Avaliação das Técnicas de Detecção do Ataque Sybil na Disseminação de Conteúdo da Internet das Coisas
Resumo
A Internet das coisas (IoT) compreende uma diversidade de objetos heterogêneos. Eles atuam nestas redes coletando dados contínuos e discretos e disseminando estas informações para aplicações provendo assim um maior bem estar para as pessoas. O serviço de disseminação de dados na IoT utiliza o meio sem fio que é inseguro. Assim, este serviço pode ser prejudicado por diversos tipos de atacantes como o blackhole, sinkhole e o Sybil. Dentre esses, o ataque Sybil desponta como o mais crítico visto que ele atua na confidencialidade destes dados. Embora as soluções encontradas na literatura sejam eficazes contra o ataque Sybil, elas desconsideram a presença de dispositivos heterogêneos ou apresentam soluções complexas. Desta forma, este trabalho apresenta um estudo sobre a efetividade e eficiência das técnicas de detecção do ataque Sybil. Desta forma, esta avaliação usa métricas de eficácia e eficiência a fim de aferir a performance de um mecanismo com características próximas da IoT.Referências
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Vamsi, P. R. and Kant, K. (2014). A lightweight sybil attack detection framework for wireless sensor networks. In Contemporary Computing (IC3), 2014 Seventh International Conference on, pages 387-393. IEEE.
Wallgren, L., Raza, S., and Voigt, T. (2013). Routing attacks and countermeasures in the rpl-based internet of things. International Journal of Distributed Sensor Networks, 2013.
Wang, X., Zhang, J., Schooler, E. M., and Ion, M. (2014). Performance evaluation of attribute-based encryption: Toward data privacy in the iot. In Communications (ICC), 2014 IEEE International Conference on, pages 725-730. IEEE.
Yu, H., Kaminsky, M., Gibbons, P. B., and Flaxman, A. (2006). Sybilguard: defending against sybil attacks via social networks. In ACM SIGCOMM Computer Communication Review, volume 36, pages 267-278. ACM.
Agrawal, S. and Vieira, D. (2013). A survey on internet of things-doi 10.5752/p. 2316-9451.2013 v1n2p78. Abakós, 1(2):78-95.
Blazquez, A., Tsiatsis, V., and Vandikas, K. (2015). Performance evaluation of openid connect for an iot information marketplace. In Vehicular Technology Conference (VTC Spring), 2015 IEEE 81st, pages 1-6. IEEE.
Buttyan, L. and Holczer, T. (2012). Traffic analysis attacks and countermeasures in wireless body area sensor networks. In World of Wireless, Mobile and Multimedia Networks (WoWMoM), 2012 IEEE International Symposium on a, pages 1-6. IEEE.
Cervantes, C. A. V. (2014). Um sistema de detecção de ataques sinkhole sobre 6lowpan para internet das coisas.
da Silva, E., Santos, A. L., Albini, L. C. P., and Lima, M. N. (2008). Quantifying misbehavior attacks against the self-organized public key management on MANETs. In Proceedings of International Conference on Security and Cryptography (SECRYPT ’08), pages 128-135, Porto, Portugal. INSTCC Press.
Gubbi, J., Buyya, R., Marusic, S., and Palaniswami, M. (2013). Internet of things (iot): A vision, architectural elements, and future directions. Future Generation Computer Systems, 29(7):1645-1660.
Li, S., Da Xu, L., and Zhao, S. (2014). The internet of things: a survey. Information Systems Frontiers, pages 1-17.
Lin, X. (2013). Lsr: mitigating zero-day sybil vulnerability in privacy-preserving vehicular peer-to-peer networks. Selected Areas in Communications, IEEE Journal on, 31(9):237-246.
Park, S., Aslam, B., Turgut, D., and Zou, C. C. (2013). Defense against sybil attack in the initial deployment stage of vehicular ad hoc network based on roadside unit support. Security and Communication Networks, 6(4):523-538.
Quercia, D. and Hailes, S. (2010). Sybil attacks against mobile users: friends and foes to the rescue. In INFOCOM, 2010 Proceedings IEEE, pages 1-5. IEEE.
Rani, R., Dolly, M. P., and Kumar, M. D. (2015). Black hole prevention & detection under average energy consumption in wsn.
Shivlal, M. and Kumar, S. U. (2012). Performance analysis of secure wireless mesh networks. Research Journal of Recent Sciences ISSN, 2277:2502.
Vamsi, P. R. and Kant, K. (2014). A lightweight sybil attack detection framework for wireless sensor networks. In Contemporary Computing (IC3), 2014 Seventh International Conference on, pages 387-393. IEEE.
Wallgren, L., Raza, S., and Voigt, T. (2013). Routing attacks and countermeasures in the rpl-based internet of things. International Journal of Distributed Sensor Networks, 2013.
Wang, X., Zhang, J., Schooler, E. M., and Ion, M. (2014). Performance evaluation of attribute-based encryption: Toward data privacy in the iot. In Communications (ICC), 2014 IEEE International Conference on, pages 725-730. IEEE.
Yu, H., Kaminsky, M., Gibbons, P. B., and Flaxman, A. (2006). Sybilguard: defending against sybil attacks via social networks. In ACM SIGCOMM Computer Communication Review, volume 36, pages 267-278. ACM.
Publicado
09/11/2015
Como Citar
EVANGELISTA, Danilo; NOGUEIRA, Michele; SANTOS, Aldri.
Avaliação das Técnicas de Detecção do Ataque Sybil na Disseminação de Conteúdo da Internet das Coisas. In: SIMPÓSIO BRASILEIRO DE SEGURANÇA DA INFORMAÇÃO E DE SISTEMAS COMPUTACIONAIS (SBSEG), 15. , 2015, Florianópolis.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2015
.
p. 295-308.
DOI: https://doi.org/10.5753/sbseg.2015.20102.
