Análise de Consumo Energético e Identificação de Ataques de Negação de Serviço em Computação em Névoa

Resumo


O constante aumento na utilização de dispositivos de Internet das Coisas (IoT), fez crescer também a preocupação com segurança. Profissionais do ecossistema de IoT devem atentar-se à possibilidade de ataques cibernéticos, dentre eles o Ataque de Negação de Serviço Distribuído (DDoS). Esta modalidade de ataque pode representar não só um pequeno atraso nas comunicações, como também a interrupção total do serviço, seja pela inundação de pacotes na rede ou pela drenagem de recursos dos equipamentos. Tratando-se de dispositivos restritos, como os de IoT, qualquer pequena elevação em seu padrão de consumo energético pode representar uma alteração significativa em seu funcionamento. Através do uso da lógica Fuzzy, este trabalho propõe inferir o grau de pertinência de um ataque DDoS em um dispositivo central da computação em névoa por meio da análise do seu padrão de consumo energético.

Palavras-chave: MQTT, Computação em Névoa, Internet das Coisas, Ataque de Negação de Serviço, Consumo de Energia, Lógica Fuzzy

Referências

Bao, C., Guan, X., Sheng, Q., Zheng, K., and Huang, X. (2016). A Tool for Denial ofService Attack Testing in IoT. page 5.

Bekaroo, G. and Santokhee, A. (2016). Power consumption of the Raspberry Pi: Acomparative analysis. 2016 IEEE International Conference on Emerging Technologiesand Innovative Business Practices for the Transformation of Societies, EmergiTech2016, pages 361-366.

Berouine, A., Akssas, E., Naitmalek, Y., Lachhab, F., Bakhouya, M., Ouladsine, R., andEssaaidi, M. (2019). A Fuzzy Logic-Based Approach for HVAC Systems Control.pages 1510-1515.

Chen, Q., Chen, H., Cai, Y., Zhang, Y., and Huang, X. (2018). Denial of Service Attack on IoT System. Proceedings - 9th International Conference on Information Technologyin Medicine and Education, ITME 2018, pages 755-758.

Dinculeaná, D. and Cheng, X. (2019). Vulnerabilities and Limitations of MQTT ProtocolUsed between IoT Devices. Applied Sciences, 9(5):848.

El-Semary, A., Edmonds, J., Gonzalez, J., and Papa, M. (2005). A framework for hy-brid fuzzy logic intrusion detection systems. JEEE International Conference on FuzzySystems, pages 325-330.

Haripriya, A. P. and Kulothungan, K. (2019). Secure-MQTT: an efficient fuzzy logic-based approach to detect DoS attack in MQTT protocol for internet of things. EURA-SIP Journal on Wireless Communications and Networking, 2019(1):90.

Harsha, M. S., Bhavani, B. M., and Kundhavai, K. R. (2018). Analysis of vulnerabilitiesin MQTT security using Shodan API and implementation of its countermeasures viaauthentication and ACLs. 2018 International Conference on Advances in Computing,Communications and Informatics, ICACCI 2018, pages 2244-2250.

Khwanrit, R., Kittipiyakul, S., Kudtonagngam, J., and Fujita, H. (2018). Accuracy Com-parison of Present Low-cost Current Sensors for Building Energy Monitoring. 2018International Conference on Embedded Systems and Intelligent Technology and Inter-national Conference on Information and Communication Technology for EmbeddedSystems, ICESIT-ICICTES 2018, pages 3-8.

Kodali, R. K. and Soratkal, S. R. (2017). MQTT based home automation system usingESP8266. JEEE Region 10 Humanitarian Technology Conference 2016, R10-HTC2016 - Proceedings, pages 1-5.

Lee, C. (1990). Fuzzy logic in control systems: fuzzy logic controller. II. IEEE Transac-tions on Systems, Man, and Cybernetics, 20(2):419-435.

Lekié, M., Galié, J., and Matié, S. (2019). An IoT Solution for Secured and RemoteSound Level Monitoring. 2019 18th International Symposium INFOTEH-JAHORINA,INFOTEH 2019 - Proceedings, (March):20-22.

Liang, L., Zheng, K., Sheng, Q., and Huang, X. (2017). A denial of service attack methodfor an IoT system. Proceedings - 2016 8th International Conference on InformationTechnology in Medicine and Education, ITME 2016, pages 360-364.

Mamdani, E. H. and Assilian, S. (1975). An experiment in linguistic synthesis with afuzzy logic controller. International Journal of Man-Machine Studies, 7(1):1-13.

Matam, R., Shukla, S., and Tyagi, G. (2017). Local Connectivity Based Boundary De-tection in Wireless Sensor Networks. Proceedings - 2016 IEEE International Confe-rence on Internet of Things; IEEE Green Computing and Communications; IEEE Cy-ber, Physical, and Social Computing; IEEE Smart Data, iThings-GreenCom-CPSCom-Smart Data 2016, pages 420-423.

Naik, N. (2017). Choice of Effective Messaging Protocols for IoT Systems : MQTT ,CoAP, AMQP and HTTP.

Niruntasukrat, A., Issariyapat, C., Pongpaibool, P., Meesublak, K., Aiumsupucgul, P.,and Panya, A. (2016). Authorization mechanism for MQTT-based Internet of Things.2016 IEEE International Conference on Communications Workshops, ICC 2016, pages290-295.

