Rajesh P. Barnwal

Heartbeat Message Based Misbehavior Detection Scheme for Vehicular Ad-hoc Networks

Safety applications in VANET mostly rely upon the correctness of position and other vehicle kinematics information contained in heartbeat messages. A false information or incorrect notification can create traffic inconvenience on the road and may results into the loss of property and human lives. An authenticated node, which disseminates false information intentionally/ unintentionally is termed as misbehaving node. Prior knowledge about this kind of misbehaving node might not be possible in ephemeral network like VANET. It is required to have some verification mechanism in place, which can ensure the reliability of the information content of heartbeat messages, at least in terms of reported position and other vehicle kinematics. A good amount of research has been reported for the authentication of the node in VANET, but misbehavior detection research in VANET is still in nascent stage. The paper proposes a heartbeat message based short-term misbehavior detection scheme, which is capable of identifying the source of false information with very high probability. The proposed scheme has been implemented and analysed in simulation environment with the help of ns-2 and VanetMobiSim. The results are found to be encouraging and pave the way for further research in this direction.

UCGNet: wireless sensor network-based active aquifer contamination monitoring and control system for underground coal gasification

SUMMARY Underground coal gasification (UCG) is a potentially effective methodology for mining underground coal. Further, there are various situations in which coal mining using conventional methods is formidable or costly, and, thus, UCG makes it feasible for recovering those coal resources from underground as alternative forms of energy. However, the environmental risk, particularly aquifer contamination, is a major bottleneck in adopting this technology by the industry. Concurrently, wireless sensor network (WSN) is a promising technology currently for use in various industrial process monitoring and control applications. The easy deployment, scalability, and low power consumption make WSN specially attractive. In this work, we propose a WSN-based aquifer contamination monitoring and controlling system for the UCG plant. Copyright

Enhancing Reliability of Vehicular Participatory Sensing Network: A Bayesian Approach

Participatory sensing (PS) is an emerging socio-technological paradigm in which citizens voluntarily participate and contribute to a distributed information system using applications installed in their hand-held devices. It can be found in a number of real-life applications, viz. traffic monitoring, air/sound pollution, garbage monitoring, social networking, commodity pricing, and so on. In these systems, information sensed by the user helps the peers in decision making. Present work considers vehicular participatory sensing systems, where registered user senses (perceives) the traffic incident and submits its report(s) to a PS application server. PS application server in turn, broadcasts those reports as alerts to its subscribers. To promote the participation, the PS systems used to have incentive schemes for the participants. However, a common problem in participatory sensing is the generation of false reports either due to wrong perception of an event or to maliciously increase the degree of participation to gain undue incentives. Such false reports make the usage of the PS system unreliable and vulnerable to the illusion attack. This work proposes a novel approach to make PS applications more reliable by identifying and filtering out the falsely reported event through automated confidence assignment based on a probabilistic model. Waze traffic alerts have been used as the dataset to validate the proposed filtering mechanism. Finally, simulation-based experiments and performance evaluation have been done to demonstrate that the proposed approach is relatively accurate.

KITE: an efficient scheme for trust estimation and detection of errant nodes in vehicular cyber-physical systems

Advancement in sensing and networking technology enhances the capability of mechatronic systems by many folds and improves the way it interacts with its physical environment. However, the dependency on network technology introduces a new set of challenges. Vehicular cyber-physical systemVCPS is one such example that came into existence with the objective of enhancing road safety and convenience. In VCPS, the safety applications rely on the correctness of the kinematics information received from other vehicles in the vicinity. Incorrect kinematics information may result in increase in road hazards and creates more confusion than convenience. Irrespective of the reasons, detection of such errant nodes in VCPS is imperative. Moreover, the trust estimation of the nodes can play an important role to classify them as genuine and errant. In this work, an efficient scheme is proposed for trust estimation and detection of those errant nodes that disseminate incorrect kinematics information in VCPS. Simulations using ns-2 and VanetMobiSim under realistic vehicular network environment are conducted to evaluate the performance of the proposed scheme. The results are encouraging and reveal that the proposed scheme is suitable for implementation in real vehicular environment for detection of such errant nodes with high accuracy. Copyright

