Web spider defense technique in wireless sensor networks

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

Analisis Penerapan Teknik Pertahanan Jaring Laba - Laba untuk Meningkatkan Akurasi Deteksi Serangan pada Wireless Sensor Network (WSN)

Menjamin keamanan dan privasi merupakan salah satu prioritas tertinggi dalam WSN karena data yang dikumpulkan oleh sensor node tidak jarang merupakan data yang bersifat rahasia. Terdapat sebuah aplikasi perangkat lunak atau perangkat keras yang dapat mendeteksi aktivitas mencurigakan dalam sebuah sistem atau jaringan berbasis nirkabel, yaitu Wireless Intrusion Detection System (WIDS). Namun, dari sekian banyak teknik pendekatan untuk WIDS belum ada yang dapat sepenuhnya terhindar dari kesalahan berupa false negative maupun false positive. Mekanisme cara kerja teknik pertahanan jaring laba – laba akan diterapkan pada alur kerja WIDS yang dibangun dengan tujuan mengurangi adanya false negative. Penerapannya dalam sistem nyata adalah memberikan delay untuk setiap paket yang masuk. Metode pengujian yang dilakukan berupa pengujian deteksi serangan dan perhitungan false negative. Pengujian deteksi serangan dilakukan dengan memberikan serangan inside attack berupa serangan access point spoofing dan serangan de-authentication flood. Hasil dari pengujian deteksi serangan menunjukkan bahwa WIDS mampu mendeteksi adanya serangan inside attack. Sementara perhitungan false negative mendapatkan hasil bahwa seiring ditambahkannya waktu delay, presentase false negative yang didapatkan mengalami penurunan namun kemudian dapat naik kembali. Pemberian waktu delay paling ideal kurang lebih 500 ms dengan tingkat presentase false negative berkurang hingga 66.37%. Kata kunci : false negative, Wireless Intrusion Detection System (WIDS), sistem keamanan, teknik pertahanan jaring laba-laba, Wireless Sensor Network (WSN)

IoT Crawler with Behavior Analyzer at Fog layer for Detecting Malicious Nodes

The limitations in terms of power and processing in IoT (Internet of Things) nodes make nodes an easy prey for malicious attacks, thus threatening business and industry. Detecting malicious nodes before they trigger an attack is highly recommended. The paper introduces a special purpose IoT crawler that works as an inspector to catch malicious nodes. This crawler is deployed in the Fog layer to inherit its capabilities, and to be an intermediate connection between the things and the cloud computing nodes. The crawler collects data streams from IoT nodes, upon a priority criterion. A behavior analyzer, with a machine learning core, detects malicious nodes according to the extracted node behavior from the crawler collected data streams. The performance of the behavior analyzer was investigated using three machine learning algorithms: Adaboost, Random forest and Extra tree. The behavior analyzer produces better testing accuracy, for the tested data, when using Extra tree compared to Adaboost and Random forest; it achieved 98.3% testing accuracy with Extra tree

Proceedings of the 2004 ONR Decision-Support Workshop Series: Interoperability

In August of 1998 the Collaborative Agent Design Research Center (CADRC) of the California Polytechnic State University in San Luis Obispo (Cal Poly), approached Dr. Phillip Abraham of the Office of Naval Research (ONR) with the proposal for an annual workshop focusing on emerging concepts in decision-support systems for military applications. The proposal was considered timely by the ONR Logistics Program Office for at least two reasons. First, rapid advances in information systems technology over the past decade had produced distributed collaborative computer-assistance capabilities with profound potential for providing meaningful support to military decision makers. Indeed, some systems based on these new capabilities such as the Integrated Marine Multi-Agent Command and Control System (IMMACCS) and the Integrated Computerized Deployment System (ICODES) had already reached the field-testing and final product stages, respectively. Second, over the past two decades the US Navy and Marine Corps had been increasingly challenged by missions demanding the rapid deployment of forces into hostile or devastate dterritories with minimum or non-existent indigenous support capabilities. Under these conditions Marine Corps forces had to rely mostly, if not entirely, on sea-based support and sustainment operations. Particularly today, operational strategies such as Operational Maneuver From The Sea (OMFTS) and Sea To Objective Maneuver (STOM) are very much in need of intelligent, near real-time and adaptive decision-support tools to assist military commanders and their staff under conditions of rapid change and overwhelming data loads. In the light of these developments the Logistics Program Office of ONR considered it timely to provide an annual forum for the interchange of ideas, needs and concepts that would address the decision-support requirements and opportunities in combined Navy and Marine Corps sea-based warfare and humanitarian relief operations. The first ONR Workshop was held April 20-22, 1999 at the Embassy Suites Hotel in San Luis Obispo, California. It focused on advances in technology with particular emphasis on an emerging family of powerful computer-based tools, and concluded that the most able members of this family of tools appear to be computer-based agents that are capable of communicating within a virtual environment of the real world. From 2001 onward the venue of the Workshop moved from the West Coast to Washington, and in 2003 the sponsorship was taken over by ONR’s Littoral Combat/Power Projection (FNC) Program Office (Program Manager: Mr. Barry Blumenthal). Themes and keynote speakers of past Workshops have included: 1999: ‘Collaborative Decision Making Tools’ Vadm Jerry Tuttle (USN Ret.); LtGen Paul Van Riper (USMC Ret.);Radm Leland Kollmorgen (USN Ret.); and, Dr. Gary Klein (KleinAssociates) 2000: ‘The Human-Computer Partnership in Decision-Support’ Dr. Ronald DeMarco (Associate Technical Director, ONR); Radm CharlesMunns; Col Robert Schmidle; and, Col Ray Cole (USMC Ret.) 2001: ‘Continuing the Revolution in Military Affairs’ Mr. Andrew Marshall (Director, Office of Net Assessment, OSD); and,Radm Jay M. Cohen (Chief of Naval Research, ONR) 2002: ‘Transformation ... ’ Vadm Jerry Tuttle (USN Ret.); and, Steve Cooper (CIO, Office ofHomeland Security) 2003: ‘Developing the New Infostructure’ Richard P. Lee (Assistant Deputy Under Secretary, OSD); and, MichaelO’Neil (Boeing) 2004: ‘Interoperability’ MajGen Bradley M. Lott (USMC), Deputy Commanding General, Marine Corps Combat Development Command; Donald Diggs, Director, C2 Policy, OASD (NII

