Resilient networking in wireless sensor networks

This report deals with security in wireless sensor networks (WSNs), especially in network layer. Multiple secure routing protocols have been proposed in the literature. However, they often use the cryptography to secure routing functionalities. The cryptography alone is not enough to defend against multiple attacks due to the node compromise. Therefore, we need more algorithmic solutions. In this report, we focus on the behavior of routing protocols to determine which properties make them more resilient to attacks. Our aim is to find some answers to the following questions. Are there any existing protocols, not designed initially for security, but which already contain some inherently resilient properties against attacks under which some portion of the network nodes is compromised? If yes, which specific behaviors are making these protocols more resilient? We propose in this report an overview of security strategies for WSNs in general, including existing attacks and defensive measures. In this report we focus at the network layer in particular, and an analysis of the behavior of four particular routing protocols is provided to determine their inherent resiliency to insider attacks. The protocols considered are: Dynamic Source Routing (DSR), Gradient-Based Routing (GBR), Greedy Forwarding (GF) and Random Walk Routing (RWR)

Electronically-switched Directional Antennas for Low-power Wireless Networks: A Prototype-driven Evaluation

We study the benefits of electronically-switched directional antennas in low-power wireless networks. This antenna technology may improve energy efficiency by increasing the communication range and by alleviating contention in directions other than the destination, but in principle requires a dedicated network stack. Unlike most existing works, we start by characterizing a real-world antenna prototype, and apply this to an existing low-power wireless stack, which we adapt with minimal changes. Our results show that: i) the combination of a low-cost directional antenna and a conventional network stack already brings significant performance improvements, e.g., nearly halving the radio-on time per delivered packet; ii) the margin of improvement available to alternative clean-slate protocol designs is similarly large and concentrated in the control rather than the data plane; iii) by artificially modifying our antenna's link-layer model, we can point at further potential benefits opened by different antenna designs

An objective based classification of aggregation techniques for wireless sensor networks

Wireless Sensor Networks have gained immense popularity in recent years due to their ever increasing capabilities and wide range of critical applications. A huge body of research efforts has been dedicated to find ways to utilize limited resources of these sensor nodes in an efficient manner. One of the common ways to minimize energy consumption has been aggregation of input data. We note that every aggregation technique has an improvement objective to achieve with respect to the output it produces. Each technique is designed to achieve some target e.g. reduce data size, minimize transmission energy, enhance accuracy etc. This paper presents a comprehensive survey of aggregation techniques that can be used in distributed manner to improve lifetime and energy conservation of wireless sensor networks. Main contribution of this work is proposal of a novel classification of such techniques based on the type of improvement they offer when applied to WSNs. Due to the existence of a myriad of definitions of aggregation, we first review the meaning of term aggregation that can be applied to WSN. The concept is then associated with the proposed classes. Each class of techniques is divided into a number of subclasses and a brief literature review of related work in WSN for each of these is also presented

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

Self-Organized Routing For Wireless Micro-Sensor Networks

In this paper we develop an energy-aware self-organized routing algorithm for the networking of simple battery-powered wireless micro-sensors (as found, for example, in security or environmental monitoring applications). In these networks, the battery life of individual sensors is typically limited by the power required to transmit their data to a receiver or sink. Thus effective network routing algorithms allow us to reduce this power and extend both the lifetime and the coverage of the sensor network as a whole. However, implementing such routing algorithms with a centralized controller is undesirable due to the physical distribution of the sensors, their limited localization ability and the dynamic nature of such networks (given that sensors may fail, move or be added at any time and the communication links between sensors are subject to noise and interference). Against this background, we present a distributed mechanism that enables individual sensors to follow locally selfish strategies, which, in turn, result in the self-organization of a routing network with desirable global properties. We show that our mechanism performs close to the optimal solution (as computed by a centralized optimizer), it deals adaptively with changing sensor numbers and topology, and it extends the useful life of the network by a factor of three over the traditional approach

Security in Wireless Sensor Networks Employing MACGSP6

Wireless Sensor Networks (WSNs) have unique characteristics which constrain them; including small energy stores, limited computation, and short range communication capability. Most traditional security algorithms use cryptographic primitives such as Public-key cryptography and are not optimized for energy usage. Employing these algorithms for the security of WSNs is often not practical. At the same time, the need for security in WSNs is unavoidable. Applications such as military, medical care, structural monitoring, and surveillance systems require information security in the network. As current security mechanisms for WSNs are not sufficient, development of new security schemes for WSNs is necessary. New security schemes may be able to take advantage of the unique properties of WSNs, such as the large numbers of nodes typical in these networks to mitigate the need for cryptographic algorithms and key distribution and management. However, taking advantage of these properties must be done in an energy efficient manner. The research examines how the redundancy in WSNs can provide some security elements. The research shows how multiple random delivery paths (MRDPs) can provide data integrity for WSNs. Second, the research employs multiple sinks to increase the total number of duplicate packets received by sinks, allowing sink voting to mitigate the packet discard rate issue of a WSN with a single sink. Third, the research examines the effectiveness of using multiple random paths in maintaining data confidentiality in WSNs. Last, the research examines the use of a rate limit to cope with packet flooding attacks in WSNs