6,914 research outputs found

    Web spider defense technique in wireless sensor networks

    Full text link
    Wireless sensor networks (WSNs) are currently widely used in many environments. Some of them gather many critical data, which should be protected from intruders. Generally, when an intruder is detected in the WSN, its connection is immediately stopped. But this way does not let the network administrator gather information about the attacker and/or its purposes. In this paper, we present a bioinspired system that uses the procedure taken by the web spider when it wants to catch its prey. We will explain how all steps performed by the web spider are included in our system and we will detail the algorithm and protocol procedure. A real test bench has been implemented in order to validate our system. It shows the performance for different response times, the CPU and RAM consumption, and the average and maximum values for ping and tracert time responses using constant delay and exponential jitter.This work has been partially supported by the "Ministerio de Ciencia e Innovacion", through the "Plan Nacional de I+D+i 2008-2011" in the "Subprograma de Proyectos de Investigacion Fundamental", Project TEC2011-27516.Cánovas Solbes, A.; Lloret, J.; Macias Lopez, EM.; Suarez Sarmiento, A. (2014). Web spider defense technique in wireless sensor networks. International Journal of Distributed Sensor Networks. 2014:1-7. https://doi.org/10.1155/2014/348606S172014Bri, D., Garcia, M., Lloret, J., & Dini, P. (2009). Real Deployments of Wireless Sensor Networks. 2009 Third International Conference on Sensor Technologies and Applications. doi:10.1109/sensorcomm.2009.69Sendra, S., Lloret, J., Garcia, M., & Toledo, J. F. (2011). Power Saving and Energy Optimization Techniques for Wireless Sensor Neworks (Invited Paper). Journal of Communications, 6(6). doi:10.4304/jcm.6.6.439-459Xie, M., Han, S., Tian, B., & Parvin, S. (2011). Anomaly detection in wireless sensor networks: A survey. Journal of Network and Computer Applications, 34(4), 1302-1325. doi:10.1016/j.jnca.2011.03.004Yu, Y., Li, K., Zhou, W., & Li, P. (2012). Trust mechanisms in wireless sensor networks: Attack analysis and countermeasures. Journal of Network and Computer Applications, 35(3), 867-880. doi:10.1016/j.jnca.2011.03.005Zhu, W. T., Zhou, J., Deng, R. H., & Bao, F. (2012). Detecting node replication attacks in wireless sensor networks: A survey. Journal of Network and Computer Applications, 35(3), 1022-1034. doi:10.1016/j.jnca.2012.01.002Maleh, Y., & Ezzati, A. (2013). A Review of Security Attacks and Intrusion Detection Schemes in Wireless Sensor Network. International Journal of Wireless & Mobile Networks, 5(6), 79-90. doi:10.5121/ijwmn.2013.5606Alrajeh, N. A., Khan, S., & Shams, B. (2013). Intrusion Detection Systems in Wireless Sensor Networks: A Review. International Journal of Distributed Sensor Networks, 9(5), 167575. doi:10.1155/2013/167575Sun, B., Osborne, L., Xiao, Y., & Guizani, S. (2007). Intrusion detection techniques in mobile ad hoc and wireless sensor networks. IEEE Wireless Communications, 14(5), 56-63. doi:10.1109/mwc.2007.4396943Fatema, N., & Brad, R. (2013). Attacks and Counterattacks on Wireless Sensor Networks. International Journal of Ad hoc, Sensor & Ubiquitous Computing, 4(6), 1-15. doi:10.5121/ijasuc.2013.4601Ankala, R. P., Kavitha, D., & Haritha, D. (2011). MOBILE AGENT BASED ROUTING in MANETS –ATTACKS & DEFENCES. Network Protocols and Algorithms, 3(4). doi:10.5296/npa.v3i4.1351Hylsberg Jacobsen, R., Zhang, Q., & Skjødeberg Toftegaard, T. (2011). Bioinspired Principles for Large-Scale Networked Sensor Systems: An Overview. Sensors, 11(4), 4137-4151. doi:10.3390/s110404137Kofahi, N. (2013). An Empirical Study to Compare the Performance of some Symmetric and Asymmetric Ciphers. International Journal of Security and Its Applications, 7(5), 1-16. doi:10.14257/ijsia.2013.7.5.01Sisodia, M. S., & Raghuwanshi, V. (2011). Anomaly Base Network Intrusion Detection by Using Random Decision Tree and Random Projection: A Fast Network Intrusion Detection Technique. Network Protocols and Algorithms, 3(4). doi:10.5296/npa.v3i4.1342Zhijie, H., & Ruchuang, W. (2012). Intrusion Detection for Wireless Sensor Network Based on Traffic Prediction Model. Physics Procedia, 25, 2072-2080. doi:10.1016/j.phpro.2012.03.352Al-Gharabally, N., El-Sayed, N., Al-Mulla, S., & Ahmad, I. (2009). Wireless honeypots. Proceedings of the 2009 conference on Information Science, Technology and Applications - ISTA ’09. doi:10.1145/1551950.1551969Gopinath V.Success analysis of deception in wireless sensor networks [M.S. thesis]2010Oklahoma State UniversityZhongshan Zhang, Keping Long, Jianping Wang, & Dressler, F. (2014). On Swarm Intelligence Inspired Self-Organized Networking: Its Bionic Mechanisms, Designing Principles and Optimization Approaches. IEEE Communications Surveys & Tutorials, 16(1), 513-537. doi:10.1109/surv.2013.062613.00014Rathore, H., & Jha, S. (2013). Bio-inspired machine learning based Wireless Sensor Network security. 2013 World Congress on Nature and Biologically Inspired Computing. doi:10.1109/nabic.2013.6617852Alrajeh, N. A., & Lloret, J. (2013). Intrusion Detection Systems Based on Artificial Intelligence Techniques in Wireless Sensor Networks. International Journal of Distributed Sensor Networks, 9(10), 351047. doi:10.1155/2013/351047Amirkolaei M. K.Enhancing bio-inspired intrusion response in Ad-hoc networks [Ph.D. thesis]August 2013Edinburgh, UKEdinburgh Napier Universityhttp://researchrepository.napier.ac.uk/6533/Muraleedharan, R., & Osadciw, L. A. (2009). An intrusion detection framework for Sensor Networks using Honeypot and Swarm Intelligence. Proceedings of the 6th Annual International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services. doi:10.4108/icst.mobiquitous2009.7084Hortos, W. S. (2012). Bio-inspired, cross-layer protocol design for intrusion detection and identification in wireless sensor networks. 37th Annual IEEE Conference on Local Computer Networks -- Workshops. doi:10.1109/lcnw.2012.6424040Benahmed, K., Merabti, M., & Haffaf, H. (2012). Inspired Social Spider Behavior for Secure Wireless Sensor Networks. International Journal of Mobile Computing and Multimedia Communications, 4(4), 1-10. doi:10.4018/jmcmc.2012100101Herberstein, M. E. (Ed.). (2009). Spider Behaviour. doi:10.1017/cbo9780511974496Ficco, M. (2010). Achieving Security by Intrusion-Tolerance Based on Event Correlation. Network Protocols and Algorithms, 2(3). doi:10.5296/npa.v2i3.42

