首页 | 本学科首页   官方微博 | 高级检索  
     


SVELTE: Real-time intrusion detection in the Internet of Things
Authors:Shahid Raza  Linus Wallgren  Thiemo Voigt
Affiliation:1. Department of Computer Engineering, Islamic Azad University, South Tehran Branch, Tehran, Iran;2. Department of Communication Engineering, Islamic Azad University, South Tehran Branch, Tehran, Iran;1. Faculty of Computer and Informatics Engineering, ?stanbul Technical University, Turkey;2. Faculty of Electrical and Electronics Engineering, ?stanbul Technical University, Turkey;1. Federal University of Santa Catarina, Florianópolis, SC, Brazil;2. State University of Western Paraná, Foz do Iguaçu, PR, Brazil
Abstract:In the Internet of Things (IoT), resource-constrained things are connected to the unreliable and untrusted Internet via IPv6 and 6LoWPAN networks. Even when they are secured with encryption and authentication, these things are exposed both to wireless attacks from inside the 6LoWPAN network and from the Internet. Since these attacks may succeed, Intrusion Detection Systems (IDS) are necessary. Currently, there are no IDSs that meet the requirements of the IPv6-connected IoT since the available approaches are either customized for Wireless Sensor Networks (WSN) or for the conventional Internet.In this paper we design, implement, and evaluate a novel intrusion detection system for the IoT that we call SVELTE. In our implementation and evaluation we primarily target routing attacks such as spoofed or altered information, sinkhole, and selective-forwarding. However, our approach can be extended to detect other attacks. We implement SVELTE in the Contiki OS and thoroughly evaluate it. Our evaluation shows that in the simulated scenarios, SVELTE detects all malicious nodes that launch our implemented sinkhole and/or selective forwarding attacks. However, the true positive rate is not 100%, i.e., we have some false alarms during the detection of malicious nodes. Also, SVELTE’s overhead is small enough to deploy it on constrained nodes with limited energy and memory capacity.
Keywords:Intrusion detection  Internet of Things  6LoWPAN  RPL  IPv6  Security  Sensor networks
本文献已被 ScienceDirect 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号