 IEEE., keywords=Forestry; Information theory, General source; Linear combinations; Multi terminals; Secret key agreement; Secret key capacities; Source models, Cryptography, fundingdetails1=21203318, fundingdetails2=Department of Science and Technology, Ministry of Science and Technology, IndiaDepartment of Science and Technology, Ministry of Science and Technology, India, डà¥�à¤�सà¤�à¥�, fundingtext1=C. Chan (email: chung.chan@cityu.edu.hk) is with the Department of Computer Science, City University of Hong Kong. His work is supported by a grant from the University Grants Committee of the Hong Kong Special Administrative Region, China (Project No. 21203318)., fundingtext2=N. Kashyap (nkashyap@iisc.ac.in) and Praneeth Kumar V. (pra-neethv@iisc.ac.in) are with the Department of Electrical Communication Engineering, Indian Institute of Science, Bangalore 560012. Their work was supported in part by a Swarnajayanti Fellowship awarded to N. Kashyap by the Department of Science & Technology (DST), Government of India., references=1. Csiszar, I., Narayan, P., Secrecy capacities for multiple terminals (2004) IEEE Transactions on Information Theory, 50 (12), pp. 3047-3061; 2. Gohari, A.A., Anantharam, V., Information-theoretic key agreement of multiple terminals-part i (2010) IEEE Transactions on Information Theory, 56 (8), pp. 3973-3996; 3. Poostindouz, A., Safavi-Naini, R., Wiretap secret key capacity of tree-pin (2019) 2019 IEEE International Symposium on Information Theory (ISIT, pp. 315-319; 4. Chan, C., Kashyap, N., Vippathalla, P.K., Zhou, Q., Secure information exchange for omniscience (2020) 2020 IEEE International Symposium on Information Theory (ISIT, pp. 966-971; 5. Nitinawarat, S., Ye, C., Barg, A., Narayan, P., Reznik, A., Secret key generation for a pairwise independent network model (2010) IEEE Transactions on Information Theory, 56 (12), pp. 6482-6489; 6. Chan, C., Mukherjee, M., Kashyap, N., Zhou, Q., Upper bounds via lamination on the constrained secrecy capacity of hypergraphical sources (2019) IEEE Transactions on Information Theory, 65 (8), pp. 5080-5093; 7. Zhou, Q., Chan, C., Yeung, R.W., On the discussion rate region for the pin model (2020) 2020 IEEE International Symposium on Information Theory (ISIT, pp. 955-959; 8. Yan, M., Sprintson, A., Algorithms for weakly secure data exchange (2013) 2013 International Symposium on Network Coding (NetCod, pp. 1-6; 9. Courtade, T.A., Halford, T.R., Coded cooperative data exchange for a secret key (2016) IEEE Transactions on Information Theory, 62 (7), pp. 3785-3795; 10. Chan, C., Zheng, L., Mutual dependence for secret key agreement (2010) 2010 44th Annual Conference on Information Sciences and Systems (CISS, pp. 1-6; 11. Chan, C., Mukherjee, M., Kashyap, N., Zhou, Q., Multiterminal secret key agreement at asymptotically zero discussion rate (2018) 2018 IEEE International Symposium on Information Theory (ISIT, pp. 2654-2658; 12. Maurer, U.M., Wolf, S., Unconditionally secure key agreement and the intrinsic conditional information (1999) IEEE Transactions on Information Theory, 45 (2), pp. 499-514; 13. Vippathalla, P.K., Chan, C., Kashyap, N., Zhou, Q., (2021) Secret Key Agreement and Secure Omniscience of Tree-PIN Source with Linear Wiretapper, , https://arxiv.org/abs/2102.01771; 14. Nitinawarat, S., Narayan, P., Perfect omniscience, perfect secrecy, and steiner tree packing (2010) IEEE Transactions on Information Theory, 56 (12), pp. 6490-6500, sponsors=IEEE Information Theory Society; The Institute of Electrical and Electronics Engineers, publisher=Institute of Electrical and Electronics Engineers Inc., issn=21578095, isbn=9781538682098, coden=PISTF, language=English, abbrevsourcetitle=IEEE Int Symp Inf Theor Proc, documenttype=Conference Paper, source=Scopus, @CONFERENCEKumar20211665, author=Kumar, PV and Dharmappa, D and Mishra, S, title=Interleaved Z₄-Linear Sequences with Improved Correlation for Satellite Navigation, journal=IEEE International Symposium on Information Theory - Proceedings, year=2021, volume=2021-July, pages=1665-1670, doi=https://doi.org/10.1109/ISIT45174.2021.9518159, note=The copyright for this article belongs to , url=https://www.scopus.com/inward/record.uri?eid=2-s2.0-85115048248&doi=10.11092fISIT45174.2021.9518159&partnerID=40&md5=23365cdf7335cd7a13a3bb0494239adc, affiliation=Indian Institute of Science, Electrical Communication Engineering, Bengaluru, India; Isro Telemetry, Tracking and Command Network, Isro, Bengaluru, India; Space Applications Centre, Indian Space Research Organization, Ahmedabad, India, abstract=Global Navigation Satellite Systems (GNSSs) typically use low-correlation sequences that have length related to the common clock frequency of 10.23 MHz. In particular, operations in the L1 frequency band, of two major GNSS systems, the Global Positioning System (GPS) and BeiDou Navigation Satellite System (BDS), employ spreading sequences having length 10230. In these two systems, the length 10230 is achieved by padding and truncating respectively, a family of Weil sequences having period that is a prime number, either 10223 or 10243. As is well known, either truncation or padding leads in general, to a degradation in correlation performance. In the present paper, we adopt a different approach, and present the design of a family of Interleaved Z₄-linear (IZ4) sequences having period exactly equal to 10230. Closed-form expressions for the correlation properties of the sequence family are included. The balance and even-correlation performance of the new family equals or improves upon the corresponding performance of the GPS and BDS signal sets. In particular, the new IZ4 family has maximum even cross-correlation value that is better by 4.4 dB, than that of the truncated or padded Weil sequences employed in these two systems. The sequence family also turns in comparable odd-correlation performance. The sequences can be generated using a simple, shift-register-based implementation presented here. © 2021 IEEE., keywords=Communication satellites; Information theory; Radio navigation; Satellites; Shift registers, Beidou navigation satellite systems; Closed-form expression; Correlation performance; Correlation properties; Cross-correlation value; Global Navigation Satellite Systems; Satellite navigation; Spreading sequences, Global positioning system, fundingtext1=This research of P. Vijay Kumar is supported by the J C Bose National Fellowship JCB/2017/000017., references=1. Gold, R., Optimal binary sequences for spread spectrum multiplexing (1967) IEEE Trans. Inform. Theory, 13, pp. 619-621. , Oct; 2. Gold, R., Maximal recursive sequences with 3-valued recursive crosscorrelation functions (1968) IEEE Trans. Inform. Theory, 14, pp. 154-156. , Jan; 3. Kasami, T., Weight distribution formula for some class of cyclic codes (1966) Coordinated Science Laboratory, , University of Illinois, Urbana, Tech. Rep. R-285 AD632574; 4. Kasami, T., Weight distribution of bose-chaudhuri-hocquenghem codes (1969) Combinatorial Mathematics and Its Applications, , Chapel Hill, NC: University of North Carolina Press; 