Detection of sinkhole attacks for supporting secure routing on 6LoWPAN for Internet of Things

The Internet of Things (IoT) networks are vulnerable to various kinds of attacks, being the sinkhole attack one of the most destructive since it prevents communication among network devices. In general, existing solutions are not effective to provide protection and security against attacks sinkhole on IoT, and they also introduce high consumption of resources de memory, storage and processing. Further, they do not consider the impact of device mobility, which in essential in urban scenarios, like smart cities. This paper proposes an intrusion detection system, called INTI (Intrusion detection of SiNkhole attacks on 6LoWPAN for InterneT of ThIngs), to identify sinkhole attacks on the routing services in IoT. Moreover, INTI aims to mitigate adverse effects found in IDS that disturb its performance, like false positive and negative, as well as the high resource cost. The system combines watchdog, reputation and trust strategies for detection of attackers by analyzing the behavior of devices. Results show the INTI performance and its effectiveness in terms of attack detection rate, number of false positives and false negatives.

[1]  Thiemo Voigt,et al.  Routing Attacks and Countermeasures in the RPL-Based Internet of Things , 2013, Int. J. Distributed Sens. Networks.

[2]  Saurabh Bagchi,et al.  RDAS: Reputation-Based Resilient Data Aggregation in Sensor Network , 2010, 2010 7th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON).

[3]  Mohammed Feham,et al.  Novel hybrid intrusion detection system for clustered wireless sensor network , 2011, ArXiv.

[4]  C. Adjih,et al.  Mobility Enhanced RPL for Wireless Sensor Networks , 2012, 2012 Third International Conference on The Network of the Future (NOF).

[5]  Omar Abdel Wahab,et al.  A cooperative watchdog model based on Dempster-Shafer for detecting misbehaving vehicles , 2014, Comput. Commun..

[6]  Thiemo Voigt,et al.  SVELTE: Real-time intrusion detection in the Internet of Things , 2013, Ad Hoc Networks.

[7]  Paolo Bellavista,et al.  Convergence of MANET and WSN in IoT Urban Scenarios , 2013, IEEE Sensors Journal.

[8]  Suat Özdemir,et al.  Functional reputation based reliable data aggregation and transmission for wireless sensor networks , 2008, Comput. Commun..

[9]  Jie Wu,et al.  Mobility Reduces Uncertainty in MANETs , 2007, IEEE INFOCOM 2007 - 26th IEEE International Conference on Computer Communications.

[10]  Adam Dunkels,et al.  Cross-Level Sensor Network Simulation with COOJA , 2006, Proceedings. 2006 31st IEEE Conference on Local Computer Networks.

[11]  马华东 Internet of Things: Objectives and Scientific Challenges , 2011 .

[12]  G. Mahadevan,et al.  A non cryptographic method of sink hole attack detection in wireless sensor networks , 2011, 2011 International Conference on Recent Trends in Information Technology (ICRTIT).

[13]  Maurizio A. Spirito,et al.  Denial-of-Service detection in 6LoWPAN based Internet of Things , 2013, 2013 IEEE 9th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob).

[14]  Stephan Haller,et al.  The Things in the Internet of Things , 2010 .