11,619 research outputs found

    A Prototype for Intrusion Detection in Wireless Sensor Networks Using Data Mining Methods

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    The Wireless Sensor Networks (WSNs) are highly distributed networks of tiny, light-weight wireless nodes, placed in large numbers to monitor the environment or system. Monitoring the system includes the measurement of physical parameters such as pressure, temperature, relative humidity and passing their data to the main node (sink). WSN faces various security attacks which can affect the overall performance and security of the system. So, it is necessary to detect and prevent the attacks on WSN. Intrusion Detection is one of the major and efficient method against attacks. Intrusion Detection Systems can act as a second line of defence and it provides security primitives to prevent attacks against computer networks. This paper focuses on a hybrid approach for intrusion detection system (IDS) based on data mining techniques. The approach is clustering analysis with the aim to improve the detection rate and decrease the false alarm rate

    Web spider defense technique in wireless sensor networks

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    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

    A novel intrusion detection framework for wireless sensor networks

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    Abstract Vehicle cloud is a new idea that uses the benefits of wireless sensor networks (WSNs) and the concept of cloud computing to provide better services to the community. It is important to secure a sensor network to achieve better performance of the vehicle cloud. Wireless sensor networks are a soft target for intruders or adversaries to launch lethal attacks in its present configuration. In this paper, a novel intrusion detection framework is proposed for securing wireless sensor networks from routing attacks. The proposed system works in a distributed environment to detect intrusions by collaborating with the neighboring nodes. It works in two modes: online prevention allows safeguarding from those abnormal nodes that are already declared as malicious while offline detection finds those nodes that are being compromised by an adversary during the next epoch of time. Simulation results show that the proposed specification-based detection scheme performs extremely well and achieves high intrusion detection rate and low false positive rate

    Intrusion Detection Systems Based on Artificial Intelligence Techniques in Wireless Sensor Networks

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    [EN] Intrusion detection system (IDS) is regarded as the second line of defense against network anomalies and threats. IDS plays an important role in network security. There are many techniques which are used to design IDSs for specific scenario and applications. Artificial intelligence techniques are widely used for threats detection. This paper presents a critical study on genetic algorithm, artificial immune, and artificial neural network (ANN) based IDSs techniques used in wireless sensor network (WSN)The authors extend their appreciation to the Distinguished Scientist Fellowship Program(DSFP) at King Saud University for funding this research.Alrajeh, NA.; Lloret, J. (2013). Intrusion Detection Systems Based on Artificial Intelligence Techniques in Wireless Sensor Networks. International Journal of Distributed Sensor Networks. 2013(351047):1-6. https://doi.org/10.1155/2013/351047S16201335104

    Implementation of Lessar Algorithm for Analysis of Network Intrusion Detection System in Wireless Sensor Networks

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    Wireless sensor networks are the result of multiple technological advances in electronics, nanotechnology, wireless communications, computing power, network development and robotics. Compose distributed systems devices usually composed of integrated, including at least CPU, radio, and sensors / actuators number. The wireless sensor networks (WSN) heterogeneous networks are formed by sensors, gateways and backend resources very limited physical. The sensors can measure parameters such as temperature, movement, lighting, humidity, etc..; the gateways establish the link with networks traditional and familiar. The back ends are responsible for the processing and display unit the captured data. Although several studies showed WSN middleware, has not been achieved with this industry acceptance due mainly to the different methodologies programming. The teams consist of WSN lowest consumption, costs and form factors. The reality is quite different environments applications are supported with equipment more powerful and fed by redundant power networks. The current article describes then implementation of lesser algorithm for analysis of network intrusion detection system in wireless sensor networks

    Intrusion Prevention and Detection in Wireless Sensor Networks

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    The broadcast nature of the transmission medium in wireless sensor networks makes information more vulnerable than in wired applications. In this dissertation we first propose a distributed, deterministic key management protocol designed to satisfy authentication and confidentiality, without the need of a key distribution center. Next we propose Scatter, a secure code authentication scheme for efficient reprogramming sensor networks. Scatter avoids the use of Elliptic Key Cryptography and manages to surpass all previous attempts for secure code dissemination in terms of energy consumption and time efficiency. Next we introduce the problem of intrusion detection in sensor networks. We define the problem formally based on a generic system model and we prove a necessary and sufficient condition for successful detection of the attacker. Finally we present the architecture and implementation of an intrusion detection system which is based on a distributed architecture and it is lightweight enough to run on the nodes

    Hierarchical Design Based Intrusion Detection System For Wireless Ad hoc Network

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    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

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

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    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
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