A non-cooperative non-zero-sum game-based dependability assessment of heterogeneous WSNs with malware diffusion
Tài liệu tham khảo
AboElFotoh, 2005, Computing reliability and message delay for cooperative wireless distributed sensor networks subject to random failures, IEEE T. Reliab., 54, 145, 10.1109/TR.2004.842540
Adiga A., Venkat S., Vullikanti A., 2016. To delay or not: Temporal vaccination games on networks. In: IEEE INFOCOM 2016 - In: Proceedings of the 35th Annual IEEE International Conference on Computer Communications, 7524351:1–7524351:9.
Al-Kuwaiti, 2009, A comparative analysis of network dependability, fault-tolerance, reliability, security, and survivability, IEEE Commun. Surv. Tutor., 11, 106, 10.1109/SURV.2009.090208
Alskaif, 2015, Game theory for energy efficiency in wireless sensor networks: latest trends, J. Netw. Comput. Appl., 54, 33, 10.1016/j.jnca.2015.03.011
Bahi, 2014, Epidemiological approach for data survivability in unattended wireless sensor networks, J. Netw. Comput. Appl., 46, 374, 10.1016/j.jnca.2014.09.011
Basilico N., Gatti N., Monga M., Sicari S., 2014. Security games for node localization through verifiable multilateration. IEEE T. Depend. Secure 11(1), pp. 72–85.
Borges, 2014, Survey on the characterization and classification of wireless sensor network applications, IEEE Commun. Surv. Tutor., 16, 1860, 10.1109/COMST.2014.2320073
Boubiche, 2016, An outline of data aggregation security in heterogeneous wireless sensor networks, Sensors, 16, 525:1, 10.3390/s16040525
Dâmaso, 2014, Reliability of wireless sensor networks, Sensors, 14, 15760, 10.3390/s140915760
Di Martino, 2012, Automated generation of performance and dependability models for the assessment of wireless sensor networks, IEEE T. Comput., 61, 870, 10.1109/TC.2011.96
Distefano, 2011, Reliability evaluation of wsn with dynamic-dependent nodes, Int. J. Reliab., Qual. Saf. Eng., 18, 515, 10.1142/S0218539311004226
Engouang, 2015, GABs: a game-based secure and energy efficient data aggregation for wireless sensor networks, Int. J. Distrib. Sens. N., 2015, 658543:1
Giannetsos, 2010, Arbitrary code injection through self-propagating worms in Von Neumann architecture devices, Comput. J., 53, 1576, 10.1093/comjnl/bxq009
Gu, 2011, A study of self-propagating mal-packets in sensor networks: attacks and defenses, Comput. Secur., 30, 13, 10.1016/j.cose.2010.10.002
Illiano, 2015, Detecting malicious data injections in wireless sensor networks: a survey, ACM Comput. Surv., 48, 24:1, 10.1145/2818184
Islam, 2013, Classification of malware based on integrated static and dynamic features, J. Netw. Comput. Appl., 36, 646, 10.1016/j.jnca.2012.10.004
Jin, 2013, Computer virus propagation model based on bounded rationality evolutionary game theory, Secur. Commun. Netw., 6, 210, 10.1002/sec.558
Kamal, 2013, Packet-level attestation (PLA): a framework for in-network sensor data reliability, ACM T. Sens. Netw., 9, 19:1
Keshri, 2014, Two time-delay dynamic model on the transmission of malicious signals in wireless sensor network, Chaos, Solitons Fractals, 68, 151, 10.1016/j.chaos.2014.08.006
Keshri, 2016, Impact of reduced scale free network on wireless sensor network, Phys. A: Stat. Mech. its Appl., 463, 236, 10.1016/j.physa.2016.07.059
Khouzani, 2012, Saddle-point strategies in malware attack, IEEE J. Sel. Area Comm., 30, 31, 10.1109/JSAC.2012.120104
Liu, 2015, A stochastic evolutionary coalition game model of secure and dependable virtual service in Sensor-Cloud, Appl. Soft Comput., 30, 123, 10.1016/j.asoc.2015.01.038
Mahmood, 2015, Reliability in wireless sensor networks: a survey and challenges ahead, Comput. Netw., 79, 166, 10.1016/j.comnet.2014.12.016
Manshaei, 2013, Game theory meets network security and privacy, ACM Comput. Surv., 45, 25:1, 10.1145/2480741.2480742
Mishra, 2013, Mathematical model on the transmission of worms in wireless sensor network, Appl. Math. Model., 37, 4103, 10.1016/j.apm.2012.09.025
