Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications

Wireless sensor networks monitor dynamic environments that change rapidly over time. This dynamic behavior is either caused by external factors or initiated by the system designers themselves. To adapt to such conditions, sensor networks often adopt machine learning techniques to eliminate the need for unnecessary redesign. Machine learning also inspires many practical solutions that maximize resource utilization and prolong the lifespan of the network. In this paper, we present an extensive literature review over the period 2002-2013 of machine learning methods that were used to address common issues in wireless sensor networks (WSNs). The advantages and disadvantages of each proposed algorithm are evaluated against the corresponding problem. We also provide a comparative guide to aid WSN designers in developing suitable machine learning solutions for their specific application challenges.Comment: Accepted for publication in IEEE Communications Surveys and Tutorial

Security techniques for sensor systems and the Internet of Things

Sensor systems are becoming pervasive in many domains, and are recently being generalized by the Internet of Things (IoT). This wide deployment, however, presents significant security issues. We develop security techniques for sensor systems and IoT, addressing all security management phases. Prior to deployment, the nodes need to be hardened. We develop nesCheck, a novel approach that combines static analysis and dynamic checking to efficiently enforce memory safety on TinyOS applications. As security guarantees come at a cost, determining which resources to protect becomes important. Our solution, OptAll, leverages game-theoretic techniques to determine the optimal allocation of security resources in IoT networks, taking into account fixed and variable costs, criticality of different portions of the network, and risk metrics related to a specified security goal. Monitoring IoT devices and sensors during operation is necessary to detect incidents. We design Kalis, a knowledge-driven intrusion detection technique for IoT that does not target a single protocol or application, and adapts the detection strategy to the network features. As the scale of IoT makes the devices good targets for botnets, we design Heimdall, a whitelist-based anomaly detection technique for detecting and protecting against IoT-based denial of service attacks. Once our monitoring tools detect an attack, determining its actual cause is crucial to an effective reaction. We design a fine-grained analysis tool for sensor networks that leverages resident packet parameters to determine whether a packet loss attack is node- or link-related and, in the second case, locate the attack source. Moreover, we design a statistical model for determining optimal system thresholds by exploiting packet parameters variances. With our techniques\u27 diagnosis information, we develop Kinesis, a security incident response system for sensor networks designed to recover from attacks without significant interruption, dynamically selecting response actions while being lightweight in communication and energy overhead

Smart Wireless Sensor Networks

The recent development of communication and sensor technology results in the growth of a new attractive and challenging area - wireless sensor networks (WSNs). A wireless sensor network which consists of a large number of sensor nodes is deployed in environmental fields to serve various applications. Facilitated with the ability of wireless communication and intelligent computation, these nodes become smart sensors which do not only perceive ambient physical parameters but also be able to process information, cooperate with each other and self-organize into the network. These new features assist the sensor nodes as well as the network to operate more efficiently in terms of both data acquisition and energy consumption. Special purposes of the applications require design and operation of WSNs different from conventional networks such as the internet. The network design must take into account of the objectives of specific applications. The nature of deployed environment must be considered. The limited of sensor nodes� resources such as memory, computational ability, communication bandwidth and energy source are the challenges in network design. A smart wireless sensor network must be able to deal with these constraints as well as to guarantee the connectivity, coverage, reliability and security of network's operation for a maximized lifetime. This book discusses various aspects of designing such smart wireless sensor networks. Main topics includes: design methodologies, network protocols and algorithms, quality of service management, coverage optimization, time synchronization and security techniques for sensor networks

Intrusion detection in IPv6-enabled sensor networks.

In this research, we study efficient and lightweight Intrusion Detection Systems (IDS) for ad-hoc networks through the lens of IPv6-enabled Wireless Sensor Actuator Networks. These networks consist of highly constrained devices able to communicate wirelessly in an ad-hoc fashion, thus following the architecture of ad-hoc networks. Current state of the art IDS in IoT and WSNs have been developed considering the architecture of conventional computer networks, and as such they do not efficiently address the paradigm of ad-hoc networks, which is highly relevant in emerging network paradigms, such as the Internet of Things (IoT). In this context, the network properties of resilience and redundancy have not been extensively studied. In this thesis, we first identify a trade-off between the communication and energy overheads of an IDS (as captured by the number of active IDS agents in the network) and the performance of the system in terms of successfully identifying attacks. In order to fine-tune this trade-off, we model networks as Random Geometric Graphs; these are a rigorous approach that allows us to capture underlying structural properties of the network. We then introduce a novel IDS architectural approach that consists of a central IDS agent and set of distributed IDS agents deployed uniformly at random over the network area. These nodes are able to efficiently detect attacks at the networking layer in a collaborative manner by monitoring locally available network information provided by IoT routing protocols, such as RPL. The detailed experimental evaluation conducted in this research demonstrates significant performance gains in terms of communication overhead and energy dissipation while maintaining high detection rates. We also show that the performance of our IDS in ad-hoc networks does not rely on the size of the network but on fundamental underling network properties, such as the network topology and the average degree of the nodes. The experiments show that our proposed IDS architecture is resilient against frequent topology changes due to node failures