CAT: Consensus-assisted trust estimation of MDS-equipped collaborators in vehicular ad-hoc network

The trust establishment in highly mobile ad-hoc network is a challenging task. Vehicular ad-hoc network (VANET) poses trust estimation problem in dynamic network environment. Presence of misbehavior detection schemes (MDS), in the vehicular node, safeguards them up to a certain extent from misbehaving vehicles but existing MDS algorithms have their own limitations in terms of capability and accuracy. In this scenario, vehicles are supposed to collaborate among themselves for getting better assessment of the misbehaving peers. However, the trustworthiness of collaborators is always a questionable factor subject to verification. Trust estimation of the collaborating nodes is essentially required to provide supplementary information for more accurate decision about the adversaries. In this paper, algorithms have been proposed to estimate trustworthiness of the MDS-equipped collaborating nodes with the help of consensus mechanism. After comparison of different proposed trust-estimation algorithms in simulated environment, results reveal that the unsupervised k-means based consensus clustering algorithm is an effective solution for precise estimation of the trustworthiness of the collaborating node.

MDS-Based Trust Estimation of Event Reporting Node in VANET

Vehicular Ad-hoc Network (VANET) is a promising technology with a great potential for providing enhanced safety and convenience to vehicles. Majority of applications in VANET involve exchange of information amongst vehicles. Adversaries may take this as an advantage to disturb the network by disseminating false information. To address this problem, there is a need to assess the real trustworthiness of the reporting vehicles. Even in presence of on-board misbehavior detection system (MDS), the reliability of the same is subject to various limitations. In this paper, a MDS-based trust estimation model has been proposed to estimate the trustworthiness of event-reporting vehicles. An efficient algorithm has been proposed for estimating the trust value of event reporting node(s) based on MDS-based feedback of the peers. The simulation based experimental results are found to be encouraging and effective in real-time trust estimation with better accuracy.

A probabilistic approach for filtering out spam reports in a vehicular participatory sensing system

Participatory sensing (PS) is an emerging socio-technological paradigm by which citizens voluntarily participate and contribute to a distributed information management system using applications installed in their hand-held devices. However, a common problem in participatory sensing is that some users generate spam (false) reports to increase their degree of participation to maliciously gain undue incentives. Such spam reports make the usage of the PS system unreliable and vulnerable to illusion attacks. This work proposes a novel approach to make PS applications authentic by identifying and filtering out spam reports through automated confidence assignment based on a probabilistic model. Waze traffic alerts have been used to validate the proposed report filtering mechanism. Results have been found to be satisfactory and useful in enhancing reliability of the PS system.

Data and Application Security in Cloud

Cloud computing is an emerging technological paradigm, which provides computing resources as utility. Like other day-to-day utilities, cloud computing follows pay-as-you-use model, where users are charged according to the usage without regard to where the services are hosted or how they are delivered. Today, majority of companies follow an IT infrastructure-driven business model. With the growing demand, rise in customer base and market place competitions, companies prefer focusing on respective business policies and services they offer, rather than IT management overheads. Therefore, there is a high probability that the future of present day business model may shift to clouds where non-IT companies no longer have to procure, manage, and maintain IT resources. They will host applications and data to the servers, which are deployed by cloud providers, possibly in geographically dispersed locations. However, security is a major challenge before outsourcing any IT needs of business. As cloud provides a multi-tenant virtual computing environment, where competitive businesses may co-exist, hosting of sensitive information for mission-critical applications is of utmost concern. This chapter reviews the recent works reported specifically in the area of data and application security relevant to cloud computing. Some works which use biologically inspired phenomenon to manage security and load balancing in cloud environment, have also been studied. The aim of this chapter is to provide an insight into the present state-of-the-art cloud security problems, proposed solutions, and identify future research directions as well as scopes in various security issues.