5. Olsen, J.D., Scholtz, R.A., Welch, L.R., Bentfunction sequences (1982) IEEE Trans. Inform. Th, pp. 858-864; 6. No, J., Kumar, P.V., A new family of binary pseudorandom sequences having optimal periodic correlation properties and larger linear span (1989) IEEE Transactions on Information Theory, 35 (2), pp. 371-379. , March; 7. Nechaev, A.A., Kerdock code in a cyclic form (1991) Disc. Math. Appl, 1 (4), pp. 365-384; 8. Boztas, S., Kumar, P.V., Binary sequences with goldlike correlation but larger linear span (1994) IEEE Trans. On Inform. Theory, 40, pp. 532-537. , March; 9. Barg, A., Two families of low-correlated sequences (1996) Applicable Algebra in Engineering, Communications and Computing, pp. 433-437; 10. Udaya, P., Siddiqi, M.U., Optimal biphase sequences with larger linear complexity derived from sequences over z4 (1996) IEEE Trans. Inform. Th, pp. 206-216. , Jan; 11. Helleseth, T., Kumar, P.V., Sequences with low correlation (1998) Handbook of Coding Theory, , edited by V. Pless and C. Huffman, Elsevier Science Publishers; 12. Tang, X., Udaya, P., Fan, P., Generalized binary udaya-siddiqi sequences (2007) IEEE Trans. Inform. Theory, 53 (3), pp. 1225-1230. , March; 13. Hammons, A.R., Jr., Vijay Kumar, P., Calderbank, A.R., Sloane, N.J.A., Solè, P., The z4-linearity of z4-linear preparata, goethals and related codes (1994) IEEE Trans. On Inform. Theory, 40, pp. 301-319. , March; 14. Gong, G., New designs for signal sets with low cross correlation, balance property, and large linear span: Gf(p) case (2002) IEEE Transactions on Information Theory, 48 (11), pp. 2847-2867. , Nov; 15. Paterson, K.G., Binary sequence sets with favorable correlations from difference sets and MDS codes (1998) IEEE Transactions on Information Theory, 44, pp. 172-180; 16. Rushanan, J.J., Weil sequences: A family of binary sequences with good correlation properties (2006) IEEE Isit, pp. 1648-1652. , July 9-14; 17. Rushanan, J., The spreading and overlay codes for the l1c signal (2007) Journal of Navigation, 54, pp. 43-51; 18. Rushanan, J.J., (2009) Spreading Code Derived from Weil Sequences, , U.S. Patent No. US 7, 511, 637 B2 Mar 31; 19. Guohua, Z., Quan, Z., Pseudonoise codes constructed by legendre sequence (2001) Electronics Letters, 38 (8), pp. 376-377; 20. (2017) BeiDou Navigation Satellite System Signal in Space Interface Control Document, , China Satellite Navigation Office, Aug; 21. Vijay Kumar, P., Dharmappa, D., Mishra, S., (2021) Method and System for Generating Spreading Codes Based on Interleaved Z4-linear Sequences for Navigation Systems, , Indian patent application number 202041006792, provisional filing on Feb. 17, 2020, complete specification filed on Feb. 15; 22. Vijay Kumar, P., Dharmappa, D., Mishra, S., Method and system for generating spreading codes based on interleaved z4-linear sequences for navigation systems (2021) Pct Filing, , international application number PCT/IN2021/050147, Feb. 16; 23. Welch, L.R., Lower bounds on the minimum correlation of signals (1974) IEEE Transactions on Information Theory; 24. Wallner, S., (2018) Navigation System Using Spreading Codes Based on Pseudo-Random Noise Sequences, , U.S. patent No. US 10, 088, 573 B2, Oct. 2; 25. (2013) Navstar GPS Space Segment/User Segment L1C Interfaces, , Interface specification IS-GPS-800D, " Sep. 24; 26. MacDonald, B.R., (1974) Finite Rings with Identity, , New York: Marcel Dekker; 27. Kumar, P.V., Helleseth, T., Calderbank, A.R., An upper bound for Weil exponential sums over Galois rings and applications (1995) IEEE Trans. On Inform. Theory, 41, pp. 456-468. , March; 28. Yang, K., Helleseth, T., Kumar, P.V., Shanbhag, A., The weight hierarchy of z4-linear codes over z4 (1996) IEEE Trans. Inform. Theory, 42, pp. 1587-1593. , Sep; 29. Weil, A., Sur les courbes algebriques et les varietes qui s'en deduisent (1945) Publ. Inst. Math. Univ. Strasbourg, 7, pp. 1-85; 30. Weil, A., On some exponential sums (1948) Proc. Nat. Acad. Sci, 34, pp. 204-207; 31. Moreno, O., Zhang, Z., Kumar, P.V., Zinoviev, V., New constructions of optimal cyclically permutable constant weight codes (1995) IEEE Trans. On Inform. Theory, 41, pp. 448-455. , March, sponsors=IEEE Information Theory Society; The Institute of Electrical and Electronics Engineers, publisher=Institute of Electrical and Electronics Engineers Inc., issn=21578095, isbn=9781538682098, coden=PISTF, language=English, abbrevsourcetitle=IEEE Int Symp Inf Theor Proc, documenttype=Conference Paper, source=Scopus, @CONFERENCEKanukurthi2021, author=Kanukurthi, B and Bhavana Obbattu, SL and Sekar, S and Tomy, J, title=Locally reconstructable non-malleable secret sharing, journal=Leibniz International Proceedings in Informatics, LIPIcs, year=2021, volume=199, doi=https://doi.org/10.4230/LIPIcs.ITC.2021.11, artnumber=11, note=The copyright for this article belongs to , url=https://www.scopus.com/inward/record.uri?eid=2-s2.0-85115346304&doi=10.42302fLIPIcs.ITC.2021.11&partnerID=40&md5=cbe3de861f3f970f881f1154c221b2f0, affiliation=Department of Computer Science and Automation, Indian Institute of Science, Bangalore, India; Microsoft Research, Bangalore, India; Department of Mathematics, Indian Institute of Science, Bangalore, India, abstract=Non-malleable secret sharing (NMSS) schemes, introduced by Goyal and Kumar (STOC 2018), ensure that a secret m can be distributed into shares m1, · · ·, mn (for some n), such that any t (a parameter â�¤ n) shares can be reconstructed to recover the secret m, any t â�� 1 shares doesn't leak information about m and even if the shares that are used for reconstruction are tampered, it is guaranteed that the reconstruction of these tampered shares will either result in the original m or something independent of m. Since their introduction, non-malleable secret sharing schemes sparked a very impressive line of research. In this work, we introduce a feature of local reconstructability in NMSS, which allows reconstruction of any portion of a secret by reading just a few locations of the shares. This is a useful feature, especially when the secret is long or when the shares are stored in a distributed manner on a communication network. In this work, we give a compiler that takes in any non-malleable secret sharing scheme and compiles it into a locally reconstructable non-malleable secret sharing scheme. To secret share a message consisting of k blocks of length Ï� each, our scheme would only require reading Ï� + log k bits (in addition to a few more bits, whose quantity is independent of Ï� and k) from each party's share (of a reconstruction set) to locally reconstruct a single block of the message. We show an application of our locally reconstructable non-malleable secret sharing scheme to a computational non-malleable secure message transmission scheme in the pre-processing model, with an improved communication complexity, when transmitting multiple messages. © 2021 Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing. All rights reserved., authorkeywords=Information theoretic cryptography; Local reconstructability; Non-malleability; Secret