A Trust Evaluation Algorithm for Wireless Sensor Networks Based on Node Behaviors and D-S Evidence Theory

For wireless sensor networks (WSNs), many factors, such as mutual interference of wireless links, battlefield applications and nodes exposed to the environment without good physical protection, result in the sensor nodes being more vulnerable to be attacked and compromised. In order to address this network security problem, a novel trust evaluation algorithm defined as NBBTE (Node Behavioral Strategies Banding Belief Theory of the Trust Evaluation Algorithm) is proposed, which integrates the approach of nodes behavioral strategies and modified evidence theory. According to the behaviors of sensor nodes, a variety of trust factors and coefficients related to the network application are established to obtain direct and indirect trust values through calculating weighted average of trust factors. Meanwhile, the fuzzy set method is applied to form the basic input vector of evidence. On this basis, the evidence difference is calculated between the indirect and direct trust values, which link the revised D-S evidence combination rule to finally synthesize integrated trust value of nodes. The simulation results show that NBBTE can effectively identify malicious nodes and reflects the characteristic of trust value that ‘hard to acquire and easy to lose’. Furthermore, it is obvious that the proposed scheme has an outstanding advantage in terms of illustrating the real contribution of different nodes to trust evaluation

Trust model genetic node recovery based on cloud theory for underwater acoustic sensor network

Underwater Acoustic Sensor Networks [UASNs] are becoming a very growing research topic in the field of WSNs. UASNs are harmful by many attacks such as Jamming attacks at the physical layer, Collision attacks at the data link layer and Dos attacks at the network layer. UASNs has a unique characteristic such as unreliable communication, mobility, and computation of underwater sensor network. Because of this the traditional security mechanism, e.g. cryptographic, encryption, authorization and authentications are not suitable for UASNs. Many trust mechanisms of TWSNs [Terrestrial Wireless Sensor Networks] had proposed to UASNs and failed to provide security for UASNs environment, due to dynamic network structure and weak link connection between sensors. In this paper, a novel Trust Model Genetic Algorithm based on Cloud Theory [TMC] for UASNs has been proposed. The TMC-GA suggested a genetic node recovery algorithm to improve the TMC network in terms of better network lifetime, residual energy and total energy consumption. Also ensures that sensor nodes are participating in the rerouting in the routing discovery and performs well in terms of successful packet delivery. Simulation result provides that the proposed TMC-Genetic node recovery algorithm outperforms compared to other related works in terms of the number of hops, end-to-end delay, total energy consumption, residual energy, routing overhead, throughput and network lifetime

Quality of Information in Mobile Crowdsensing: Survey and Research Challenges

Smartphones have become the most pervasive devices in people's lives, and are clearly transforming the way we live and perceive technology. Today's smartphones benefit from almost ubiquitous Internet connectivity and come equipped with a plethora of inexpensive yet powerful embedded sensors, such as accelerometer, gyroscope, microphone, and camera. This unique combination has enabled revolutionary applications based on the mobile crowdsensing paradigm, such as real-time road traffic monitoring, air and noise pollution, crime control, and wildlife monitoring, just to name a few. Differently from prior sensing paradigms, humans are now the primary actors of the sensing process, since they become fundamental in retrieving reliable and up-to-date information about the event being monitored. As humans may behave unreliably or maliciously, assessing and guaranteeing Quality of Information (QoI) becomes more important than ever. In this paper, we provide a new framework for defining and enforcing the QoI in mobile crowdsensing, and analyze in depth the current state-of-the-art on the topic. We also outline novel research challenges, along with possible directions of future work.Comment: To appear in ACM Transactions on Sensor Networks (TOSN

Investigating Open Issues in Swarm Intelligence for Mitigating Security Threats in MANET

The area of Mobile Adhoc Network (MANET) has being a demanded topic of research for more than a decade because of its attractive communication features associated with various issues. This paper primarily discusses on the security issues, which has been still unsolved after abundant research work. The paper basically stresses on the potential features of Swarm Intelligence (SI) and its associated techniques to mitigate the security issues. Majority of the previous researches based on SI has used Ant Colony Optimization (ACO) or Particle Swarm Optimization (PSO) extensively. Elaborated discussion on SI with respect to trust management, authentication, and attack models are made with support of some of the recent studies done in same area. The paper finally concludes by discussing the open issues and problem identification of the review

Byzantine Attack and Defense in Cognitive Radio Networks: A Survey

The Byzantine attack in cooperative spectrum sensing (CSS), also known as the spectrum sensing data falsification (SSDF) attack in the literature, is one of the key adversaries to the success of cognitive radio networks (CRNs). In the past couple of years, the research on the Byzantine attack and defense strategies has gained worldwide increasing attention. In this paper, we provide a comprehensive survey and tutorial on the recent advances in the Byzantine attack and defense for CSS in CRNs. Specifically, we first briefly present the preliminaries of CSS for general readers, including signal detection techniques, hypothesis testing, and data fusion. Second, we analyze the spear and shield relation between Byzantine attack and defense from three aspects: the vulnerability of CSS to attack, the obstacles in CSS to defense, and the games between attack and defense. Then, we propose a taxonomy of the existing Byzantine attack behaviors and elaborate on the corresponding attack parameters, which determine where, who, how, and when to launch attacks. Next, from the perspectives of homogeneous or heterogeneous scenarios, we classify the existing defense algorithms, and provide an in-depth tutorial on the state-of-the-art Byzantine defense schemes, commonly known as robust or secure CSS in the literature. Furthermore, we highlight the unsolved research challenges and depict the future research directions.Comment: Accepted by IEEE Communications Surveys and Tutoiral