Moosavi, 2014, A game-theoretic framework for robust optimal intrusion detection in wireless sensor networks, IEEE T. Inf. Foren. Secur., 9, 1367, 10.1109/TIFS.2014.2332816
Razak, 2016, The rise of “malware”: bibliometric analysis of malware study, J. Netw. Comput. Appl., 75, 58, 10.1016/j.jnca.2016.08.022
Senouci, 2012, Performance evaluation of network lifetime spatial-temporal distribution for WSN routing protocols, J. Netw. Comput. Appl., 35, 1317, 10.1016/j.jnca.2012.01.016
Shamshirband, 2014, Cooperative game theoretic approach using fuzzy Q-learning for detecting and preventing intrusions in wireless sensor networks, Eng. Appl. Artif. Intel., 32, 228, 10.1016/j.engappai.2014.02.001
Shen, 2012, Survivability evaluation towards attacked WSNs based on stochastic game and continuous-time Markov chain, Appl. Soft Comput., 12, 1467, 10.1016/j.asoc.2012.01.009
Shen, 2014, Differential game-based strategies for preventing malware propagation in wireless sensor networks, IEEE T. Inf. Foren. Secur., 9, 1962, 10.1109/TIFS.2014.2359333
Shen, 2015, Quantal response equilibrium-based strategies for intrusion detection in WSNs, Mob. Inf. Syst., 2015, 179839:1
Shen, 2015, Optimal report strategies for WBANs using a cloud-assisted IDS, Int. J. Distrib. Sens. N., 2015, 184239:1
Shen, 2016, Trust dynamics in WSNs: an evolutionary game-theoretic approach, J. Sens., 2016, 4254701:1, 10.1155/2016/4254701
Shen, 2016, Reliability evaluation for clustered WSNs under malware propagation, Sensors, 16, 855:1, 10.3390/s16060855
Silva, 2012, Reliability and availability evaluation of wireless sensor networks for industrial applications, Sensors, 12, 806, 10.3390/s120100806
Spyridopoulos, 2015, A game theoretical method for cost-benefit analysis of malware dissemination prevention, Inf. Secur. J., 24, 164
Tang, 2011, A modified SI epidemic model for combating virus spread in Wireless Sensor Networks, Int. J. Wirel. Inf. Netw., 18, 319, 10.1007/s10776-011-0147-z
Tanwar, 2015, A systematic review on heterogeneous routing protocols for wireless sensor network, J. Netw. Comput. Appl., 53, 39, 10.1016/j.jnca.2015.03.004
Van Mieghem, 2006
Wang, 2014, Reliability and lifetime modeling of wireless sensor nodes, Microelectron. Reliab., 54, 160, 10.1016/j.microrel.2013.08.001
Wang, 2009, An improved SIR model for analyzing the dynamics of worm propagation in wireless sensor networks, Chin. J. Electron., 18, 8
Wang, 2010, EiSIRS: a formal model to analyze the dynamics of worm propagation in wireless sensor networks, J. Comb. Optim., 20, 47, 10.1007/s10878-008-9190-9
Wang, 2013, Reaction-diffusion modeling of malware propagation in mobile wireless sensor networks, Sci. China Inf. Sci., 56, 1, 10.1007/s11432-013-4977-4
Wang, 2014, A pulse immunization model for inhibiting malware propagation in mobile wireless sensor networks, Chin. J. Electron., 23, 810
Wang, 2014, Modeling the propagation of worms in networks: a survey, IEEE Commun. Surv. Tutor., 16, 942, 10.1109/SURV.2013.100913.00195
Wang, 2015, Combinatorial analysis of body sensor networks subject to probabilistic competing failures, Reliab. Eng. Syst. Saf., 142, 388, 10.1016/j.ress.2015.06.005
Yan, 2015, A novel OBDD-based reliability evaluation algorithm for wireless sensor networks on the multicast model, Math. Probl. Eng., 2015, 269781:1, 10.1155/2015/269781
Yu, 2015, Malware propagation in large-scale networks, IEEE Trans.. Knowl. Data Eng., 27, 170, 10.1109/TKDE.2014.2320725
Yu, 2015, Modeling malicious activities in cyber space, IEEE Netw., 29, 83, 10.1109/MNET.2015.7340429
Yue, 2016, An efficient reliability evaluation method for industrial wireless sensor networks, J. Southeast Univ. (Engl. Ed.), 32, 195
Zhu, 2015, Dynamical analysis and optimal control for a malware propagation model in an information network, Neurocomputing, 149, 1370, 10.1016/j.neucom.2014.08.060
Zonouz, 2014, Reliability-oriented single-path routing protocols in wireless sensor networks, IEEE Sens. J., 14, 4059, 10.1109/JSEN.2014.2332296