Rasheed Hussain

Rethinking Vehicular Communications: Merging VANET with cloud computing

Despite the surge in Vehicular Ad Hoc NETwork (VANET) research, future high-end vehicles are expected to under-utilize the on-board computation, communication, and storage resources. Olariu et al. envisioned the next paradigm shift from conventional VANET to Vehicular Cloud Computing (VCC) by merging VANET with cloud computing. But to date, in the literature, there is no solid architecture for cloud computing from VANET standpoint. In this paper, we put forth the taxonomy of VANET based cloud computing. It is, to the best of our knowledge, the first effort to define VANET Cloud architecture. Additionally we divide VANET clouds into three architectural frameworks named Vehicular Clouds (VC), Vehicles using Clouds (VuC), and Hybrid Vehicular Clouds (HVC). We also outline the unique security and privacy issues and research challenges in VANET clouds.

Cooperation-Aware VANET Clouds: Providing Secure Cloud Services to Vehicular Ad Hoc Networks

Abstract —Over the last couple of years, traditional VANET (Vehicular Ad Hoc NETwork) evolved into VANET-based clouds. From the VANET standpoint, applications became richer by virtue of the boom in automotive telematics and infotainment technologies. Nevertheless, the research community and industries are concerned about the under-utilization of rich computation, communication, and storage resources in middle and high-end vehicles. This phenomenon became the driving force for the birth of VANET-based clouds. In this paper, we envision a novel application layer of VANET-based clouds based on the cooperation of the moving cars on the road, called CaaS (Cooperation as a Service). CaaS is divided into TIaaS (Traffic Information as a Service), WaaS (Warning as a Service), and IfaaS (Infotainment as a Service). Note, however, that this work focuses only on TIaaS and WaaS. TIaaS provides vehicular nodes, more precisely subscribers, with the fine-grained traffic information constructed by CDM (Cloud Decision Module) as a result of the cooperation of the vehicles on the roads in the form of mobility vectors. On the other hand, WaaS provides subscribers with potential warning messages in case of hazard situations on the road. Communication between the cloud infrastructure and the vehicles is done through GTs (Gateway Terminals), whereas GTs are physically realized through RSUs (Road-Side Units) and vehicles with 4G Internet access. These GTs forward the coarse-grained cooperation from vehicles to cloud and fine-grained traffic information and warnings from cloud to vehicles (subscribers) in a secure, privacy-aware fashion. In our proposed scheme, privacy is conditionally preserved wherein the location and the identity of the cooperators are preserved by leveraging the modified location-based encryption and, in case of any dispute, the node is subject to revocation. To the best of our knowledge, our proposed scheme is the first effort to offshore the extended traffic view construction function and warning messages dissemination function to the cloud.

Towards Privacy Aware Pseudonymless Strategy for Avoiding Profile Generation in VANET

Inspiring from MANET (Mobile Ad hoc NETworks), VANET (Vehicular Ad hoc NETworks) employing vehicles as nodes, provide a wide range of applications in transportation system. The security of VANET has been a hot topic among the research community. VANETs must meet the basic security requirements such as authentication, integrity, confidentiality and privacy. In VANET, vehicles send beacon messages periodically every 100-300ms which carry speed and position information used for safe driving. The privacy of user is abused by profile generation where the adversary makes movement profiles against the vehicle using the identity information in the beacon. We outline the strategies using pseudonyms to provide privacy of user. After finding out deficiencies in pseudonym-based schemes, we propose a pseudonymless strategy to avoid profilation. In our scheme, we assume that each car is equipped with TRH (Tamper-Resistant Hardware) carrying out secure operations. Our proposed scheme assures the avoidance of profile generation without using mix zones and silent periods. We show that our proposed scheme is computationally efficient and less bandwidth consuming than other systems.

TIaaS: Secure Cloud-assisted Traffic Information Dissemination in Vehicular Ad Hoc Networks

In the recent past, a new concept termed as VANET-based clouds evolved from traditional VANET incorporating both VANET and cloud computing technologies in order to provide vehicle drivers, passengers, and consumers with safe, reliable, and infotainment-rich services while driving on the roads. In this paper, we use a framework of VANET-based clouds proposed by Hussain et al. namely VuC (VANET using Clouds) and define another layer TIaaS (Traffic Information as a Service) atop the cloud computing stack. TIaaS layer provides vehicular nodes (more precisely subscribers) with fine-grained traffic information in a secure way. Additionally our proposed scheme provides security, privacy, and conditional anonymity which are of prime concern in VANET clouds.

Vehicle Witnesses as a Service: Leveraging Vehicles as Witnesses on the Road in VANET Clouds

Inspired by the dramatic evolution of VANE clouds, this paper proposes a new VANET-cloud service called VWaaS (Vehicle Witnesses as a Service) in which vehicles moving on the road serve as anonymous witnesses of designated events such as a terrorist attack or a deadly accident. When confronted the events, a group of vehicles with mounted cameras collaborate with roadside stationary cameras to take pictures of the site of interest (SoI) around them, and send the pictures to the cloud infrastructure anonymously. The pictures are sent to the cloud in a way that the privacy of the senders can be protected, and kept by the cloud for future investigation. However, for the case that the pictures are used as an evidence of court trial, we made the privacy protection to be conditional and thus can be revoked by authorized entity(s) if necessary.