Algorithms based on spider daddy long legs for finding the optimal route in securing mobile ad hoc networks

Mobile ad hoc networks (MANETs) are wireless networks that are subject to severe attacks, such as the black hole attack. One of the goals in the research is to find a method to prevent black hole attacks without decreasing network throughput or increasing routing overhead. The routing mechanism in define uses route requests (RREQs; for discovering routes) and route replies (RREPs; for receiving paths). However, this mechanism is vulnerable to attacks by malicious black hole nodes. The mechanism is developed to find the shortest secure path and to reduce overhead using the information that is available in the routing tables as an input to propose a more complex nature-inspired algorithm. The new method is called the Daddy Long-Legs Algorithm (PGO-DLLA), which modifies the standard AODV and optimizes the routing process. This method avoids dependency exclusively on the hop counts and destination sequence numbers (DSNs) that are exploited by malicious nodes in the standard AODV protocol. The experiment by performance metrics End-to-End delay and packet delivery ratio are compared in order to determine the best effort traffic. The results showed the PGO-DLLA improvement of the shortest and secure routing from black hole attack in MANET. In addition, the results indicate better performance than the related works algorithm with respect to all metrics excluding throughput which AntNet is best in routing when the pause time be more than 40 seconds. PGODLLA is able to improve the route discovery against the black hole attacks in AODV. Experiments in this thesis have shown that PGO-DLLA is able to reduce the normalized routing load, end-to-end delay, and packet loss and has a good throughput and packet delivery ratio when compared with the standard AODV protocol, BAODV protocol, and the current related protocols that enhance the routing security of the AODV protocols

Towards Cyber Security for Low-Carbon Transportation: Overview, Challenges and Future Directions

In recent years, low-carbon transportation has become an indispensable part as sustainable development strategies of various countries, and plays a very important responsibility in promoting low-carbon cities. However, the security of low-carbon transportation has been threatened from various ways. For example, denial of service attacks pose a great threat to the electric vehicles and vehicle-to-grid networks. To minimize these threats, several methods have been proposed to defense against them. Yet, these methods are only for certain types of scenarios or attacks. Therefore, this review addresses security aspect from holistic view, provides the overview, challenges and future directions of cyber security technologies in low-carbon transportation. Firstly, based on the concept and importance of low-carbon transportation, this review positions the low-carbon transportation services. Then, with the perspective of network architecture and communication mode, this review classifies its typical attack risks. The corresponding defense technologies and relevant security suggestions are further reviewed from perspective of data security, network management security and network application security. Finally, in view of the long term development of low-carbon transportation, future research directions have been concerned.Comment: 34 pages, 6 figures, accepted by journal Renewable and Sustainable Energy Review

Systems and algorithms for wireless sensor networks based on animal and natural behavior

In last decade, there have been many research works about wireless sensor networks (WSNs) focused on improving the network performance as well as increasing the energy efficiency and communications effectiveness. Many of these new mechanisms have been implemented using the behaviors of certain animals, such as ants, bees, or schools of fish.These systems are called bioinspired systems and are used to improve aspects such as handling large-scale networks, provide dynamic nature, and avoid resource constraints, heterogeneity, unattended operation, or robustness, amongmanyothers.Therefore, thispaper aims to studybioinspired mechanisms in the field ofWSN, providing the concepts of these behavior patterns in which these new approaches are based. The paper will explain existing bioinspired systems in WSNs and analyze their impact on WSNs and their evolution. In addition, we will conduct a comprehensive review of recently proposed bioinspired systems, protocols, and mechanisms. Finally, this paper will try to analyze the applications of each bioinspired mechanism as a function of the imitated animal and the deployed application. Although this research area is considered an area with highly theoretical content, we intend to show the great impact that it is generating from the practical perspective.Sendra, S.; Parra Boronat, L.; Lloret, J.; Khan, S. (2015). Systems and algorithms for wireless sensor networks based on animal and natural behavior. International Journal of Distributed Sensor Networks. 2015:1-19. doi:10.1155/2015/625972S1192015Iram, R., Sheikh, M. I., Jabbar, S., & Minhas, A. A. (2011). Computational intelligence based optimization in wireless sensor network. 2011 International Conference on Information and Communication Technologies. doi:10.1109/icict.2011.5983561Lloret, J., Bosch, I., Sendra, S., & Serrano, A. (2011). A Wireless Sensor Network for Vineyard Monitoring That Uses Image Processing. 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Air Force Institute of Technology Research Report 2009

This report summarizes the research activities of the Air Force Institute of Technology’s Graduate School of Engineering and Management. It describes research interests and faculty expertise; lists student theses/dissertations; identifies research sponsors and contributions; and outlines the procedures for contacting the school. Included in the report are: faculty publications, conference presentations, consultations, and funded research projects. Research was conducted in the areas of Aeronautical and Astronautical Engineering, Electrical Engineering and Electro-Optics, Computer Engineering and Computer Science, Systems and Engineering Management, Operational Sciences, Mathematics, Statistics and Engineering Physics