sharing, keywords=Automata theory; Transmissions, Communications networks; Information-theoretic cryptography; Local reconstructability; Non-malleability; Non-malleable; Reconstructable; Secret sharing schemes; Secret-sharing; Secure message transmission; Transmission schemes, Information theory, fundingdetails1=Microsoft ResearchMicrosoft Research, MSR, fundingdetails2=Tata Consultancy ServicesTata Consultancy Services, TCS, fundingtext1=Funding Bhavana Kanukurthi: Microsoft Research Grant. Sruthi Sekar: Research supported in part by TCS Research Grant., references=1. Aggarwal, Divesh, Agrawal, Shashank, Gupta, Divya, Maji, Hemanta K., Pandey, Omkant, Prabhakaran, Manoj, Optimal computational split-state non-malleable codes (2016) Theory of Cryptography - 13th International Conference, pp. 393-417. , TCC 2016-A, Tel Aviv, Israel, January 10-13, Proceedings, Part II, pages 2016; 2. Aggarwal, Divesh, DamgÃ¥rd, Ivan, Nielsen, Jesper Buus, Obremski, Maciej, Purwanto, Erick, Ribeiro, João L., Simkin, Mark, Stronger leakage-resilient and non-malleable secret sharing schemes for general access structures Advances in Cryptology - CRYPTO 2019 - 39th Annual International Cryptology Conference, Santa Barbara, CA, USA, August 18-22, 2019, Proceedings, Part II, volume 11693 of Lecture Notes in Computer Science, pp. 510-539. , Alexandra Boldyreva and Daniele Micciancio, editors, pages Springer, 2019; 3. Badrinarayanan, Saikrishna, Srinivasan, Akshayaram, Revisiting non-malleable secret sharing Advances in Cryptology - EURO-CRYPT 2019 - 38th Annual International Conference on the Theory and Applications of Cryptographic Techniques, Darmstadt, Germany, May 19-23, 2019, Proceedings, Part I, volume 11476 of Lecture Notes in Computer Science, pp. 593-622. , Yuval Ishai and Vincent Rijmen, editors, pages Springer, 2019; 4. Bellare, Mihir, Namprempre, Chanathip, Authenticated encryption: Relations among notions and analysis of the generic composition paradigm (2000) International Conference on the Theory and Application of Cryptology and Information Security, pp. 531-545. , Springer; 5. Bellare, Mihir, Rogaway, Phillip, Encode-then-encipher encryption: How to exploit nonces or redundancy in plaintexts for efficient cryptography (2000) International Conference on the Theory and Application of Cryptology and Information Security, pp. 317-330. , Springer; 6. Blakley, G.R., Safeguarding cryptographic keys (1979) Proceedings of the 1979 AFIPS National Computer Conference, pp. 313-317. , Monval, NJ, USA, AFIPS Press; 7. Brian, Gianluca, Faonio, Antonio, Obremski, Maciej, Simkin, Mark, Venturi, Daniele, Non-malleable secret sharing against bounded joint-tampering attacks in the plain model Advances in Cryptology - CRYPTO 2020 - 40th Annual International Cryptology Conference, CRYPTO 2020, Santa Barbara, CA, USA, August 17-21, 2020, Proceedings, Part III, volume 12172 of Lecture Notes in Computer Science, pp. 127-155. , Daniele Micciancio and Thomas Ristenpart, editors, pages Springer, 2020; 8. Brian, Gianluca, Faonio, Antonio, Venturi, Daniele, Continuously non-malleable secret sharing for general access structures Theory of Cryptography - 17th International Conference, TCC 2019, Nuremberg, Germany, December 1-5, 2019, Proceedings, Part II, volume 11892 of Lecture Notes in Computer Science, pp. 211-232. , Dennis Hofheinz and Alon Rosen, editors, pages Springer, 2019; 9. Chandran, Nishanth, Kanukurthi, Bhavana, Obbattu, Sai Lakshmi Bhavana, Sekar, Sruthi, Constant rate (non-malleable) secret sharing schemes tolerating joint adaptive leakage (2020) Cryptology ePrint Archive, , https://eprint.iacr.org/2020/1252, Report 2020/1252; 10. Chandran, Nishanth, Kanukurthi, Bhavana, Ostrovsky, Rafail, Locally updatable and locally decodable codes (2014) Theory of Cryptography, pp. 489-514. , Yehuda Lindell, editor, pages Berlin, Heidelberg, Springer Berlin Heidelberg; 11. Chandran, Nishanth, Kanukurthi, Bhavana, Raghuraman, Srinivasan, Information-theoretic local non-malleable codes and their applications Theory of Cryptography - 13th International Conference, TCC 2016-A, Tel Aviv, Israel, January 10-13, 2016, Proceedings, Part II, volume 9563 of Lecture Notes in Computer Science, pp. 367-392. , Eyal Kushilevitz and Tal Malkin, editors, pages Springer, 2016; 12. Chattopadhyay, Eshan, Goodman, Jesse, Goyal, Vipul, Li, Xin, Leakage-resilient extractors and secret-sharing against bounded collusion protocols (2020) Electron. Colloquium Comput. Complex, 27, p. 60. , https://eccc.weizmann.ac.il/report/2020/060; 13. Coretti, Sandro, Faonio, Antonio, Venturi, Daniele, Rate-optimizing compilers for continuously non-malleable codes Applied Cryptography and Network Security - 17th International Conference, ACNS 2019, Bogota, Colombia, June 5-7, 2019, Proceedings, volume 11464 of Lecture Notes in Computer Science, pp. 3-23. , Robert H. Deng, Valérie Gauthier-Umaña, Martín Ochoa, and Moti Yung, editors, pages Springer, 2019; 14. Dachman-Soled, Dana, Kulkarni, Mukul, Shahverdi, Aria, Local non-malleable codes in the bounded retrieval model (2018) Public-Key Cryptography - PKC 2018, pp. 281-311. , Michel Abdalla and Ricardo Dahab, editors, pages Cham, Springer International Publishing; 15. Dachman-Soled, Dana, Liu, Feng-Hao, Shi, Elaine, Zhou, Hong-Sheng, Locally decodable and updatable non-malleable codes and their applications (2015) Theory of Cryptography, pp. 427-450. , Yevgeniy Dodis and Jesper Buus Nielsen, editors, pages Berlin, Heidelberg, Springer Berlin Heidelberg; 16. Dolev, Danny, Dwork, Cynthia, Waarts, Orli, Yung, Moti, Perfectly secure message transmission (1993) J. ACM, 40 (1), pp. 17-47; 17. Faonio, Antonio, Venturi, Daniele, Non-malleable secret sharing in the computational setting: Adaptive tampering, noisy-leakage resilience, and improved rate Advances in Cryptology - CRYPTO 2019 - 39th Annual International Cryptology Conference, Santa Barbara, CA, USA, August 18-22, 2019, Proceedings, Part II, volume 11693 of Lecture Notes in Computer Science, pp. 448-479. , Alexandra Boldyreva and Daniele Micciancio, editors, pages Springer, 2019; 18. Goyal, Vipul, Kumar, Ashutosh, Non-malleable secret sharing (2018) Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing, STOC 2018, pp. 685-698. , Ilias Diakonikolas, David Kempe, and Monika Henzinger, editors, Los Angeles, CA, USA, June 25-29, pages ACM, 2018; 19. Goyal, Vipul, Kumar, Ashutosh, Non-malleable secret sharing for general access structures (2018) Advances in Cryptology - CRYPTO 2018, pp. 501-530. , Hovav Shacham and Alexandra Boldyreva, editors, pages Cham, Springer International Publishing; 20. Katz, Jonathan, Lindell, Yehuda, (2014) Introduction to modern cryptography, , CRC press; 21. Katz, Jonathan, Trevisan, Luca, On the efficiency of local decoding procedures for error-correcting codes (2000) Proceedings of the Thirty-Second Annual ACM Symposium on Theory of Computing, STOC'00, pp. 80-86. , page New York, NY, USA, Association for Computing Machinery; 22. Katz, Jonathan, Yung, Moti, Unforgeable encryption and chosen ciphertext secure modes of operation (2000) International