Secure Message Dissemination with QoS Guaranteed Routing in Internet of Vehicles

Internet of Vehicles (IoV) is a variant of vehicular adhoc network (VANET) where vehicles can communicate with other vehicles, infrastructure devices, parking lots and even pedestrians.  Communication to other entities is facilitates through various services like DSRC, C2C-CC. Fake messages can be propagated by attackers for various selfish needs. Complex authentication procedures can affect the propagation of emergency messages. Thus a light weight mechanism to ensure the trust of messages without affecting the delivery deadlines for emergency messages. Addressing this problem, this work proposes a clustering based network topology for IoV where routing is optimized for message dissemination of various classes using hybrid meta-heuristics.  In addition, two stage message authentication technique combining collaborative authentication with Bayesian filtering is proposed to verify the authenticity of message. Through simulation analysis, the proposed solution is found to detect fake messages with an accuracy of 96% with 10% lower processing delay compared to existing works

MARINE: Man-in-the-middle attack resistant trust model IN connEcted vehicles

Vehicular Ad-hoc NETwork (VANET), a novel technology holds a paramount importance within the transportation domain due to its abilities to increase traffic efficiency and safety. Connected vehicles propagate sensitive information which must be shared with the neighbors in a secure environment. However, VANET may also include dishonest nodes such as Man-in-the-Middle (MiTM) attackers aiming to distribute and share malicious content with the vehicles, thus polluting the network with compromised information. In this regard, establishing trust among connected vehicles can increase security as every participating vehicle will generate and propagate authentic, accurate and trusted content within the network. In this paper, we propose a novel trust model, namely, Man-in-the-middle Attack Resistance trust model IN connEcted vehicles (MARINE), which identifies dishonest nodes performing MiTM attacks in an efficient way as well as revokes their credentials. Every node running MARINE system first establishes trust for the sender by performing multi-dimensional plausibility checks. Once the receiver verifies the trustworthiness of the sender, the received data is then evaluated both directly and indirectly. Extensive simulations are carried out to evaluate the performance and accuracy of MARINE rigorously across three MiTM attacker models and the bench-marked trust model. Simulation results show that for a network containing 35% MiTM attackers, MARINE outperforms the state of the art trust model by 15%, 18%, and 17% improvements in precision, recall and F-score, respectively.N/A

Biometric Based Intrusion Detection System using Dempster-Shafer Theory for Mobile Ad hoc Network Security

In wireless mobile ad hoc network, mainly, two approaches are followed to protect the security such as prevention-based approaches and detection-based approaches. A Mobile Ad hoc Network (MANET) is a collection of autonomous wireless mobile nodes forming temporary network to interchange data (data packets) without using any fixed topology or centralized administration. In this dynamic network, each node changes its geographical position and acts as a router for forwarding packets to the other node. Current MANETs are basically vulnerable to different types of attacks. The multimodal biometric technology gives possible resolves for continuous user authentication and vulnerability in high security mobile ad hoc networks (MANETs). Dempster’s rule for combination gives a numerical method for combining multiple pieces of data from unreliable observers. This paper studies biometric authentication and intrusion detection system with data fusion using Dempster–Shafer theory in such MANETs. Multimodal biometric technologies are arrayed to work with intrusion detection to improve the limitations of unimodal biometric technique

A STABLE CLUSTERING SCHEME WITH NODE PREDICTION IN MANET

The main concern in MANET is increasing network lifetime and security. Clustering is one of the approaches that help in maintaining network stability. Electing an efficient and reliable Cluster Head (CH) is a challenging task. Many approaches are proposed for efficient clustering, weight-based clustering is one among them. This paper proposes a stable clustering scheme which provides network stability and energy efficiency. Proposed Stable Clustering Algorithm with Node Prediction (SCA-NP) computes the weight of the node using a combination of node metrics. Among these metrics, Direct Trust (DT) of the node provides a secure choice of CH and Node Prediction metric based on the minimum estimated time that node stay in the cluster provides the stable clustering. Mobility prediction is considered as the probability that a node stays in the network. This metric helps in electing CH which is available in the network for a longer time. Simulation is done in NS3 to evaluate the performance of SCA-NP in terms of clusters formed, network lifetime, efficiency in packet delivery, detecting malicious nodes and avoiding them in communication