Osanaiye, O., Chen, S., Yan, Z., Lu, R., Choo, K. K. R., and Dlodlo, M. (2017). FromCloud to Fog Computing: A Review and a Conceptual Live VM Migration Framework.JEEE Access, 5:8284-8300.

Pappis, C. P. and Siettos, C. I. (2005). Fuzzy Reasoning, pages 437-474. Springer US,Boston, MA.

Pavelic, M., Bajt, V., and Kusek, M. (2018). Energy efficiency of machine-to-machineprotocols. 2018 41st International Convention on Information and CommunicationTechnology, Electronics and Microelectronics, MIPRO 2018 - Proceedings, pages 361-366.

Peralta, G., Iglesias-Urkia, M., Barcelo, M., Gomez, R., Moran, A., and Bilbao, J. (2017).Fog computing based efficient IoT scheme for the Industry 4.0. Proceedings of the2017 IEEE International Workshop of Electronics, Control, Measurement, Signals andtheir Application to Mechatronics, ECMSM 2017, pages 1-6.

Potrino, G., De Rango, F., and Santamaria, A. F. (2019). Modeling and evaluation ofa new IoT security system for mitigating DoS attacks to the MQTT broker. IEEEWireless Communications and Networking Conference, WCNC, 2019-April: 1-6.

Rahimi, P. and Chrysostomou, C. (2019). Improving the Network Lifetime and Perfor-mance of Wireless Sensor Networks for IoT Applications Based on Fuzzy Logic. InProceedings - 15th Annual International Conference on Distributed Computing in Sen-sor Systems, DCOSS 2019, pages 667-674. IEEE.

Roohi, A., Adeel, M., and Shah, M. A. (2019). DDosS in IoT: A roadmap towards se-curity countermeasures. ICAC 2019 - 2019 25th IEEE International Conference onAutomation and Computing, (September):1-6.

Santiago, S. and Arockiam, L. (2017). A novel fuzzy based energy efficient routingfor Internet of Things. 2017 International Conference on Algorithms, Methodology,Models and Applications in Emerging Technologies, ICAMMAET 2017, 2017-Janua:1—4.

Shah, B. (2018). Fuzzy Energy Efficient Routing for Internet of Things (IoT). Internati-onal Conference on Ubiquitous and Future Networks, ICUFN, 2018-July:320-325.

Shapsough, S., Aloul, F., and Zualkernan, I. A. (2018). Securing Low-Resource Edge De-vices for IoT Systems. 2018 International Symposium in Sensing and Instrumentationin JoT Era, ISSI 2018.

Shinde, S. A., Nimkar, P. A., Singh, S. P., Salpe, V. D., and Jadhav, Y. R. (2016). MQTT- Message queuing telemetry transport. International Journal of Research, 3(3):240-244.

Singh, D., Tripathi, G., and Jara, A. J. (2014). A survey of Internet-of-Things: Futurevision, architecture, challenges and services. 2014 IEEE World Forum on Internet ofThings, WF-IoT 2014, pages 287-292.

Toldinas, J., Lozinskis, B., Baranauskas, E., and Dobrovolskis, A. (2019). MQTT Qualityof Service versus Energy Consumption. 2019 23rd International Conference Electro-nics, pages 1-4.

Veeramanikanda.M, S. S. (2017). Publish/Subscribe Broker based Architecture for fogcomputing. International Conference on Energy, Communication, Data Analytics andSoft Computing.

Venanzi, R., Kantarci, B., Foschini, L., and Bellavista, P. (2018). MQTT-Driven NodeDiscovery for Integrated IoT-Fog Settings Revisited: The Impact of Advertiser Dyna-micity. Proceedings - 12th IEEE International Symposium on Service-Oriented System Engineering, SOSE 2018 and 9th International Workshop on Joint Cloud Computing,JCC 2018, pages 31-39.

Vignau, B., Khoury, R., and Halle, S. (2019). 10 Years of IoT Malware: A Feature-BasedTaxonomy. Proceedings - Companion of the 19th IEEE International Conference onSoftware Quality, Reliability and Security, ORS-C 2019, pages 458-465.

Vrettos, G., Logaras, E., and Kalligeros, E. (2018). Towards Standardization of MQTT-Alert-based Sensor Networks: Protocol Structures Formalization and Low-End NodeSecurity. 2018 IEEE 13th International Symposium on Industrial Embedded Systems,SIES 2018 - Proceedings, pages 1-4.

Xu, Y., Mahendran, V., and Radhakrishnan, S. (2016). Towards SDN-based fog com-puting: MQTT broker virtualization for effective and reliable delivery. 2076 8th In-ternational Conference on Communication Systems and Networks, COMSNETS 2016,pages 1-6.
Publicado
07/12/2020
CRUZ, Diogo Vinícius Martins; PIGATTO, Daniel Fernando; VENDRAMIN, Ana Cristina Barreiras Kochem. Análise de Consumo Energético e Identificação de Ataques de Negação de Serviço em Computação em Névoa. In: WORKSHOP EM CLOUDS E APLICAÇÕES (WCGA), 18. , 2020, Rio de Janeiro. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2020 . p. 80-93. DOI: https://doi.org/10.5753/wcga.2020.12446.