1. Basilico, N., Gatti, N., and Amigoni, F. Leader-follower strategies for robotic patrolling in environments with arbitrary topologies, 8th Inter-national Conference on Autonomous Agents and Multi-Agent Systems, (2009) 57–64.
2. Bigdeli, H. and Hassanpour, H. Modeling and solving multiobjective secu-rity game problem using multiobjective bilevel problem and its application in metro security system, Journal of Electronical and Cyber Defence, Special Issue of the International Conference on Combinatorics, Cryp-tography and Computation (In Persian), (2017) 31–38.
3. Bigdeli, H. and Hassanpour, H. An approach to solve multi-objective lin-ear production planning games with fuzzy parameters, Yugosl. J. Oper. Res. 28(2), (2018) 237–248.
4. Bigdeli, H. and Hassanpour, H. Solving defender-attacker game with mul-tiple decision makers using expected-value Model, Casp. J. Math. Sci. (CJMS) (2020).
5. Bigdeli, H., Hassanpour, H. and Tayyebi, J. Optimistic and pessimistic solutions of single and multi-objective matrix games with fuzzy payoffs and analysis of some military cases, Scientific Journal of Advanced Defense Science and Technology (In Persian), (2017) 133–145.
6. Bigdeli, H., Hassanpour, H. and Tayyebi, J. Constrained bimatrix games with fuzzy goals and its application in nuclear negotiations, Iran. J. Nu-mer. Anal. Optim., 8(1), (2018) 81–110.
7. Bigdeli, H., Hassanpour, H. and Tayyebi, J. Multiobjective security game with fuzzy payoffs, Iran. J. Fuzzy Syst. 16(1), (2019) 89–101.
8. Brown, G., Carlyle, M., Diehl, D., Kline, J. and Wood, K. A two-sided optimization for theater ballistic missile defense, Oper. Res. 53(5), (2005) 745–763.
9. Buckley, J.J. Joint solution to fuzzy programming problems, Fuzzy Sets Syst. 72(2), (1995) 215–220.
10. Cohen, F. and Koike, D. Misleading attackers with deception, In Proceed-ings from the Fifth Annual IEEE SMC Information Assurance Workshop, (2004) 30–37.
11. Conitzer, V. and Sandholm, T. Computing the optimal strategy to commit to, 7th ACM conference on Electronic commerce, (2006) 82–90.
12. Daniel, D.C. and Herbig, K.L. Strategic military deception, New York: Pergamon Press, 1981.
13. Dickerson, J.P., Simari, G.I., Subrahmanian, V.S. and Kraus, S. A graph-theoretic approach to protect static and moving targets from adversaries, 9th International Conference on Autonomous Agents and Multiagent Sys-tems: volume 1-Volume 1, (2010) 299–306.
14. Do, C.T., Tran, N.H., Hong, C., Kamhoua, C.A., Kwiat, K.A., Blasch, E., Ren, S., Pissinou, N. and Iyengar, S.S. Game theory for cyber security and privacy, ACM Comput. Surv. (CSUR), 50(2), (2017) 1–37.
15. Dubois, D. and Prade, H. Fuzzy sets and statistical data, Eur. J. Oper. Res. 25(3), (1986) 345–356.
16. Ehrgott, M. Multicriteria optimization, Springer Science & Business Me-dia, 2005.
17. Esmaieli, S., Hassanpour, H. and Bigdeli, H. Lexicographic programming for solving security game with fuzzy payoffs and computing optimal decep-tion strategy, Defensive Future Study Researches Journal (In Persian), 5(16), (2020) 89–108.
18. Fang, F., Nguyen, T.H., Pickles, R., Lam, W.Y., Clements, G.R., An, B., Singh, A., Tambe, M. and Lemieux, A. Deploying PAWS: field optimiza-tion of the protection assistant for wildlife security, In Twenty-Eighth IAAI Conference, (2016).
19. Frank. Jr. and Willard C. Politico military deception at sea in the Spanish civil war, 1936-39., Intell. Natl. Secur. 5(3), (1990) 84–112.
20. Fugate, S. and Ferguson-Walter, K. Artificial intelligence and game the-ory models for defending critical networks with cyber deception, AI Mag. 40(1), (2019) 49–62.
21. Hamilton, D.L. Deception in Soviet military doctrine and operations, NAVAL POSTGRADUATE SCHOOL MONTEREY CA, 1986.
22. Heilpern, S. The expected valued of a fuzzy number, Fuzzy sets Syst. 47, (1992) 81–86.
23. Kang, B., Wei, D., Li, Y. and Deng, Y. A method of converting Z-number to classical fuzzy number, J. Inf. Comput. Sci. 9(3), (2012) 703–709.