Enhanced cluster based trust management framework for mobile Ad hoc networks

Trust management in decentralized networks and MANETs are much more complicated than the traditional access point based on wireless networks. The nodes in MANETs are used to provide trust information or evidence to find trustworthy nodes. However, the trust evaluation procedure depends on the local information due to its limited resources. In a trust management framework, there are issues to be resolved that include inefficient monitoring system with trust, inaccuracy in trust computation assign and lack of path selection based on trust. Therefore, in this research, a Trust Management Framework (TMF) was developed to address the aforementioned issues. The framework has the capability to monitor the network, assign trust values, and select an appropriate path for the transmission of packets among nodes which depends on the assignment of trust values. The TMF provides a secure cluster-based trust management to monitor the network that minimizes network overhead, improves path selection based on trust evaluation, and assigns trust for clusters-nodes with improved packet delivery ratio and delay. The performance of the TMF was assessed by performing simulation with Network Simulator version 2 (NS2). The results of the framework were compared with the state-of-the-art frameworks such as Requirement for Neural TMF (RNTMF), Recommendation Trust Framework with Defence Framework (RTMD), and Energy Efficient Secure Dynamic Source Routing (EESDSR). The results demonstrated that the Packets Delivery Ratio (PDR) of the TMF was 25.2% better than RNTMF, 21.4% better than RTMD, and 18.4% better than EESDSR. The overhead of the TMF was 4.5% less than RNTMF, 23.2% less than RTMD, and 26.8% less than EESDSR. The findings showed that TMF has better performance in terms of trust management in MANETs

Context Aware Computing for The Internet of Things: A Survey

As we are moving towards the Internet of Things (IoT), the number of sensors deployed around the world is growing at a rapid pace. Market research has shown a significant growth of sensor deployments over the past decade and has predicted a significant increment of the growth rate in the future. These sensors continuously generate enormous amounts of data. However, in order to add value to raw sensor data we need to understand it. Collection, modelling, reasoning, and distribution of context in relation to sensor data plays critical role in this challenge. Context-aware computing has proven to be successful in understanding sensor data. In this paper, we survey context awareness from an IoT perspective. We present the necessary background by introducing the IoT paradigm and context-aware fundamentals at the beginning. Then we provide an in-depth analysis of context life cycle. We evaluate a subset of projects (50) which represent the majority of research and commercial solutions proposed in the field of context-aware computing conducted over the last decade (2001-2011) based on our own taxonomy. Finally, based on our evaluation, we highlight the lessons to be learnt from the past and some possible directions for future research. The survey addresses a broad range of techniques, methods, models, functionalities, systems, applications, and middleware solutions related to context awareness and IoT. Our goal is not only to analyse, compare and consolidate past research work but also to appreciate their findings and discuss their applicability towards the IoT.Comment: IEEE Communications Surveys & Tutorials Journal, 201

