A Survey of Intrusion Detection Systems in Wireless Sensor Networks

By Ismail Butun, Salvatore Domenic Morgera, Ravi Sankar. IEEE Communications Surveys and Tutorials, 2014

968 citations recorded by the source corpus.

Subfields: Computer Networks and Communications

View Paper: https://www.semanticscholar.org/paper/8e2527113c652a25dad5a8af72a67f2d0bbb2706

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In Computer Networks and Communications

Citations in the corpus

A Review of Intrusion Detection Systems Using Machine and Deep Learning in Internet of Things: Challenges, Solutions and Future Directions (2020, background): “Having the advantage of not requiring any learning phase after specifying a rule set [105], these techniques suffer from lack of adaptability to varied environments and are liable to errors in specifications [19].”
Machine Learning Based Solutions for Security of Internet of Things (IoT): A Survey (2020, background): “In the past few years, ML techniques have been advanced remarkably for IoT security purposes [85], [86].”
Security for the Internet of Things: A Survey of Existing Protocols and Open Research Issues (2015, positive): “mechanisms, and existing works on intrusion detection for sensor networks [86]–[88] may provide useful guidance in developing appropriate mechanisms for 6LoWPAN-based IoT”
A survey of intrusion detection in Internet of Things (2017, background): “nologies related to IoT such as mobile ad hoc networks (MANETs) [27, 28, 29], wireless sensor networks (WSNs) [30, 31, 32], cloud computing [33] and cyber-physical systems [34].”
A Roadmap Toward the Resilient Internet of Things for Cyber-Physical Systems (2018, background): “The expected or faulty behavior is represented either via formal models or specifications (runtime verification) [29], [30], signatures describing attack behaviors [23], [24], learned models (classification, statistics) [23], [24], [31], [39], clusters or the data instances itself (nearest-neighbor)”
Machine Learning in IoT Security: Current Solutions and Future Challenges (2019, neutral): “Similarly, in [161], [162], the authors focused”
WSN-DS: A Dataset for Intrusion Detection Systems in Wireless Sensor Networks (2016, background): “Unfortunately, achieving this objective becomes a major challenge because of the constrained resources of WSNs including battery energy, memory, and processing capabilities [4].”
Security of the Internet of Things: Vulnerabilities, Attacks, and Countermeasures (2019, background): “1: To monitor environment-related events (such as wildfire, earthquake, ocean, pollution, water quality, wildlife), to collect information regarding human-related activities and observation of human behavior (such as elder-care, nursery, healthcare), to provide mission-critical information (such as ”
IoT Elements, Layered Architectures and Security Issues: A Comprehensive Survey (2018, methodology): “Smart grid [71], environmental monitoring [72] and an intrusion detection system [73,74] are the applications of IoT in which a wireless sensors network is used.”
Network Intrusion Detection for IoT Security Based on Learning Techniques (2019, background): “two reasons; first because many surveys have treated it in details like [28], [116]–[118]; second, because our survey concentrates on IoT systems with its heterogeneity and all the”
Toward Information Privacy for the Internet of Things: A Nonparametric Learning Approach (2018, background): “INTRODUCTION S ENSOR networks have seen widespread applications in industrial, military, and civilian monitoring applications like intrusion detection, target tracking, leakage detection and fall detection [1]–[7].”
A Survey of Multi-Objective Optimization in Wireless Sensor Networks: Metrics, Algorithms, and Open Problems (2016, background): “Tracking applications include habitat tracking [56], traffic tracking [57], military target tracking [58], etc.”
Internet of things security: A top-down survey (2018, background): “Some surveys [25, 89] have discussed intrusion detection systems (IDS) in wireless sensor networks and Internet of Things and have provided analysis and comparison of the main existing IDSs.”
A Two-Layer Dimension Reduction and Two-Tier Classification Model for Anomaly-Based Intrusion Detection in IoT Backbone Networks (2019, methodology): “The Network layer not only serves as a backbone for connecting different IoT devices, but also provides opportunities for deploying network-based security defense mechanisms such as Network Intrusion Detection Systems (NIDS) [5]–[7].”
Survey of intrusion detection systems: techniques, datasets and challenges (2019, methodology): “AIDS can be classified into a number of categories based on the method used for training, for instance, statistical based, knowledge-based and machine learning based (Butun et al., 2014).”
IoT security: Review, blockchain solutions, and open challenges (2017, background): “Similarly, the authors in [12, 13, 14] target a comparative evaluation of intrusion detection systems.”
Intrusion detection systems for IoT-based smart environments: a survey (2018, methodology): “[48] recommended using a distributed IDS scheme for mobile applications, a centralized IDS scheme for stationary applications and a hierarchical IDS scheme for cluster-based applications.”