Energy efficient and secure wireless communications for wireless sensor networks

This dissertation considers wireless sensor networks (WSNs) operating in severe environments where energy efficiency and security are important factors. This main aim of this research is to improve routing protocols in WSNs to ensure efficient energy usage and protect against attacks (especially energy draining attacks) targeting WSNs. An enhancement of the existing AODV (Ad hoc On-Demand Distance Vector) routing protocol for energy efficiency, called AODV-Energy Harvesting Aware (AODVEHA), is proposed and evaluated. It not only inherits the advantages of AODV which are well suited to ad hoc networks, but also makes use of the energy harvesting capability of sensor nodes in the network. In addition to the investigation of energy efficiency, another routing protocol called Secure and Energy Aware Routing Protocol (ETARP) designed for energy efficiency and security of WSNs is presented. The key part of the ETARP is route selection based on utility theory, which is a novel approach to simultaneously factor energy efficiency and trustworthiness of routes in the routing protocol. Finally, this dissertation proposes a routing protocol to protect against a specific type of resource depletion attack called Vampire attacks. The proposed resource-conserving protection against energy draining (RCPED) protocol is independent of cryptographic methods, which brings advantage of less energy cost and hardware requirement. RCPED collaborates with existing routing protocols, detects abnormal sign of Vampire attacks and determines the possible attackers. Then routes are discovered and selected on the basis of maximum priority, where the priority that reflects the energy efficiency and safety level of route is calculated by means of Analytic Hierarchy Process (AHP). The proposed analytic model for the aforementioned routing solutions are verified by simulations. Simulations results validate the improvements of proposed routing approaches in terms of better energy efficiency and guarantee of security

Wireless Body Area Network (WBAN): A Survey on Architecture, Technologies, Energy Consumption, and Security Challenges

Wireless body area networks (WBANs) are a new advance utilized in recent years to increase the quality of human life by monitoring the conditions of patients inside and outside hospitals, the activities of athletes, military applications, and multimedia. WBANs consist of intelligent micro- or nano-sensors capable of processing and sending information to the base station (BS). Sensors embedded in the bodies of individuals can enable vital information exchange over wireless communication. Network forming of these sensors envisages long-term medical care without restricting patients’ normal daily activities as part of diagnosing or caring for a patient with a chronic illness or monitoring the patient after surgery to manage emergencies. This paper reviews WBAN, its security challenges, body sensor network architecture and functions, and communication technologies. The work reported in this paper investigates a significant security-level challenge existing in WBAN. Lastly, it highlights various mechanisms for increasing security and decreasing energy consumption

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

On reliable and secure RPL (routing protocol low-power and lossy networks) based monitoring and surveillance in oil and gas fields

Different efforts have been made to specify protocols and algorithms for the successful operation of the Internet of things Networks including, for instance, the Low Power and Lossy Networks (LLNs) and Linear Sensor Networks (LSNs). Into such efforts, IETF, the Internet Engineering Task Force, created a working group named, ROLL, to investigate the requirement of such networks and devising more efficient solutions. The effort of this group has resulted in the specification of the IPv6 Routing Protocol for LLNs (RPL), which was standardized in 2012. However, since the introduction of RPL, several studies have reported that it suffers from various limitations and weaknesses including scalability, slow convergence, unfairness of load distribution, inefficiency of bidirectional communication and security, among many others. For instance, a serious problem is RPL’s under-specification of DAO messages which may result in conflict and inefficient implementations leading to a poor performance and scalability issues. Furthermore, RPL has been found to suffer from several security issues including, for instance, the DAO flooding attack, in which the attacker floods the network with control messages aiming to exhaust network resources. Another fundamental issue is related to the scarcity of the studies that investigate RPL suitability for Linear Sensor Networks (LSN) and devising solution in the lieu of that.Motivated by these observations, the publications within this thesis aim to tackle some of the key gaps of the RPL by introducing more efficient and secure routing solutions in consideration of the specific requirements of LLNs in general and LSNs as a special case. To this end, the first publication proposes an enhanced version of RPL called Enhanced-RPL aimed at mitigating the memory overflow and the under-specification of the of DAOs messages. Enhanced-RPL has shown significant reduction in control messages overhead by up to 64% while maintaining comparable reliability to RPL. The second publication introduces a new technique to address the DAO attack of RPL which has been shown to be effective in mitigating the attack reducing the DAO overhead and latency by up to 205% and 181% respectively as well as increasing the PDR by up to 6% latency. The third and fourth publications focus on analysing the optimal placement of nodes and sink movement pattern (fixed or mobile) that RPL should adopt in LSNs. It was concluded based on the results obtained that RPL should opt for fixed sinks with 10 m distance between deployed nodes