SECURITY, PRIVACY AND APPLICATIONS IN VEHICULAR AD HOC NETWORKS

With wireless vehicular communications, Vehicular Ad Hoc Networks (VANETs) enable numerous applications to enhance traffic safety, traffic efficiency, and driving experience. However, VANETs also impose severe security and privacy challenges which need to be thoroughly investigated. In this dissertation, we enhance the security, privacy, and applications of VANETs, by 1) designing application-driven security and privacy solutions for VANETs, and 2) designing appealing VANET applications with proper security and privacy assurance. First, the security and privacy challenges of VANETs with most application significance are identified and thoroughly investigated. With both theoretical novelty and realistic considerations, these security and privacy schemes are especially appealing to VANETs. Specifically, multi-hop communications in VANETs suffer from packet dropping, packet tampering, and communication failures which have not been satisfyingly tackled in literature. Thus, a lightweight reliable and faithful data packet relaying framework (LEAPER) is proposed to ensure reliable and trustworthy multi-hop communications by enhancing the cooperation of neighboring nodes. Message verification, including both content and signature verification, generally is computation-extensive and incurs severe scalability issues to each node. The resource-aware message verification (RAMV) scheme is proposed to ensure resource-aware, secure, and application-friendly message verification in VANETs. On the other hand, to make VANETs acceptable to the privacy-sensitive users, the identity and location privacy of each node should be properly protected. To this end, a joint privacy and reputation assurance (JPRA) scheme is proposed to synergistically support privacy protection and reputation management by reconciling their inherent conflicting requirements. Besides, the privacy implications of short-time certificates are thoroughly investigated in a short-time certificates-based privacy protection (STCP2) scheme, to make privacy protection in VANETs feasible with short-time certificates. Secondly, three novel solutions, namely VANET-based ambient ad dissemination (VAAD), general-purpose automatic survey (GPAS), and VehicleView, are proposed to support the appealing value-added applications based on VANETs. These solutions all follow practical application models, and an incentive-centered architecture is proposed for each solution to balance the conflicting requirements of the involved entities. Besides, the critical security and privacy challenges of these applications are investigated and addressed with novel solutions. Thus, with proper security and privacy assurance, these solutions show great application significance and economic potentials to VANETs. Thus, by enhancing the security, privacy, and applications of VANETs, this dissertation fills the gap between the existing theoretic research and the realistic implementation of VANETs, facilitating the realistic deployment of VANETs

Intelligent detection of black hole attacks for secure communication in autonomous and connected vehicles

Detection of Black Hole attacks is one of the most challenging and critical routing security issues in vehicular ad hoc networks (VANETs) and autonomous and connected vehicles (ACVs). Malicious vehicles or nodes may exist in the cyber-physical path on which the data and control packets have to be routed converting a secure and reliable route into a compromised one. However, instead of passing packets to a neighbouring node, malicious nodes bypass them and drop any data packets that could contain emergency alarms. We introduce an intelligent black hole attack detection scheme (IDBA) tailored to ACV. We consider four key parameters in the design of the scheme, namely, Hop Count, Destination Sequence Number, Packet Delivery Ratio (PDR), and End-to-End delay (E2E). We tested the performance of our IDBA against AODV with Black Hole (BAODV), Intrusion Detection System (IdsAODV), and EAODV algorithms. Extensive simulation results show that our IDBA outperforms existing approaches in terms of PDR, E2E, Routing Overhead, Packet Loss Rate, and Throughput

A trust framework for peer-to-peer interaction in ad hoc networks

PhDAs a wider public is increasingly adopting mobile devices with diverse applications, the idea of who to trust while on the move becomes a crucial one. The need to find dependable partners to interact is further exacerbated in situations where one finds oneself out of the range of backbone structures such as wireless base stations or cellular networks. One solution is to generate self-started networks, a variant of which is the ad hoc network that promotes peer-to-peer networking. The work in this thesis is aimed at defining a framework for such an ad hoc network that provides ways for participants to distinguish and collaborate with their most trustworthy neighbours. In this framework, entities create the ability to generate trust information by directly observing the behaviour of their peers. Such trust information is also shared in order to assist those entities in situations where prior interactions with their target peers may not have existed. The key novelty points of the framework focus on aggregating the trust evaluation process around the most trustworthy nodes thereby creating a hierarchy of nodes that are distinguished by the class, defined by cluster heads, to which they belong. Furthermore, the impact of such a framework in generating additional overheads for the network is minimised through the use of clusters. By design, the framework also houses a rule-based mechanism to thwart misbehaving behaviour or non-cooperation. Key performance indicators are also defined within this work that allow a framework to be quickly analysed through snapshot data, a concept analogous to those used within financial circles when assessing companies. This is also a novel point that may provide the basis for directly comparing models with different underlying technologies. The end result is a trust framework that fully meets the basic requirements for a sustainable model of trust that can be developed onto an ad hoc network and that provides enhancements in efficiency (using clustering) and trust performance