Recursive-clustering-based approach for denial of service (DoS) attacks in wireless sensors networks

SUMMARYThis paper presents a novel approach for detecting denial of service attacks. In particular, the concern is on the sleeping deprivation attacks such as the malicious nodes that use flooding technique. Our approach is based on wireless sensor network (WSN) clustering. It consists in recursivel...

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Published in:	International journal of communication systems Vol. 28; no. 2; pp. 309 - 324
Main Authors:	Fouchal, S., Mansouri, D., Mokdad, L., Iouallalen, M.
Format:	Journal Article
Language:	English
Published:	Chichester Blackwell Publishing Ltd 25.01.2015 Wiley Subscription Services, Inc Wiley
Subjects:	Algorithms Clustering Computer Science Denial of service attacks DoS attack FFUCA Flooding LEACH Mathematical models Remote sensors Sensors Wireless networks WSN
ISSN:	1074-5351, 1099-1131
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Abstract	SUMMARYThis paper presents a novel approach for detecting denial of service attacks. In particular, the concern is on the sleeping deprivation attacks such as the malicious nodes that use flooding technique. Our approach is based on wireless sensor network (WSN) clustering. It consists in recursively clustering sensors until a required granularity (chosen by the expert) is achieved. We apply our approach with two different clustering algorithms. Indeed, we use the common clustering WSN algorithm Low Energy Algorithm Adaptive Clustering Hierarchy and the general clustering method Fast and Flexible Unsupervised Clustering Algorithm (FFUCA) based on ultrametric properties. We discuss the behavior of the approach with the two algorithms. Also, we present numerical results that show the efficiency of recursive clustering using the FFUCA algorithm. Copyright © 2013 John Wiley & Sons, Ltd. This paper presents a novel approach for detecting denial of service attacks in wireless sensor networks. The concern here is on the sleeping deprivation attacks such as malicious sensors that use flooding technique. The idea consists in clustering sensors recursively until a required granularity is achieved. We use here a generic clustering algorithm named Fast and Flexible Unsupervised Clustering Algorithm based on ultrametric properties. We present numerical results that show the efficiency of our approach using the Fast and Flexible Unsupervised Clustering Algorithm.
AbstractList	This paper presents a novel approach for detecting denial of service attacks. In particular, the concern is on the sleeping deprivation attacks such as the malicious nodes that use flooding technique. Our approach is based on wireless sensor network (WSN) clustering. It consists in recursively clustering sensors until a required granularity (chosen by the expert) is achieved. We apply our approach with two different clustering algorithms. Indeed, we use the common clustering WSN algorithm Low Energy Algorithm Adaptive Clustering Hierarchy and the general clustering method Fast and Flexible Unsupervised Clustering Algorithm (FFUCA) based on ultrametric properties. We discuss the behavior of the approach with the two algorithms. Also, we present numerical results that show the efficiency of recursive clustering using the FFUCA algorithm. Copyright © 2013 John Wiley & Sons, Ltd. This paper presents a novel approach for detecting denial of service attacks. In particular, the concern is on the sleeping deprivation attacks such as the malicious nodes that use flooding technique. Our approach is based on wireless sensor network (WSN) clustering. It consists in recursively clustering sensors until a required granularity (chosen by the expert) is achieved. We apply our approach with two different clustering algorithms. Indeed, we use the common clustering WSN algorithm Low Energy Algorithm Adaptive Clustering Hierarchy and the general clustering method Fast and Flexible Unsupervised Clustering Algorithm (FFUCA) based on ultrametric properties. We discuss the behavior of the approach with the two algorithms. Also, we present numerical results that show the efficiency of recursive clustering using the FFUCA algorithm. Copyright copyright 2013 John Wiley & Sons, Ltd. This paper presents a novel approach for detecting denial of service attacks in wireless sensor networks. The concern here is on the sleeping deprivation attacks such as malicious sensors that use flooding technique. The idea consists in clustering sensors recursively until a required granularity is achieved. We use here a generic clustering algorithm named Fast and Flexible Unsupervised Clustering Algorithm based on ultrametric properties. We present numerical results that show the