24. Karmakar, S., Seikh, M.R. and Castillo, O. Type-2 intuitionistic fuzzy matrix games based on a new distance measure: Application to biogas-plant implementation problem, Appl. Soft Comput. 106, (2021) p.107357.
25. Korzhyk, D., Conitzer, V. and Parr, R. Complexity of computing optimal Stackelberg strategies in security resource allocation games, 24th AAAI Conference on Artificial Intelligence, (2010) 805–810.
26. Letchford, J. and Vorobeychik, Y. Computing randomized security strate-gies in networked domains, Applied adversarial Reasoning and Risk Mod-eling, In Workshops at the Twenty-Fifth AAAI Conference on Artificial Intelligence, 2011.
27. Lye, K. and Wing, J.M. Game strategies in network security, Int. J. Inf. Secur. 4(1), (2005) 71–86.
28. McQueen, M.A. and Boyer, W.F. Deception used for cyber defense of control systems, 2nd Conference on Human System Interactions, (2009) 624–631.
29. Nishizaki, I. and Sakawa, M. Stackelberg solutions to multiobjective two-level linear programming problems, J. Optim. Theory Appl. 103(1), (1999) 161–182.
30. Oikonomakis, P. Strategic military deception prerequisites of success in technological environment, 2016.
31. Ren, A., Wang, Y. and Xue, X. Interactive programming approach for solving the fully fuzzy bilevel linear programming problem, Knowl Based Syst. 99, (2016) 103–111.
32. Rowe, N.C., Custy, E.J. and Duong, B.T. Defending cyberspace with fake honeypots, J. Comput. 2(2), (2007) 25–36.
33. Saati, S.M., Memariani, A. and Jahanshahloo, G.R. Efficiency analysis and ranking of DMUs with fuzzy data, Fuzzy Optim. Decis. Mak. 1(3) (2002) 255-267.
34. Sakawa, M. Fuzzy sets and interactive multiobjective optimization, Plenumpress, New York and London, 1993.
35. Sakawa, M. and Nishizaki, I. Cooperative and noncooperative multi-level programming, Springer, New York and London, 2009.
36. Seikh, M.R., Dutta, S. and Li, D.F. Solution of matrix games with rough interval pay‐offs and its application in the telecom market share problem, Int. J. Intell. Syst. 36(10), (2021) 6066–6100.
37. Seikh, M.R., Karmakar, S. and Castillo, O. A novel defuzzification ap-proach of Type-2 fuzzy variable to solving matrix games, An application to plastic ban problem, Iran. J. Fuzzy Syst. 18(5), (2021) 155–172.
38. Seikh, M.R., Karmakar, S. and Nayak, P.K. Matrix games with dense fuzzy payoffs, Int. J. Intell. Syst. 36(4), (2021) 1770–1799.
39. Seikh, M.R., Karmakar, S. and Xia, M. Solving matrix games with hesi-tant fuzzy pay-offs, Iran. J. Fuzzy Syst. 17(4), (2020) 25–40.
40. Sokri, A. Optimal resource allocation in cyber-security: A game theoretic approach, Procedia Comput. Sci. 134, (2018) 283–288.
41. Tambe, M. Security and game theory: algorithms, deployed systems, lessons learned, Cambridge University Press, 2011.
42. Trejo, K.K., Clempner, J.B. and Poznyak, A.S. A Stackelberg security game with random strategies based on the extraproximal theoretic ap-proach, Eng. Appl. Artif. Intell. 37, (2015) 145–153.
43. Trejo, K.K., Kristal K., Clempner, J.B. and Poznyak, A.S. Adapting strategies to dynamic environments in controllable Stackelberg security games, IEEE 55th Conference on Decision and Control (CDC), (2016) 5484–5489.
44. Wang, A., Cai, Y., Yang, W. and Hou, Z. A Stackelberg security game with cooperative jamming over a multiuser OFDMA network, IEEE Wire-less Communications and Networking Conference (WCNC), (2013) 4169–4174.
45. Yin, Y., An, B., Vorobeychik, Y. and Zhuang, J., Optimal deceptive strategies in security games: A preliminary study, In Proc. of AAAI, 2013.
46. Zadeh, L.A. A note on Z-numbers, Inform. Sci. 181(14) (2011) 2923–2932.
47. Zhu, Q. Game theory for cyber deception: A tutorial, 6th Annual Sym-posium on Hot Topics in the Science of Security, (2019) 1–3.