Using public buses as mobile gateways in vehicular clouds

Recently Vehicular Ad Hoc NETwork (VANET) evolved to a rather more application and services-rich infrastructure referred to as VANET-based clouds. However the initial deployment stage of VANET is going to be crucial due to lack of proper infrastructure. In this paper, based on the predictability of time and space of the public buses in urban scenario, we use these buses as mobile gateways among vehicles on the road, VANET authorities, and cloud infrastructure. We consider data aggregation as a use-case for our proposed scheme where buses collect beacons and service requests from vehicles and send it to cloud, whereas cloud provides services to vehicles through buses. Additionally a real-time road network is considered in Seoul, South Korea where the public buses provide perfect connectivity among other vehicles.

Privacy-Aware VANET Security: Putting Data-Centric Misbehavior and Sybil Attack Detection Schemes into Practice

The past decade has witnessed a growing interest in VANET (Vehicular Ad Hoc NETwork) and its myriad potential applications. Nevertheless, despite the surge in VANET research, security and privacy issues have been the root cause of impeded momentum in VANET deployment. In this paper we focus on misbehavior and Sybil attacks from VANET standpoint. With intrusion capabilities in hand, malicious users in VANET can inject false information and launch Sybil attack. Sybil attack refers to pretending one physical node to be many and in worst case almost all kinds of attacks can be launched in the presence of Sybil attack. Misbehavior in VANET can be categorized as a sub-effect of Sybil attack where a malicious vehicular node(s) spoof legitimate identities. There are two main strategies for avoiding misbehavior in VANET; Entity-centric strategies that focus on the revocation of misbehaving nodes by revocation authorities. On the other hand, Data-centric approach mainly focuses on the soundness of information rather than the source of information. We cover both strategies where decision on which strategy to be used, is taken on the basis of traffic situation. In a dense traffic regime, we propose SADS (Sybil Attack Detection Scheme) whereas in sparse traffic regime, we propose LMDS (Location-Based Misbehavior Detection Scheme). Our proposed schemes leverage position verification of the immediate source of warning message. Furthermore, we guarantee security and privacy (conditional anonymity) for both beacons and warning messages.

On Secure and Privacy-Aware Sybil Attack Detection in Vehicular Communications

The foreseen dream of Vehicular Ad Hoc NETwork (VANET) deployment is obstructed by long-chased security and privacy nightmares. Despite of the increasing demand for perfect privacy, it conflicts with rather more serious security threat called ‘Sybil Attack’ which refers to, impersonation of one physical entity for many, namely Sybil nodes. In such circumstances, data received from malicious Sybil attacker may seem as if it was received from many distinct physical nodes. Sybil nodes may deliberately mislead other neighbors, resulting in catastrophic situations like traffic jams or even deadly accidents. Preventing such attacks in a privacy-enabled environment is not a trivial task. In this paper, we aim at two conflicting goals, i.e. privacy and Sybil attack in VANET. We leverage pseudonymless beaconing in order to preserve privacy. To cope with Sybil attack, we put forth a twofold strategy. In order to avoid Sybil attack through scheduled beacons, we employ tamper resistant module (TRM) to carry out a pre-assembly data analysis on data that is used to assemble beacons whereas for event reporting message (ERM), we employ road side units (RSUs) to localize Sybil nodes in VANET and report them to the revocation authority(s). RSUs distribute authorized tokens among the benign vehicular nodes which in turn are consumed to report ERMs. RSUs collect ERMs for certain event and figures out if more than one ERM for the same event includes identical token or, if an ERM is sent more than once by the same source. Our proposed scheme preserves privacy in both beacons and ERMs, and provides conditional anonymity where in case of a dispute; malicious attackers are subject to revocation. We also show that our proposed scheme outperforms the previously proposed scheme from security and computational complexity standpoint.

Privacy-aware route tracing and revocation games in VANET-based clouds

The foreseen dream of reliable, safe, and comfortable driving experience is yet to become reality since automobile industries are testing their waters for VANET (Vehicular Ad Hoc NETwork) deployment. But nevertheless, security and privacy issues have been the root cause of hindrance in VANET deployment. Recently, VANET evolved to VANET-based clouds as a result of resources-rich high-end cars. Soon after, Hussain et al. defined different architectural frameworks for VANET-based clouds. In this paper, we aim at a specific framework namely VuC (VANET using Clouds) where VANET and CC (Cloud Computing) cooperate with each other in order to provide VANET users (more precisely subscribers) with services. We propose a lightweight privacy-aware revocation and route tracing mechanism for VuC. Beacons broadcasted by vehicles are stored in cloud infrastructure as cooperation from VANET and after processing, cloud provides VANET subscribers with services. Revocation authorities can revoke and trace the path taken by the target node for a specified timespan by exploiting the beacons stored in the cloud. Our proposed scheme is secure, preserves conditional privacy, and is computationally less expensive than the previously proposed schemes.

Privacy Preserving Cloud-Based Computing Platform (PPCCP) for Using Location Based Services

Mobile cloud computing (MCC) is an emerging trend which combines the benefits of cloud computing with the mobile devices. This new technology not only offers tremendous computing power and storage to the mobile devices with limited processing and storage capabilities but also increases the affordability and reliability. Despite providing various benefits, MCC is still in its early stages in providing trust guarantees to a user. Location-Based Services (LBS), on the other hand, are those services which operate on a users location to provide him/her services such as finding nearby restaurants, hospitals, bus terminal and ATMs, to name a few. While a users location is mandatory for LBS to work, it imposes serious threats to the users privacy. In this paper we propose a privacy preserving cloud-based computing architecture for using location-based services. On one hand, our architecture provides a secure mechanism for using LBS services anonymously while on the other hand it utilizes untrusted but fast and reliable cloud services for its implementation in an efficient and effective manner. Moreover, we provide various attack scenarios and show that how our architecture preserves the privacy of the user and is difficult to compromise.