Biblio
Source location privacy (SLP) is becoming an important property for a large class of security-critical wireless sensor network applications such as monitoring and tracking. Much of the previous work on SLP have focused on the development of various protocols to enhance the level of SLP imparted to the network, under various attacker models and other conditions. Others works have focused on analysing the level of SLP being imparted by a specific protocol. In this paper, we focus on deconstructing routing-based SLP protocols to enable a better understanding of their structure. We argue that the SLP-aware routing protocols can be classified into two main categories, namely (i) spatial and (ii) temporal. Based on this, we show that there are three important components, namely (i) decoy selection, (ii) use and routing of control messages and (iii) use and routing of decoy messages. The decoy selection technique imparts the spatial or temporal property of SLP-aware routing. We show the viability of the framework through the construction of well-known SLP-aware routing protocols using the identified components.
The security of Wireless Sensor Networks (WSNs) is vital in several applications such as the tracking and monitoring of endangered species such as pandas in a national park or soldiers in a battlefield. This kind of applications requires the anonymity of the source, known as Source Location Privacy (SLP). The main aim is to prevent an adversary from tracing back a real event to the originator by analyzing the network traffic. Previous techniques have achieved high anonymity such as Dummy Uniform Distribution (DUD), Dummy Adaptive Distribution (DAD) and Controlled Dummy Adaptive Distribution (CAD). However, these techniques increase the overall overhead of the network. To overcome this shortcoming, a new technique is presented: Exponential Dummy Adaptive Distribution (EDAD). In this technique, an exponential distribution is used instead of the uniform distribution to reduce the overhead without sacrificing the anonymity of the source. The exponential distribution improves the lifetime of the network since it decreases the number of transmitted packets within the network. It is straightforward and easy to implement because it has only one parameter $łambda$ that controls the transmitting rate of the network nodes. The conducted adversary model is global, which has a full view of the network and is able to perform sophisticated attacks such as rate monitoring and time correlation. The simulation results show that the proposed technique provides less overhead and high anonymity with reasonable delay and delivery ratio. Three different analysis models are developed to confirm the validation of our technique. These models are visualization model, a neural network model, and a steganography model.
Sensor networks mainly deployed to monitor and report real events, and thus it is very difficult and expensive to achieve event source anonymity for it, as sensor networks are very limited in resources. Data obscurity i.e. the source anonymity problem implies that an unauthorized observer must be unable to detect the origin of events by analyzing the network traffic; this problem has emerged as an important topic in the security of wireless sensor networks. This work inspects the different approaches carried for attaining the source anonymity in wireless sensor network, with variety of techniques based on different adversarial assumptions. The approach meeting the best result in source anonymity is proposed for further improvement in the source location privacy. The paper suggests the implementation of most prominent and effective LSB Steganography technique for the improvement.