    Intrusion-aware Alert Validation Algorithm for Cooperative Distributed Intrusion Detection Schemes of Wireless Sensor Networks

    Get PDF
    Existing anomaly and intrusion detection schemes of wireless sensor networks have mainly focused on the detection of intrusions. Once the intrusion is detected, an alerts or claims will be generated. However, any unidentified malicious nodes in the network could send faulty anomaly and intrusion claims about the legitimate nodes to the other nodes. Verifying the validity of such claims is a critical and challenging issue that is not considered in the existing cooperative-based distributed anomaly and intrusion detection schemes of wireless sensor networks. In this paper, we propose a validation algorithm that addresses this problem. This algorithm utilizes the concept of intrusion-aware reliability that helps to provide adequate reliability at a modest communication cost. In this paper, we also provide a security resiliency analysis of the proposed intrusion-aware alert validation algorithm.Comment: 19 pages, 7 figure

    A Survey on Wireless Sensor Network Security

    Full text link
    Wireless sensor networks (WSNs) have recently attracted a lot of interest in the research community due their wide range of applications. Due to distributed nature of these networks and their deployment in remote areas, these networks are vulnerable to numerous security threats that can adversely affect their proper functioning. This problem is more critical if the network is deployed for some mission-critical applications such as in a tactical battlefield. Random failure of nodes is also very likely in real-life deployment scenarios. Due to resource constraints in the sensor nodes, traditional security mechanisms with large overhead of computation and communication are infeasible in WSNs. Security in sensor networks is, therefore, a particularly challenging task. This paper discusses the current state of the art in security mechanisms for WSNs. Various types of attacks are discussed and their countermeasures presented. A brief discussion on the future direction of research in WSN security is also included.Comment: 24 pages, 4 figures, 2 table

    Hierarchical Design Based Intrusion Detection System For Wireless Ad hoc Network

    Full text link
    In recent years, wireless ad hoc sensor network becomes popular both in civil and military jobs. However, security is one of the significant challenges for sensor network because of their deployment in open and unprotected environment. As cryptographic mechanism is not enough to protect sensor network from external attacks, intrusion detection system needs to be introduced. Though intrusion prevention mechanism is one of the major and efficient methods against attacks, but there might be some attacks for which prevention method is not known. Besides preventing the system from some known attacks, intrusion detection system gather necessary information related to attack technique and help in the development of intrusion prevention system. In addition to reviewing the present attacks available in wireless sensor network this paper examines the current efforts to intrusion detection system against wireless sensor network. In this paper we propose a hierarchical architectural design based intrusion detection system that fits the current demands and restrictions of wireless ad hoc sensor network. In this proposed intrusion detection system architecture we followed clustering mechanism to build a four level hierarchical network which enhances network scalability to large geographical area and use both anomaly and misuse detection techniques for intrusion detection. We introduce policy based detection mechanism as well as intrusion response together with GSM cell concept for intrusion detection architecture.Comment: 16 pages, International Journal of Network Security & Its Applications (IJNSA), Vol.2, No.3, July 2010. arXiv admin note: text overlap with arXiv:1111.1933 by other author
    corecore