Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey

Wireless sensor networks (WSNs) consist of autonomous and resource-limited devices. The devices cooperate to monitor one or more physical phenomena within an area of interest. WSNs operate as stochastic systems because of randomness in the monitored environments. For long service time and low maintenance cost, WSNs require adaptive and robust methods to address data exchange, topology formulation, resource and power optimization, sensing coverage and object detection, and security challenges. In these problems, sensor nodes are to make optimized decisions from a set of accessible strategies to achieve design goals. This survey reviews numerous applications of the Markov decision process (MDP) framework, a powerful decision-making tool to develop adaptive algorithms and protocols for WSNs. Furthermore, various solution methods are discussed and compared to serve as a guide for using MDPs in WSNs

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

ETARP: An Energy Efficient Trust-Aware Routing Protocol for Wireless Sensor Networks

his paper presents a new routing protocol called Secure and Energy Aware Routing Protocol (ETARP) designed for energy efficiency and security for wireless sensor networks (WSNs). ETARP attempts to deal with WSN applications operating in extreme environments such as the battleield. The key part of the routing protocol is route selection based on utility theory. The concept of utility is a novel approach to simultaneously factor energy eiciency and trustworthiness of routes in the routing protocol. ETARP discovers and selects routes on the basis of maximum utility with incurring additional cost in overhead compared to the commonAODV (Ad Hoc On Demand Distance Vector) routing protocol. Simulation results show that, in comparison to previously proposed routing protocols, namely, AODV-EHA and LTB-AODV (Light-Weight Trust-Based Routing Protocol), the proposed ETARP can keep the same security level while achieving more energy eiciency for data packet delivery

Markov decision processes with applications in wireless sensor networks: A survey

Ministry of Education, Singapore under its Academic Research Funding Tier

Emerging Communications for Wireless Sensor Networks

Wireless sensor networks are deployed in a rapidly increasing number of arenas, with uses ranging from healthcare monitoring to industrial and environmental safety, as well as new ubiquitous computing devices that are becoming ever more pervasive in our interconnected society. This book presents a range of exciting developments in software communication technologies including some novel applications, such as in high altitude systems, ground heat exchangers and body sensor networks. Authors from leading institutions on four continents present their latest findings in the spirit of exchanging information and stimulating discussion in the WSN community worldwide

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

Principles of Physical Layer Security in Multiuser Wireless Networks: A Survey

This paper provides a comprehensive review of the domain of physical layer security in multiuser wireless networks. The essential premise of physical-layer security is to enable the exchange of confidential messages over a wireless medium in the presence of unauthorized eavesdroppers without relying on higher-layer encryption. This can be achieved primarily in two ways: without the need for a secret key by intelligently designing transmit coding strategies, or by exploiting the wireless communication medium to develop secret keys over public channels. The survey begins with an overview of the foundations dating back to the pioneering work of Shannon and Wyner on information-theoretic security. We then describe the evolution of secure transmission strategies from point-to-point channels to multiple-antenna systems, followed by generalizations to multiuser broadcast, multiple-access, interference, and relay networks. Secret-key generation and establishment protocols based on physical layer mechanisms are subsequently covered. Approaches for secrecy based on channel coding design are then examined, along with a description of inter-disciplinary approaches based on game theory and stochastic geometry. The associated problem of physical-layer message authentication is also introduced briefly. The survey concludes with observations on potential research directions in this area.Comment: 23 pages, 10 figures, 303 refs. arXiv admin note: text overlap with arXiv:1303.1609 by other authors. IEEE Communications Surveys and Tutorials, 201

DMN2SC: Detecting Malicious Nodes with 2-hop Secure Channel Support in Wireless Sensor Networks

Security in wireless sensor networks is critical due to its way of open communication. In this paper we have considered suite of attacks and provided a solution to detect malicious nodes. In literature, many schemes have been proposed to mitigate such attacks but very few detect the malicious nodes effectively and also no single solution detects all attacks. In the proposed approach, each node chooses the parent node for forwarding the packet towards Sink. Each node adds its identity as a routing path marker and encrypts only the bytes added by a node in packet before forwarding to parent. Child node observes the parent, handles acknowledgement from 2-hop distance node and decides the trust on parent based on successful and unsuccessful transactions. Data transmission is divided into multiple rounds of equal time duration. Each node sends a trust value report via multiple paths to Sink at the end of each round. Sink identifies the malicious node based on the number of packets a node participates in forwarding and also based on the trust value report sent from each node for its parent. Each node chooses the parent node at the beginning of a round based on its own observation on parent to recover itself from malicious parent node. With the combination of trust factor, 2-hop acknowledgement and fixed path routing to detect malicious activity, simulation results show that proposed method detect malicious nodes efficiently and early, and also with low percentage of false detection, compared to other recently proposed approaches

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