Workshop on Fast Software Encryption, pp. 284-299. , Springer; 23. Kishore, Ravi, Kumar, Ashutosh, Vanarasa, Chiranjeevi, Srinathan, Kannan, On the price of proactivizing round-optimal perfectly secret message transmission (2018) IEEE Trans. Inf. Theory, 64 (2), pp. 1404-1422; 24. Krawczyk, Hugo, Secret sharing made short Advances in Cryptology - CRYPTO'93, 13th Annual International Cryptology Conference, Santa Barbara, California, USA, August 22-26, 1993, Proceedings, volume 773 of Lecture Notes in Computer Science, pp. 136-146. , Douglas R. Stinson, editor, pages Springer, 1993; 25. Kumar, Ashutosh, Meka, Raghu, Sahai, Amit, Leakage-resilient secret sharing against colluding parties (2019) 60th IEEE Annual Symposium on Foundations of Computer Science, FOCS 2019, pp. 636-660. , David Zuckerman, editor, Baltimore, Maryland, USA, November 9-12, pages IEEE Computer Society, 2019; 26. Kumar, Ashutosh, Meka, Raghu, Zuckerman, David, Bounded collusion protocols, cylinder-intersection extractors and leakage-resilient secret sharing (2020) Electron. Colloquium Comput. Complex, 27, p. 55. , https://eccc.weizmann.ac.il/report/2020/055; 27. Kurosawa, Kaoru, Suzuki, Kazuhiro, Truly efficient 2-round perfectly secure message transmission scheme (2009) IEEE Trans. Inf. Theory, 55 (11), pp. 5223-5232; 28. Lin, Fuchun, Cheraghchi, Mahdi, Guruswami, Venkatesan, Safavi-Naini, Reihaneh, Wang, Huaxiong, Non-malleable secret sharing against affine tampering (2019), CoRR, abs/1902.06195, arXiv:1902.06195; 29. Shamir, Adi, How to share a secret (1979) Communications of the ACM, 22 (11), pp. 612-613; 30. Srinathan, K., Narayanan, Arvind, Pandu Rangan, C., Optimal perfectly secure message transmission Advances in Cryptology - CRYPTO 2004, 24th Annual International CryptologyConference, Santa Barbara, California, USA, August 15-19, 2004, Proceedings, volume 3152 of Lecture Notes in Computer Science, pp. 545-561. , Matthew K. Franklin, editor, pages Springer, 2004; 31. Srinivasan, Akshayaram, Vasudevan, Prashant Nalini, Leakage resilient secret sharing and applications (2019) Advances in Cryptology - CRYPTO 2019, pp. 480-509. , Alexandra Boldyreva and Daniele Micciancio, editors, pages Cham, Springer International Publishing; 32. Wang, Yongge, Desmedt, Yvo, Perfectly secure message transmission revisited (2008) IEEE Trans. Inf. Theory, 54 (6), pp. 2582-2595, correspondenceaddress1=Kanukurthi, B.; Department of Computer Science and Automation, India; Bhavana Obbattu, S.L.; Microsoft ResearchIndia; Sekar, S.; Department of Mathematics, India; Tomy, J.; Department of Computer Science and Automation, India, editor=Tessaro S., publisher=Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing, issn=18688969, isbn=9783959771979, language=English, abbrevsourcetitle=Leibniz Int. Proc. Informatics, LIPIcs, documenttype=Conference Paper, source=Scopus, @BOOKSetturu20211, author=Setturu, B and Rajan, KS and Ramachandra, TV, title=Modeling Forest Landscape Dynamics, journal=Modeling Forest Landscape Dynamics, year=2021, pages=1-249, note=The copyright for this article belongs to , url=https://www.scopus.com/inward/record.uri?eid=2-s2.0-85115213459&partnerID=40&md5=dd597df5a962a12d9a8e6527a4ba51b1, affiliation=Energy and Wetlands Research Group (EWRG), Centre for Ecological Sciences, Indian Institute of Science, Bangalore, India; Lab for Spatial Informatics (LSI), International Institute of Information Technology, Andhra Pradesh, India; Energy and Wetlands Research Group (EWRG), Convener of Environmental Information System (ENVIS), Centre for Ecological Sciences (CES), Bengaluru, India, abstract=The landscape is a mosaic of ecosystem elements, which changes in size, shape, spatial arrangement, and quality of the patches/elements due to complex, multi-scalar processes which influence the ecosystem's biotic components. The changes in the abiotic and biotic assets of a landscape are referred to as landscape dynamics. Changes in the structure of the landscape will have implications on ecosystem functions and processes. Landscape dynamics driven by land use land cover (LULC) changes due to anthropogenic activities are affecting ecology, biodiversity, hydrological regime, and hence people's livelihood. There has been increasing apprehensions about environmental degradation, depletion of natural resources due to uncontrolled anthropogenic activities, and their consequences on long-term sustainability of socio-economic systems around the world. This necessitates an understanding of landscape dynamics and the visualization of likely changes for evolving appropriate strategies for prudent management of natural resources. This publication provides insights to LULC dynamics of forest ecosystems, which will help in the prudent management of ecosystems. © 2021 by Nova Science Publishers, Inc. All rights reserved., references=1. Antrop, M., Why landscapes of the past are important for the future (2005) Landscape and urban planning, 70 (1-2), pp. 21-34; 2. Adhikari, S., Southworth, J., Simulating forest cover changes of Bannerghatta National Park based on a CA-Markov model: a remote sensing approach (2012) Remote Sensing, 4 (10), pp. 3215-3243; 3. Agarwal, C., Green, G.M., Grove, J.M., Evans, T.P., Schweik, C.M., A review and assessment of land-use change models. Dynamics of space, time, and human choice. Bloomington and South Burlington. Center for the Study of Institutions, Population, and Environmental Change, Indiana University and USDA Forest Service (2001) CIPEC Collaborative Report Series, p. 1; 4. Arsanjani, J.J., Kainz, W., Mousivand, A.J., Tracking dynamic land-use change using spatially explicit Markov Chain based on cellular automata: the case of Tehran (2011) International Journal of Image and Data Fusion, 2 (4), pp. 329-345; 5. Areendran, G., Raj, K., Mazumdar, S., Munsi, M., Govil, H., Sen, P.K., Geospatial modeling to assess elephant habitat suitability and corridors in northern Chhattisgarh, India (2011) Tropical Ecology, 52 (3), pp. 275-283; 6. Armenteras, D., Rudas, G., Rodriguez, N., Sua, S., Romero, M., Patterns and causes of deforestation in the Colombian Amazon (2006) Ecological indicators, 6 (2), pp. 353-368; 7. Arts, B., Buizer, M., Horlings, L., Ingram, V., van Oosten, C., Opdam, P., Landscape Approaches: A State-of-the-Art Review (2017) Annual Review of Environment and Resources, 42, pp. 439-463; 8. Atkinson, P.M., Lewis, P., Geostatistical classification for remote sensing: an introduction (2000) Computers & Geosciences, 26 (4), pp. 361-371; 9. Baker, W.L., A review of models of landscape change (1989) Landscape ecology, 2 (2), pp. 111-133; 10. Barange, M., Beaugrand, G., Harris, R., Perry, R.I., Scheffer, M., Werner, F., Regime shifts in marine ecosystems: detection, prediction and management (2008) Trends in Ecology & Evolution, 23 (7), pp. 402-409; 11. Bates, P.J.J., Harrison, D.L., (2000) Bats of the Indian subcontinent, , ETI, University of Amsterdam; 12. Batty, M., Torrens, P.M., Modeling complexity: The limits to prediction (2001) Cybergeo, p. 21; 13. Beinat, E., Value functions for environmental