Improving the Resilience of Wireless Sensor Networks Against Security Threats: A Survey and Open Research Issues

Wireless Sensor Network (WSN) technology has gained importance in recent years due to its various benefits, practicability and extensive utilization in diverse applications. The innovation helps to make real-time automation, monitoring, detecting and tracking much easier and more effective than previous technologies. However, as well as their benefits and enormous potential, WSNs are vulnerable to cyber-attacks. This paper is a systematic literature review of the security-related threats and vulnerabilities in WSNs. We review the safety of and threats to each WSN communication layer and then highlight the importance of trust and reputation, and the features related to these, to address the safety vulnerabilities. Finally, we highlight the open research areas which need to be addressed in WSNs to increase their flexibility against security threats

Communication and Content Trust Aware Routing For Clustered IoT Network

Security has become a major concern in practical applications related to Internet of Things, a Trust Aware Routing is found as second line of defence. To ensure a secure and hassle-free communication in IoT, this paper proposes a new routing strategy called as Communication and Content Trust Aware Routing (CCTAR) for Clustered IoT network. CCTAR is applied on a clustered IoT network in which the entire nodes are clustered into different clusters. Distance, initial energy, transmission range, angle of overlap and the sensing range are the fur major metrics used to cluster the network into hierarchical clusters followed by Cluster Head Selection. Next, the Trust Aware routing computes three different trust metrics namely Nobility rust, bilateral trust and Data oriented trust to determine the trustworthiness of Cluster Heads. The experimental evaluation of the proposed mechanism shows its superiority in terms of malicious nodes identification, Storage overhead reduction and Network lifetime improvisation

BlockChain: A distributed solution to automotive security and privacy

Interconnected smart vehicles offer a range of sophisticated services that benefit the vehicle owners, transport authorities, car manufacturers and other service providers. This potentially exposes smart vehicles to a range of security and privacy threats such as location tracking or remote hijacking of the vehicle. In this article, we argue that BlockChain (BC), a disruptive technology that has found many applications from cryptocurrencies to smart contracts, is a potential solution to these challenges. We propose a BC-based architecture to protect the privacy of the users and to increase the security of the vehicular ecosystem. Wireless remote software updates and other emerging services such as dynamic vehicle insurance fees, are used to illustrate the efficacy of the proposed security architecture. We also qualitatively argue the resilience of the architecture against common security attacks

Distributed Fault Detection in Smart Spaces Based on Trust Management

AbstractApplication performance in a smart space is affected by faulty behaviours of nodes and communication networks. Detection of faults helps diagnosis of problems and maintenance can be done to restore performance, for example, by replacing or reconfiguring faulty parts. Fault detection methods in the literature are too complex for typical low-resource devices and they do not perform well in detecting intermittent faults. We propose a fully distributed fault detection method that relies on evaluating statements about trustworthiness of aggregated data from neighbors. Given one or more trust statements that describe a fault-free state, the trustor node determines for each observation coming from the trustee whether it is an outlier or not. Several fault types can be explored using different trust statements whose parameters are assessed differently. The trustor subsequently captures the observation history of the trustee node in only two evidence variables using evidence update rules that give more weight to recent observations. The proposed method detects not only permanent faults but also intermittent faults with high accuracy and low false alarm rate

Enhanced EQSR based QoS Mechanism for Wireless Sensor Networks

Wireless sensor networks are widely used in real-time applications. Due to the resource limited nature of sensor networks providing Quality of Service (QoS) is quiet interesting and challenging task for the researchers in recent years. The QoS based schemes require to cope up with the energy constrained smaller devices. Therefore, allowing QoS applications in sensor networks mandate it to implement in separate layers. In this work an enhanced version of Energy Efficient Quality of Service Routing (EQSR) is offered. The enhanced EQSR maximizes the task of the application in mixed delay sensitive and delay tolerant applications. The scheme balances the energy by distributing the traffic in a disperse manner that guaranties the delay sensitive packets to be forwarded on time within the tolerable delay. By conducting simulations with varying scenarios the performance of the protocol is evaluated and compared with the base EQSR. The simulation results have proven that the enhanced EQSR works better by lowering the energy and increasing the packet delivery ratio

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