efficiency of our approach using the Fast and Flexible Unsupervised Clustering Algorithm. SUMMARY This paper presents a novel approach for detecting denial of service attacks. In particular, the concern is on the sleeping deprivation attacks such as the malicious nodes that use flooding technique. Our approach is based on wireless sensor network (WSN) clustering. It consists in recursively clustering sensors until a required granularity (chosen by the expert) is achieved. We apply our approach with two different clustering algorithms. Indeed, we use the common clustering WSN algorithm Low Energy Algorithm Adaptive Clustering Hierarchy and the general clustering method Fast and Flexible Unsupervised Clustering Algorithm (FFUCA) based on ultrametric properties. We discuss the behavior of the approach with the two algorithms. Also, we present numerical results that show the efficiency of recursive clustering using the FFUCA algorithm. Copyright © 2013 John Wiley & Sons, Ltd. SUMMARYThis paper presents a novel approach for detecting denial of service attacks. In particular, the concern is on the sleeping deprivation attacks such as the malicious nodes that use flooding technique. Our approach is based on wireless sensor network (WSN) clustering. It consists in recursively clustering sensors until a required granularity (chosen by the expert) is achieved. We apply our approach with two different clustering algorithms. Indeed, we use the common clustering WSN algorithm Low Energy Algorithm Adaptive Clustering Hierarchy and the general clustering method Fast and Flexible Unsupervised Clustering Algorithm (FFUCA) based on ultrametric properties. We discuss the behavior of the approach with the two algorithms. Also, we present numerical results that show the efficiency of recursive clustering using the FFUCA algorithm. Copyright © 2013 John Wiley & Sons, Ltd. This paper presents a novel approach for detecting denial of service attacks in wireless sensor networks. The concern here is on the sleeping deprivation attacks such as malicious sensors that use flooding technique. The idea consists in clustering sensors recursively until a required granularity is achieved. We use here a generic clustering algorithm named Fast and Flexible Unsupervised Clustering Algorithm based on ultrametric properties. We present numerical results that show the efficiency of our approach using the Fast and Flexible Unsupervised Clustering Algorithm.
Author	Fouchal, S. Iouallalen, M. Mansouri, D. Mokdad, L.
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References_xml	– reference: Khan S, Loo J. Cross layer secure and resource-aware on-demand routing protocol for hybrid wireless mesh networks. Wireless Personal Communications January 2012; 62(1):201-214. – reference: Li B, Batten L. Using mobile agents to recover from node and database compromise in path-based DoS attacks in wireless sensor networks. Journal of Network and Computer Applications 2009; 32:337-387. – reference: Son JG, Jung S, Kim JH, Seo DI, Kim S. Research on a denial of service (DoS) detection system based on global interdependent behaviors in a sensor network environment. Sensors ISSN 2010; 10(11):10376-10386. – reference: Younis O, Fahmy S. HEED: a hybrid, energy-efficient distributed clustering approach for ad hoc sensor networks. IEEE Transactions on Mobile Computing 2004; 3(4):366-379. – reference: Perrig A, Szewczyk R, Wen V, Culler D, Tygar JD. SPINS: Security Protocols for Sensor Networks. Mobile Computing and Networking 2001: 189-199. – reference: Fouchal F, Ahat A, BenAmor S, Lavallée I, Bui M. Competitive clustering algorithms based on ultrametric properties. Journal of Computational Science (Elsevier) June 2012; 4(4):219-231. (JOCS-D-11-00136R1, IOD: 10.1016/j.jocs.2011.11.004). – reference: Shankar M, Sridar M, Rajani M. Performance evaluation of leach protocol in wireless network. International Journal of Scientific & Engineering Research January 2012; 3:281-283. – reference: Ali Alrajeh N, Khan S, Lloret J, Loo J. Secure routing protocol using cross-layer design and energy harvesting in wireless sensor networks. IJDSN February 2013; 2013. – reference: Popescu AM, Tudorache GI, Peng B, Kemp AH. Surveying position based routing protocols for wireless sensor and ad-hoc networks. Computer and Mathematics with Applications 2012; 4(1). – reference: Liming X, Xiaohua J, Kunxiao Z. QoS multicast routing in cognitive radio ad hoc networks. International Journal of Communication Systems January 2012; 25(1):30-46. – reference: Le A, Loo J, Lasebae A, Aiash M, Luo Y. 6lowpan: a study on QoS security threats and countermeasures using intrusion detection system approach. International Journal of Communication Systems September 2012; 25(9):11891212. – reference: Agah A, Das SK. Preventing DoS attacks in wireless sensor networks: a repeated game theory approach. International Journal of Network Security 2007; 5(2):145-153. – reference: Chen R-M, Hsieh K-T. Effective allied network security system based on designed scheme with conditional legitimate probability against distributed network attacks and intrusions. International Journal of Communication Systems May 2012; 25(5):672-688. – reference: Ozdemir S, Xiao Y. Secure data aggregation in wireless sensor networks: a comprehensive overview. Computer Networks 2009; 53:2022-2037. – reference: Hsieh MY, Huang YM, Chao HC. Adaptive security design with malicious node detection in cluster-based sensor networks. Computer Communications 2007; 30:2385-2400. – reference: Khan AUR, Madani SA, Hayat K, Khan SU, Sharma N. Clustering-based power-controlled routing for mobile wireless sensor networks. International Journal of Communication Systems April 2012; 25(4):529-542. – reference: Oliviera LB, Ferreira A, Vilaça MA, Wong HC, Bern M, Dahab R, Loureiro AAF. SecLEACH-on the security of clustered sensor networks. Signal Processing 2007; 87:2882-2895. – reference: Ibriq J, Mahgoub I. Hikes: hierarchical key establishment scheme for wireless sensor networks. International Journal of Communication Systems November 2012. DOI: 10.1002/dac.2438. – reference: Hsin Lai G, Chen C-M. Detecting denial of service attacks in sensor networks. Journal of Computers January 2008; 4(18). – reference: Hu F, Sharma N. Security considerations in ad hoc sensor networks. Ad Hoc Networks 2005; 3:69-89. – reference: Son J-H, Luo H, Seo S-W. Denial of service attack-resistant flooding authentication in wireless sensor networks. Computer Communications 2010; 33:1531-1542. – reference: Hamieh A, Ben-Othman J. Detection of jamming attacks in wireless ad hoc networks using error distribution. IEEE International Conference on Communications (ICC) June 2009: 1-6. – reference: Castellano G, Fanelli AM, Torsello MA. A neuro-fuzzy collaborative filtering approach for web recommendation. International Journal of Communication Systems 2007; 1(1):27-39. – reference: Islam MH, Nadeem K, Khan SA. Optimal sensor placement for detection against distributed denial of service attacks. Pakistan Journal of Engineering & Applied Sciences 2009; 4:80-92. – reference: Agah A, Das SK. Preventing DoS attacks in wireless sensor networks: a repeated game theory approach. International Journal of Network Security September 2007; 5(2):145-153. – reference: Fang S, Berber SM, Swain AK. Energy distribution-aware clustering algorithm for dense wireless sensor networks. International Journal of Communication Systems September-October 2010; 23(9-10):12231251. – reference: Claycomb WR, Shin D. A novel node level security policy framework for wireless sensor networks. Journal of Network and Computer Applications 2011; 34:418-428. – year: 2012 article-title: Hikes: hierarchical key establishment scheme for wireless sensor networks publication-title: International Journal of Communication Systems – start-page: 173 year: 2012 end-page: 177 – volume: 4 start-page: 219 issue: 4 year: 2012 end-page: 231 article-title: Competitive clustering algorithms based on ultrametric properties publication-title: Journal of Computational Science (Elsevier) – volume: 1 start-page: 27 issue: 1 year: 2007 end-page: 39 article-title: A neuro‐fuzzy collaborative filtering approach for web recommendation publication-title: International Journal of Communication Systems – volume: 25 start-page: 672 issue: 5 year: 2012 end-page: 688 article-title: Effective allied network security system based on designed scheme with conditional legitimate probability against distributed network attacks and intrusions publication-title: International Journal of Communication Systems – 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Snippet	SUMMARYThis paper presents a novel approach for detecting denial of service attacks. In particular, the concern is on the sleeping deprivation attacks such as... This paper presents a novel approach for detecting denial of service attacks. In particular, the concern is on the sleeping deprivation attacks such as the... SUMMARY This paper presents a novel approach for detecting denial of service attacks. In particular, the concern is on the sleeping deprivation attacks such as...
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SubjectTerms	Algorithms Clustering Computer Science Denial of service attacks DoS attack FFUCA Flooding LEACH Mathematical models Remote sensors Sensors Wireless networks WSN
Title	Recursive-clustering-based approach for denial of service (DoS) attacks in wireless sensors networks
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