management (1997) Value Functions for Environmental Management, pp. 77-106. , Springer, Dordrecht; 14. Bernasconi, M., Choirat, C., Seri, R., The analytic hierarchy process and the theory of measurement (2010) Management Science, 56 (4), pp. 699-711; 15. Bharath, H.A., Chandan, M.C., Vinay, S., Ramachandra, T.V., Modelling urban dynamics in rapidly urbanising Indian cities (2018) The Egyptian Journal of Remote Sensing and Space Science, 21 (3), pp. 201-210; 16. Bhat, P., Hegde, G., Hegde, G.R., Ethnomedicinal practices in different communities of Uttara Kannada district of Karnataka for treatment of wounds (2012) Journal of ethnopharmacology, 143 (2), pp. 501-514; 17. Bogaert, J., Ceulemans, R., Salvador-Van Eysenrode, D., Decision tree algorithm for detection of spatial processes in landscape transformation (2004) Environmental management, 33 (1), pp. 62-73; 18. Behera, M.D., Borate, S.N., Panda, S.N., Behera, P.R., Roy, P.S., Modelling and analyzing the watershed dynamics using Cellular Automata (CA)-Markov model-A geo-information based approach (2012) Journal of earth system science, 121 (4), pp. 1011-1024; 19. Brose, U., Martinez, N.D., Williams, R.J., Estimating species richness: sensitivity to sample coverage and insensitivity to spatial patterns (2003) Ecology, 84 (9), pp. 2364-2377; 20. Briassoulis, H., Analysis of Land Use Change: Theoretical and Modeling Approaches (2000) The Web Book of Regional Science, 410. , Regional Research Institute, West Virginia University; 21. Bürgi, M., Hersperger, A.M., Schneeberger, N., Driving forces of landscape change-current and new directions (2004) Landscape ecology, 19 (8), pp. 857-868; 22. Bürgi, M., Straub, A., Gimmi, U., Salzmann, D., The recent landscape history of Limpach valley, Switzerland: considering three empirical hypotheses on driving forces of landscape change (2010) Landscape Ecology, 25 (2), pp. 287-297; 23. Cagnolo, L., Cabido, M., Valladares, G., Plant species richness in the Chaco Serrano Woodland from central Argentina: ecological traits and habitat fragmentation effects (2006) Biological conservation, 132 (4), pp. 510-519; 24. Carpenter, S.R., Ecological Futures: Building an Ecology of the Long Now1 (2002) Ecology, 83 (8), pp. 2069-2083; 25. Chandran, M.D.S., Rao, G.R., Gururaja, K.V., Ramachandra, T.V., Ecology of the swampy relic forests of Kathalekan from Central Western Ghats, India (2010) Bioremediation, Biodiversity and Bioavailability, 4 (1), pp. 54-68; 26. Chang, N.B., Parvathinathan, G., Breeden, J.B., Combining GIS with fuzzy multicriteria decision-making for landfill siting in a fast-growing urban region (2008) Journal of environmental management, 87 (1), pp. 139-153; 27. Chaturvedi, R.K., Gopalakrishnan, R., Jayaraman, M., Bala, G., Joshi, N.V., Sukumar, R., Ravindranath, N.H., Impact of climate change on Indian forests: a dynamic vegetation Modeling approach (2011) Mitigation and Adaptation Strategies for Global Change, 16 (2), pp. 119-142; 28. Chitale, V.S., Behera, M.D., Roy, P.S., Future of endemic flora of biodiversity hotspots in India (2014) PLoS One, 9 (12), p. e115264; 29. Cowling, R.M., Egoh, B., Knight, A.T., O'Farrell, P.J., Reyers, B., Rouget'll, M., Roux, D.J., Wilhelm-Rechman, A., An operational model for mainstreaming ecosystem services for implementation (2008) Proc Natl Acad Sci USA, 105, pp. 9483-9488; 30. Daniels, R.R., Joshi, N.V., Gadgil, M., Changes in the bird fauna of Uttara Kannada, India, in relation to changes in land use over the past century (1990) Biological Conservation, 52 (1), pp. 37-48; 31. Daniels, R.R., (2005) Amphibians of peninsular India, , Universities Press; 32. Daniels, R.R., Vencatesan, J., (2008) Western Ghats: Biodiversity, People, Conservation, , Rupa & Company; 33. Daniel, C.J., Frid, L., Sleeter, B.M., Fortin, M.J., Stateand-transition simulation models: a framework for forecasting landscape change (2016) Methods in Ecology and Evolution, 7 (11), pp. 1413-1423; 34. de Leeuw, J., Georgiadou, Y., Kerle, N., de Gier, A., Inoue, Y., Ferwerda, J., Smies, M., Narantuya, D., The function of remote sensing in support of environmental policy (2010) Remote sensing, 2 (7), pp. 1731-1750; 35. Duda, R.O., Hart, P.E., Stork, D.G., (2012) Pattern classification, , John Wiley & Sons; 36. Echeverria, C., Coomes, D.A., Hall, M., Newton, A.C., Spatially explicit models to analyze forest loss and fragmentation between 1976 and 2020 in southern Chile (2008) Ecological Modeling, 212 (3), pp. 439-449; 37. Esty, D.C., Environmental protection in the information age (2004) NYUL Rev, 79, p. 115; 38. Evans, T.P., Manire, A., de Castro, F., Brondizio, E., McCracken, S., A dynamic model of household decision-making and parcel level landcover change in the Eastern Amazon (2001) Ecological Modeling, 143, pp. 95-113; 39. (2011) State of the World's Forests, , Research and Extension, FAO, Viale delle Terme di Caracalla, 00153. Rome, Italy; 40. (2016) State of the World's Forests. Forests and Agriculture: Land-Use Challenges and Opportunities, Viale delle Terme di Caracalla, 00153, , Rome, Italy; 41. Filatova, T., Polhill, J.G., van Ewijk, S., Regime shifts in coupled socio-environmental systems: review of Modeling challenges and approaches (2006) Environment Modeling Softwate, 75, pp. 333-347; 42. Foley, J.A., DeFries, R., Asner, G.P., Barford, C., Bonan, G., Carpenter, S.R., Chapin, F.S., Helkowski, J.H., Global consequences of land use (2005) Science, 309 (5734), pp. 570-574; 43. Forman, R.T.T., Gordron, M., (1986) Landscape Ecology, , JohnWiley & Sons, New York; 44. Fraser, R.H., Olthof, I., Pouliot, D., Monitoring land cover change and ecological integrity in Canada's national parks (2009) Remote Sensing of Environment, 113 (7), pp. 1397-1409; 45. Fu, B.J., Zhang, Q.J., Chen, L.D., Zhao, W.W., Gulinck, H., Liu, G.B., Yang, Q.K., Zhu, Y.G., Temporal change in land use and its relationship to slope degree and soil type in a small catchment on the Loess Plateau of China (2006) Catena, 65 (1), pp. 41-48; 46. Fuller, D.O., Forest fragmentation in Loudoun County, Virginia, USA evaluated with multitemporal Landsat imagery (2001) Landscape Ecology, 16 (7), pp. 627-642; 47. Gadgil, M., Chandran, M.S., Environmental impact of forest based industries on the evergreen forests of Uttara Kannada district: A Case Study (1989) Final report,' submitted to Department of Ecology and Environment. Government of Karnataka; 48. Gadgil, M., Daniels, R.R., Ganeshaiah, K.N., Prasad, S.N., Murthy, M.S.R., Jha, C.S., Ramesh, B.R., Subramanian, K.A., Mapping ecologically sensitive, significant and salient areas of Western Ghats: proposed protocols and methodology (2011) Current Science, 100 (2), pp. 175-182; 49. Garrido, P., Elbakidze, M., Angelstam, P., Plieninger, T., Pulido, F., Moreno, G., Stakeholder perspectives of wood-pasture ecosystem services: A case study from Iberian dehesas (2017) Land Use Policy, 60, pp. 324-333; 50. Gaucherel, C., Houet, T., Preface to the selected papers on spatially explicit landscape Modeling: current practices and challenges (2009) Ecological Modeling, 220 (24), pp. 3477-3480; 