Formal verification of secure ad-hoc network routing protocols using deductive model-checking

Ad-hoc networks do not rely on a pre-installed infrastructure, but they are formed by end-user devices in a self-organized manner. A consequence of this principle is that end-user devices must also perform routing functions. However, end-user devices can easily be compromised, and they may not follow the routing protocol faithfully. Such compromised and misbehaving nodes can disrupt routing, and hence, disable the operation of the network. In order to cope with this problem, several secured routing protocols have been proposed for ad-hoc networks. However, many of them have design flaws that still make them vulnerable to attacks mounted by compromised nodes. In this paper, we propose a formal verification method for secure ad-hoc network routing protocols that helps increasing the confidence in a protocol by providing an analysis framework that is more systematic, and hence, less error-prone than the informal analysis. Our approach is based on a new process calculus that we specifically developed for secure ad-hoc network routing protocols and a deductive proof technique. The novelty of this approach is that contrary to prior attempts to formal verification of secure ad-hoc network routing protocols, our verification method can be made fully automated

Formal verication of secure ad-hoc network routing protocols using deductive model-checking

Ad-hoc networks do not rely on a pre-installed infrastructure, but they are formed by end-user devices in a self-organized manner. A consequence of this principle is that end-user devices must also perform routing functions. However, end-user devices can easily be compromised, and they may not follow the routing protocol faithfully. Such compromised and misbehaving nodes can disrupt routing, and hence, disable the operation of the network. In order to cope with this problem, several secured routing protocols have been proposed for ad-hoc networks. However, many of them have design aws that still make them vulnerable to attacks mounted by compromised nodes. In this paper, we propose a formal verication method for secure ad-hoc network routing protocols that helps increasing the condence in a protocol by providing an analysis framework that is more systematic, and hence, less error-prone than the informal analysis. Our approach is based on a new process algebra that we specically developed for secure ad-hoc network routing protocols and a deductive proof technique. The novelty of this approach is that contrary to prior attempts to formal verication of secure ad-hoc network routing protocols, our verication method can be made fully automated, and provides expressiveness for explicitly modelling cryptography privitive

X-Vine: Secure and Pseudonymous Routing Using Social Networks

Distributed hash tables suffer from several security and privacy vulnerabilities, including the problem of Sybil attacks. Existing social network-based solutions to mitigate the Sybil attacks in DHT routing have a high state requirement and do not provide an adequate level of privacy. For instance, such techniques require a user to reveal their social network contacts. We design X-Vine, a protection mechanism for distributed hash tables that operates entirely by communicating over social network links. As with traditional peer-to-peer systems, X-Vine provides robustness, scalability, and a platform for innovation. The use of social network links for communication helps protect participant privacy and adds a new dimension of trust absent from previous designs. X-Vine is resilient to denial of service via Sybil attacks, and in fact is the first Sybil defense that requires only a logarithmic amount of state per node, making it suitable for large-scale and dynamic settings. X-Vine also helps protect the privacy of users social network contacts and keeps their IP addresses hidden from those outside of their social circle, providing a basis for pseudonymous communication. We first evaluate our design with analysis and simulations, using several real world large-scale social networking topologies. We show that the constraints of X-Vine allow the insertion of only a logarithmic number of Sybil identities per attack edge; we show this mitigates the impact of malicious attacks while not affecting the performance of honest nodes. Moreover, our algorithms are efficient, maintain low stretch, and avoid hot spots in the network. We validate our design with a PlanetLab implementation and a Facebook plugin.Comment: 15 page

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

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