51. Gibon, A., Sheeren, D., Monteil, C., Ladet, S., Balent, G., Modeling and simulating change in reforesting mountain landscapes using a social-ecological framework (2010) Landscape Ecology, 25 (2), pp. 267-285; 52. Giriraj, A., Irfan-Ullah, M., Murthy, M.S.R., Beierkuhnlein, C., Modeling spatial and temporal forest cover change patterns (1973-2020): A case study from South Western Ghats (India) (2008) Sensors, 8 (10), pp. 6132-6153; 53. Girod, B., Wiek, A., Mieg, H., Hulme, M., The evolution of the IPCC's emissions scenarios (2009) Environmental science & policy, 12 (2), pp. 103-118; 54. Goldstein, B.A., Polley, E.C., Briggs, F.B., Random forests for genetic association studies (2011) Statistical applications in genetics and molecular biology, 10 (1); 55. Green, B.H., Simmons, E.A., Woltjer, I., (1996) Landscape conservation: Some steps towards developing a new conservation dimension, , University of London, Department of Agriculture, Horticulture and Environment, Wye College, Ashford, Kent, UK; 56. Groeneveld, J., Müller, B., Buchmann, C.M., Dressler, G., Guo, C., Hase, N., Hoffmann, F., Liebelt, V., Theoretical foundations of human decision-making in agent-based land use models-A review (2017) Environmental Modeling & software, 87, pp. 39-48; 57. Gupta, R.K., Prasad, T.S., Rao, P.K., Manikavelu, P.B., Problems in upscaling of high resolution remote sensing data to coarse spatial resolution over land surface (2000) Advances in Space Research, 26 (7), pp. 1111-1121; 58. Hansen, M.C., Loveland, T.R., A review of large area monitoring of land cover change using Landsat data (2012) Remote sensing of Environment, 122, pp. 66-74; 59. Hansen, M.C., Potapov, P.V., Moore, R., Hancher, M., Turubanova, S., Tyukavina, A., Thau, D., Kommareddy, A., High-resolution global maps of 21st-century forest cover change (2013) Science, 342 (6160), pp. 850-853; 60. Harper, K.A., Macdonald, S.E., Burton, P.J., Chen, J., Brosofske, K.D., Saunders, S.C., Euskirchen, E.S., Esseen, P.A., Edge influence on forest structure and composition in fragmented landscapes (2005) Conservation Biology, 19 (3), pp. 768-782; 61. Heistermann, M., Muller, C., Ronneberger, K., Land in sight?: Achievements, deficits and potentials of continental to global scale land-use Modeling (2006) Agriculture, Ecosystems & Environment, 114 (2-4), pp. 141-158; 62. Holderieath, J., Spatiotemporal management under heterogeneous damage and uncertain parameters. An agent-based approach (2016) 2016 Annual Meeting, July 31-August 2, 2016, Boston, Massachusetts, , (No. 235850). Agricultural and Applied Economics Association; 63. Holland, E.P., Aegerter, J.N., Dytham, C., Smith, G.C., Landscape as a model: the importance of geometry (2007) PLoS Computational Biology, 3 (10), p. e200; 64. Hutchinson, J.J., Campbell, C.A., Desjardins, R.L., Some perspectives on carbon sequestration in agriculture (2007) Agricultural and forest meteorology, 142 (2-4), pp. 288-302; 65. Ipcc, W., (2000) Special report on emissions scenarios. Intergovernmental panel on climate change special reports on climate change, p. 570. , Cambridge University Press, Cambridge; 66. Summary for policymakers (2007) Climate Change 2007: Impacts, Adaptation and Vulnerability, pp. 7-22. , Parry, M. L., Canziani, O. F., Palutikof, J. P., van der Linden, P. J., Hanson, C. E. (Eds.). Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, UK; 67. (2008) Towards New Scenarios for Analysis of Emissions, Climate Change, Impacts, and Response Strategies, , In: Moss, R., Babiker, M., Brinkman, S., Calvo, E., Carter, T., Edmonds, J., Elgizouli, I., Emori, S., Erda, L., Hibbard, K., Jones, R., Kainuma, M., Kelleher, J., Lamarque, J. F., Manning, M., Matthews, B., Meehl, J., Meyer, L., Mitchell, J., Nakicenovic, N., O'Neill, B., Pichs, R., Riahi, K., Rose, S., Runci, P., Stouffer, R., Vuuren, D. v., Weyant, J., Wilbanks, T., Ypersele, J. P. v., Zurek, M. (Eds.), IPCC, Geneva; 68. Irwin, E.G., Geoghegan, J., Theory, data, methods: developing spatially explicit economic models of land use change (2001) Agriculture, Ecosystems & Environment, 85 (1), pp. 7-24; 69. Joshi, A.R., Dinerstein, E., Wikramanayake, E., Anderson, M.L., Olson, D., Jones, B.S., Seidensticker, J., Davis, C.L., Tracking changes and preventing loss in critical tiger habitat (2016) Science advances, 2 (4), p. e1501675; 70. Kamath, S.U., (1985) Karnataka State Gazetteer, Uttara Kannada District, , Government of Karnataka Press; 71. Kennedy, R.E., Townsend, P.A., Gross, J.E., Cohen, W.B., Bolstad, P., Wang, Y.Q., Adams, P., Remote sensing change detection tools for natural resource managers: Understanding concepts and tradeoffs in the design of landscape monitoring projects (2009) Remote sensing of environment, 113 (7), pp. 1382-1396; 72. Kenyon, W., Hill, G., Shannon, P., Scoping the role of agriculture in sustainable flood management (2008) Land Use Policy, 25 (3), pp. 351-360; 73. Keshavarzi, A., Land Suitability Evaluation using fuzzy continuous classification (A Case Study: Ziaran Region) (2010) Modern Applied Science, 4, pp. 72-81; 74. Keshtkar, H., Voigt, W., A spatiotemporal analysis of landscape change using an integrated Markov chain and cellular automata models (2016) Modeling Earth Systems and Environment, 2 (1), p. 10; 75. Kinzig, A.P., Ryan, P., Etienne, M., Allison, H., Elmqvist, T., Walker, B.H., Resilience and regime shifts: assessing cascading effects (2006) Ecology and society, 11 (1); 76. Kok, K., Farrow, A., Veldkamp, A., Verburg, P.H., A method and application of multi-scale validation in spatial land use models (2001) Agriculture, Ecosystems & Environment, 85 (1), pp. 223-238; 77. Kordi, M., Brandt, S.A., Effects of increasing fuzziness on analytic hierarchy process for spatial multicriteria decision analysis (2012) Computers, Environment and Urban Systems, 36 (1), pp. 43-53; 78. Krishnanjan, P., Arya, V.S., Sudhakar, S., Biodiversity hotspot Modeling and temporal analysis of Meghalaya using Remote sensing technique (2014) International Journal of Environmental Sciences, 4 (5), pp. 772-785; 79. Kuèas, A.N., Trakimas, G., Balèiauskas, N.A.S., Vaitkus, G., Multi-scale analysis of forest fragmentation in Lithuania (2011) Baltic Forest, 17 (1), pp. 128-135; 80. Kumar, U., Kerle, N., Punia, M., Ramachandra, T.V., Mining land cover information using multilayer perceptron and decision tree from MODIS data (2010) Journal of the Indian Society of Remote Sensing, 38 (4), pp. 592-603; 81. Kumar, R., Nandy, S., Agarwal, R., Kushwaha, S.P.S., Forest cover dynamics analysis and prediction modeling using logistic regression model (2014) Ecological Indicators, 45, pp. 444-455; 82. Lambin, E.F., Turner, B.L., Geist, H.J., Agbola, S.B., Angelsen, A., Bruce, J.W., Coomes, O.T., George, P., The causes of land-use and land-cover change: moving beyond the myths (2001) Global environmental change, 11 (4), pp. 261-269; 83. Lambin, E.F., Geist, H., Lepers, E., Dynamics of land use and land cover change in tropical regions (2003) Environent and Resources, 28, pp. 205-241; 84. Laurance, W.F., Lovejoy, T.E., Vasconcelos, H.L., Bruna, E.M., Didham, R.K., Stouffer, P.C., Gascon, C., Sampaio, E., Ecosystem decay of Amazonian forest fragments: a 22-year investigation (2002) Conservation Biology, 16 (3), pp. 605-618; 85. Li, Y., Liao, Q.F., Li, X., Liao, S.D., Chi, G.B., Peng, S.L., Towards an operational system for regional-scale rice yield estimation using a time-series of Radarsat Scan SAR images (2003) International Journal of Remote Sensing, 24, pp. 4207-4220; 86. Li, Z., Liu, W., Zheng, F., The land use changes and its relationship with topographic factors in the Jing river catchment on the Loess Plateau of China (2013) SpringerPlus, 2, p. S3. , December. Springer International Publishing; 87. Lillesand, T., Kiefer, R.W., Chipman, J., (2014) Remote sensing and image interpretation, , John Wiley & Sons; 88. Lindenmayer, D., Hobbs, R.J., Montague-Drake, R., Alexandra, J., Bennett, A., Burgman, M., Cale, P., Driscoll, D., A checklist for ecological management of landscapes for conservation (2008) Ecology letters, 11 (1), pp. 78-91; 89. Liu, C., Frazier, P., Kumar, L., Comparative assessment of the measures of thematic classification accuracy (2007) Remote sensing of environment, 107 (4), pp. 606-616; 90. Liu, Y., Modeling sustainable urban growth in a rapidly urbanising region using a fuzzy-constrained cellular automata approach (2012) International Journal of Geographical Information Science, 26 (1), pp. 151-167; 91. Maes, J., Paracchini, M.L., Zulian, G., Dunbar, M.B., Alkemade, R., Synergies and trade-offs between ecosystem service supply, biodiversity, and habitat conservation status in Europe (2012) Biological conservation, 155, pp. 1-12; 92. Martinuzzi, S., Radeloff, V.C., Joppa, L.N., Hamilton, C.M., Helmers, D.P., Plantinga, A.J., Lewis, D.J., Scenarios of future land use change around United States' protected areas (2015) Biological Conservation, 184, pp. 446-455; 93. Mas, J.F., Kolb, M., Paegelow, M., Olmedo, M.T.C., Houet, T., Inductive pattern-based land use/cover change models: A comparison of four software packages (2014) Environmental Modeling & Software, 51, pp. 94-111; 94. Matthews, R., Gilbert, N., Roach, A., Polhill, J., Gotts, N., Agent-based land-use models: a review of applications (2007) Landscape Ecology, 22, pp. 1447-1459; 95. Messier, C., Puettmann, K., Filotas, E., Coates, D., Dealing with non-linearity and uncertainty in forest management (2016) Current Forestry Reports, 2 (2), pp. 150-161; 96. Mesta, P.N., Bharath, S., Subash Chandran, M.D., Rajan, K.S., Ramachandra, T.V., Inventorying, mapping and monitoring of mangroves towards sustainable management of West Coast, India (2014) J Geophysics Remote Sensing, 3, pp. 130-138; 97. Meyer, W.B., Past and Present Land-use and Land-cover in the U.S. A (1995) Consequences, 1 (1), pp. 25-33; 98. Mladenoff, D.J., White, M.A., Pastor, J., Crow, T.R., Comparing spatial pattern in unaltered old-growth and disturbed forest landscapes (1993) Ecological Applications, 3, pp. 294-306; 99. (2000) Report of the Committee on identifying parameters for designating Ecologically Sensitive Areas in India, , (Pronab Sen Committee Report); 100. Moen, J., Keskitalo, E.C.H., Interlocking panarchies in multi-use boreal forests in Sweden (2010) Ecology and Society, 15 (3); 101. Mondal, M.S., Sharma, N., Garg, P.K., Kappas, M., Statistical independence test and validation of CA Markov land use land cover (LULC) prediction results (2016) The Egyptian Journal of Remote Sensing and Space Science, 19 (2), pp. 259-272; 102. Moran, E., Ojima, D., Buchmann, N., Canadell, J., Graumlich, L., Jackson, R., Jaramillo, V., Murdiyarso, D., GLP (2005): Science Plan and Implementation Strategy (2005) IGPB, , Report No. 53/IHDP Report No. 19; 103. Mosadeghi, R., Warnken, J., Tomlinson, R., Mirfenderesk, H., Comparison of Fuzzy-AHP and AHP in a spatial multi-criteria decision making model for urban land-use planning (2015) Computers Environment Urban System, 49, pp. 54-56; 104. Muddle, D., Briggs, K., Dashwood, C., Dijkstra, T., The influence of slope geology on landslide occurrence during extreme rainfall (2015) Proceedings of XVI European Conference on Soil Mechanics and Geotechnical Engineering, , Edinburgh, Scotland, September; 105. Mukhopadhaya, S., Land use and Land Cover Change Modeling using CA-Markov Case Study: Deforestation Analysis of Doon Valley (2016) Journal of Agroecology and Natural Resource Management, 3 (1), pp. 1-5; 106. Munroe, D.K., Croissant, C., York, A.M., Land use policy and landscape fragmentation in an urbanizing region: Assessing the impact of zoning (2005) Applied Geography, 25 (2), pp. 121-141; 107. Myllyviita, T., Hujala, T., Kangas, A., Leskinen, P., Decision support in assessing the sustainable use of forests and other natural resources-a comparative review (2011) The Open Forest Science Journal, 4, pp. 24-24; 108. Nakicenovic, N., Alcamo, J., Grubler, A., Riahi, K., Roehrl, R.A., Rogner, H.H., Victor, N., (2000) Special report on emissions scenarios (SRES), a special report of Working Group III of the intergovernmental panel on climate change, , Cambridge University Press; 109. (1999) Global environmental change: Research pathways for the next decade, , National Academies Press; 110. Committee on Grand Challenges in Environmental Sciences (2001) Grand challenges in environmental sciences, , National Academy Press; 111. (2014) Advancing Land Change Modeling: Opportunities and Research Requirements, , The National Academies Press: Washington, DC, USA, 2014; 112. Olofsson, P., Foody, G.M., Herold, M., Stehman, S.V., Woodcock, C.E., Wulder, M.A., Good practices for estimating area and assessing accuracy of land change (2014) Remote Sensing of Environment, 148, pp. 42-57; 113. Opdam, P., Steingröver, E., van Rooij, S., Ecological networks: a spatial concept for multi-actor planning of sustainable landscapes (2006) Landscape and urban planning, 75 (3-4), pp. 322-332; 114. Ostapowicz, K., Vogt, P., Riitters, K.H., Kozak, J., Estreguil, C., Impact of scale on morphological spatial pattern of forest (2008) Landscape ecology, 23 (9), pp. 1107-1117; 115. Overmars, K.P., Verburg, P.H., Analysis of land use drivers at the watershed and household level: Linking two paradigms at the Philippine forest fringe (2005) International Journal of Geographical information science, 19 (2), pp. 125-152; 116. Paloniemi, R., Tikka, P.M., Ecological and social aspects of biodiversity conservation on private lands (2008) Environmental Science & Policy, 11 (4), pp. 336-346; 117. Parker, D.C., Manson, S.M., Janssen, M.A., Hoffmann, M.J., Deadman, P., Multi-agent systems for the simulation of landuse and land-cover change: A review (2003) Annals of the association of American Geographers, 93 (2), pp. 314-337; 118. Payés, A.C.L.M., Pavão, T., dos Santos, R.F., The conservation success over time: Evaluating the land use and cover change in a protected area under a long re-categorization process (2013) Land Use Policy, 30 (1), pp. 177-185; 119. Plexida, S.G., Sfougaris, A.I., Ispikoudis, I.P., Papanastasis, V.P., Selecting landscape metrics as indicators of spatial heterogeneity-A comparison among Greek landscapes (2014) International Journal of Applied Earth Observation and Geoinformation, 26, pp. 26-35; 120. Poelmans, L., van Rompaey, A., Complexity and performance of urban expansion models (2010) Computers, Environment and Urban Systems, 34 (1), pp. 17-27; 121. Pohl, C., (1996) Geometric aspects of multisensor image fusion for topographic map updating in the humid Tropics, , ITC publication No. 39 (Enschede: ITC); 122. Pontius, R.G., Cornell, J.D., Hall, C.A.S., Modeling the spatial pattern of land-use change with GEOMOD2: Application and validation for Costa Rica (2001) Agriculture, Ecosystems & Environment, 85 (1-3), pp. 191-203; 123. Pontius, R.G., Jr., Millones, M., Death to Kappa: birth of quantity disagreement and allocation disagreement for accuracy assessment (2011) International Journal of Remote Sensing, 32 (15), pp. 4407-4429; 124. Prasad, P.R.C., Sringeswara, A.N., Reddy, C.S., Nagabhatla, N., Rajan, K.S., Giriraj, A., Murthy, M.S.R., Dutt, C.B.S., Assessment of forest fragmentation and species diversity in North Andaman Islands (India): a geospatial approach (2009) International Journal of Ecology & Developmentâ�¢, 14 (F09), pp. 33-46; 125. Puettmann, K.J., Restoring the adaptive capacity of forest ecosystems (2014) Journal of sustainable forestry, 33, pp. S15-S27; 126. Puyravaud, J.P., Standardizing the calculation of the annual rate of deforestation (2003) Forest ecology and management, 177 (1-3), pp. 593-596; 127. Qiaomin, Z., Shuzhen, S., The mangrove wetland resources and their conservation in China (2001) Journal of natural resources, 16 (1), pp. 28-36; 128. Ramachandra, T.V., Shruthi, B.V., Spatial mapping of renewable energy potential (2007) Renewable and Sustainable Energy Reviews, 11 (7), pp. 1460-1480; 129. Ramachandra, T.V., Ganapathy, S., Vegetation analysis in Uttara Kannada district using GIS and Remote sensing techniques (2008) ENVIS Technical Report, 24. , CES, IISc; 130. Ramachandra, T.V., Kumar, U., Characterisation of landscape with forest fragmentation dynamics (2011) Journal of Geographic Information System, 3 (3), pp. 242-253; 131. Ramachandra, T.V., Bharath, S., Bharath, H.A., Peri-Urban to Urban Landscape Patterns Elucidation through Spatial Metrics (2012) International Journal of Engineering Research and Development, 2 (12), pp. 58-81; 132. Ramachandra, T.V., Chandran, M.D.S., Joshi, N.V., Julka, P., Kumar, U., Bharath, H.A., Prakash, N.M., Mukri, V., (2012) Landslide Susceptible Zone Mapping in Uttara Kannada, Central Western Ghats, p. 560012. , ENVIS Technical Report 28, Energy & Wetlands Research Group, Centre for Ecological Sciences, Indian Institute of Science, Bangalore; 133. Ramachandra, T.V., Bharath, S., Bharath, A., Spatio-temporal dynamics along the terrain gradient of diverse landscape (2014) Journal of Environmental Engineering and Landscape Management, 22 (1), pp. 50-63; 134. Ramachandra, T.V., Hegde, G., Krishnadas, G., Scope of solar energy in Uttara Kannada, Karnataka State, India: roof top PV for domestic electricity and standalone systems for irrigation (2014) Productivity, 55 (1), p. 100; 135. Ramachandra, T.V., Hegde, G., Krishnadas, G., Potential assessment and decentralized applications of wind energy in Uttarakannada, Karnataka (2014) International Journal of Renewable energy Resources, 4 (1), pp. 1-10; 136. Ramachandra, T.V., Hegde, G., Bharath, S., Krishnadas, G., Bioenergy: A sustainable energy option for rural India (2014) Advances in Forestry Letters (AFL), 3 (1), pp. 1-15; 137. Ramachandra, T.V., Chandran, M.D.S., Joshi, N.V., Karthick, B., Mukri, V.D., Ecohydrology of Lotic Systems in Uttara Kannada, Central Western Ghats, India (2015) Environmental Management of River Basin Ecosystems, pp. 621-665. , In Springer, Cham; 138. Ramachandra, T.V., Bharath, S., Chandran, M.D.S., Geospatial analysis of forest fragmentation in Uttara Kannada District, India, 2016 (2016) Forest Ecosystems, 3 (1), pp. 1-15. , https://doi.org/10.1186/s40663-016-0069-4; 139. Ramachandra, T.V., Bharath, S., Geoinformatics based Valuation of Forest Landscape Dynamics in Central Western Ghats, India (2018) J Remote Sensing & GIS, 7 (227), p. 2; 140. Ramachandra, T.V., Bharath, S., Carbon Sequestration Potential of the Forest Ecosystems in the Western Ghats, a Global Biodiversity Hotspot (2020) Natural Resources Research, 29, pp. 2753-2771. , https://doi.org/10.1007/s11053-019-09588-0; 141. Ramachandra, T.V., Vinay, S., Bharath, S., Chandran, M.D., Aithal, B.H., Insights into riverscape dynamics with the hydrological, ecological and social dimensions for water sustenance (2020) Current Science (00113891), 118 (9); 142. Ramachandra, T.V., Bharath, S., Carbon Footprint of Karnataka: Accounting of Sources and Sinks (2021) Carbon Footprint Case Studies, pp. 53-92. , Springer, Singapore; 143. Ramakrishnan, P.S., (2000) Mountain biodiversity, land use dynamics, and traditional ecological knowledge, , Oxford & IBH Pub. Co; 144. Reddy, C.S., Singh, S., Dadhwal, V.K., Jha, C.S., Rao, N.R., Diwakar, P.G., Predictive Modeling of the spatial pattern of past and future forest cover changes in India (2017) Journal of Earth System Science, 126 (1), p. 8; 145. Reis, S., Analyzing land use/land cover changes using remote sensing and GIS in Rize, North-East Turkey (2008) Sensors, 8 (10), pp. 6188-6202; 146. Renard, Q., Pélissier, R., Ramesh, B.R., Kodandapani, N., Environmental susceptibility model for predicting forest fire occurrence in the Western Ghats of India (2012) International Journal of Wildland Fire, 21 (4), pp. 368-379; 147. Revenga, C., Developing indicators of ecosystem condition using geographic information systems and remote sensing (2005) Regional Environmental Change, 5 (4), pp. 205-214; 148. Riitters, K.H., Wickham, J.D., O'neill, R.V., Jones, K.B., Smith, E.R., Coulston, J.W., Wade, T.G., Smith, J.H., Fragmentation of continental United States forests (2002) Ecosystems, 5 (8), pp. 0815-0822; 149. Riitters, K.H., Wickham, J.D., Coulston, J.W., A preliminary assessment of Montreal process indicators of forest fragmentation for the United States (2004) Environmental monitoring and assessment, 91 (1-3), pp. 257-276; 150. Rounsevell, M.D., Pedroli, B., Erb, K.H., Gramberger, M., Busck, A.G., Haberl, H., Kristensen, S., Lotze-Campen, H., Challenges for land system science (2012) Land Use Policy, 29 (4), pp. 899-910; 151. Roy, P.S., Murthy, M.S.R., Roy, A., Kushwaha, S.P.S., Singh, S., Jha, C.S., Behera, M.D., Gupta, S., Forest fragmentation in India (2013) Current Science, 105 (6), pp. 774-780; 152. Saaty, T.L., Decision making with the analytic

Item Type:	Conference Paper
Publication:	IEEE International Symposium on Information Theory - Proceedings
Publisher:	Institute of Electrical and Electronics Engineers Inc.
Additional Information:	The copyright for this article belongs to Authors
Department/Centre:	Division of Electrical Sciences > Electrical Communication Engineering
Date Deposited:	29 Nov 2021 11:16
Last Modified:	29 Nov 2021 11:16
URI:	http://eprints.iisc.ac.in/id/eprint/70264

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