A Framework for Incident Detection and notification in Vehicular Ad-Hoc Networks

The US Department of Transportation (US-DOT) estimates that over half of all congestion events are caused by highway incidents rather than by rush-hour traffic in big cities. The US-DOT also notes that in a single year, congested highways due to traffic incidents cost over $75 billion in lost worker productivity and over 8.4 billion gallons of fuel. Further, the National Highway Traffic Safety Administration (NHTSA) indicates that congested roads are one of the leading causes of traffic accidents, and in 2005 an average of 119 persons died each day in motor vehicle accidents. Recently, Vehicular Ad-hoc Networks (VANET) employing a combination of Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) wireless communication have been proposed to alert drivers to traffic events including accidents, lane closures, slowdowns, and other traffic-safety issues. In this thesis, we propose a novel framework for incident detection and notification dissemination in VANETs. This framework consists of three main components: a system architecture, a traffic incident detection engine and a notification dissemination mechanism. The basic idea of our framework is to collect and aggregate traffic-related data from passing cars and to use the aggregated information to detect traffic anomalies. Finally, the suitably filtered aggregated information is disseminated to alert drivers about traffic delays and incidents. The first contribution of this thesis is an architecture for the notification of traffic incidents, NOTICE for short. In NOTICE, sensor belts are embedded in the road at regular intervals, every mile or so. Each belt consists of a collection of pressure sensors, a simple aggregation and fusion engine, and a few small transceivers. The pressure sensors in each belt allow every message to be associated with a physical vehicle passing over that belt. Thus, no one vehicle can pretend to be multiple vehicles and then, is no need for an ID to be assigned to vehicles. Vehicles in NOTICE are fitted with a tamper-resistant Event Data Recorder (EDR), very much like the well-known black-boxes onboard commercial aircraft. EDRs are responsible for storing vehicles behavior between belts such as acceleration, deceleration and lane changes. Importantly, drivers can provide input to the EDR, using a simple menu, either through a dashboard console or through verbal input. The second contribution of this thesis is to develop incident detection techniques that use the information provided by cars in detecting possible incidents and traffic anomalies using intelligent inference techniques. For this purpose, we developed deterministic and probabilistic techniques to detect both blocking incidents, accidents for examples, as well as non-blocking ones such as potholes. To the best of our knowledge, our probabilistic technique is the first VANET based automatic incident detection technique that is capable of detecting both blocking and non blocking incidents. Our third contribution is to provide an analysis for vehicular traffic proving that VANETs tend to be disconnected in many highway scenarios, consisting of a collection of disjoint clusters. We also provide an analytical way to compute the expected cluster size and we show that clusters are quite stable over time. To the best of our knowledge, we are the first in the VANET community to prove analytically that disconnection is the norm rather than the exceptions in VANETs. Our fourth contribution is to develop data dissemination techniques specifically adapted to VANETs. With VANETs disconnection in mind, we developed data dissemination approaches that efficiently propagate messages between cars and belts on the road. We proposed two data dissemination techniques, one for divided roads and another one for undivided roads. We also proposed a probabilistic technique used by belts to determine how far should an incident notification be sent to alert approaching drivers. Our fifth contribution is to propose a security technique to avoid possible attacks from malicious drivers as well as preserving driver\u27s privacy in data dissemination and notification delivery in NOTICE. We also proposed a belt clustering scheme to reduce the probability of having a black-hole in the message dissemination while reducing also the operational burden if a belt is compromised

SEE-TREND: SEcurE Traffic-Related EveNt Detection in Smart Communities

It has been widely recognized that one of the critical services provided by Smart Cities and Smart Communities is Smart Mobility. This paper lays the theoretical foundations of SEE-TREND, a system for Secure Early Traffic-Related EveNt Detection in Smart Cities and Smart Communities. SEE-TREND promotes Smart Mobility by implementing an anonymous, probabilistic collection of traffic-related data from passing vehicles. The collected data are then aggregated and used by its inference engine to build beliefs about the state of the traffic, to detect traffic trends, and to disseminate relevant traffic-related information along the roadway to help the driving public make informed decisions about their travel plans, thereby preventing congestion altogether or mitigating its nefarious effects

FRIEND: A Cyber-Physical System for Traffic Flow Related Information Aggregation and Dissemination

The major contribution of this thesis is to lay the theoretical foundations of FRIEND — A cyber-physical system for traffic Flow-Related Information aggrEgatioN and Dissemination. By integrating resources and capabilities at the nexus between the cyber and physical worlds, FRIEND will contribute to aggregating traffic flow data collected by the huge fleet of vehicles on our roads into a comprehensive, near real-time synopsis of traffic flow conditions. We anticipate providing drivers with a meaningful, color-coded, at-a-glance view of flow conditions ahead, alerting them to congested traffic. FRIEND can be used to provide accurate information about traffic flow and can be used to propagate this information. The workhorse of FRIEND is the ubiquitous lane delimiters (a.k.a. cat\u27s eyes) on our roadways that, at the moment, are used simply as dumb reflectors. Our main vision is that by endowing cat\u27s eyes with a modest power source, detection and communication capabilities they will play an important role in collecting, aggregating and disseminating traffic flow conditions to the driving public. We envision the cat\u27s eyes system to be supplemented by road-side units (RSU) deployed at regular intervals (e.g. every kilometer or so). The RSUs placed on opposite sides of the roadway constitute a logical unit and are connected by optical fiber under the median. Unlike inductive loop detectors, adjacent RSUs along the roadway are not connected with each other, thus avoiding the huge cost of optical fiber. Each RSU contains a GPS device (for time synchronization), an active Radio Frequency Identification (RFID) tag for communication with passing cars, a radio transceiver for RSU to RSU communication and a laptop-class computing device. The physical components of FRIEND collect traffic flow-related data from passing vehicles. The collected data is used by FRIEND\u27s inference engine to build beliefs about the state of the traffic, to detect traffic trends, and to disseminate relevant traffic flow-related information along the roadway. The second contribution of this thesis is the development of an incident classification and detection algorithm that can be used to classify different types of traffic incident Then, it can notify the necessary target of the incident. We also compare our incident detection technique with other VANET techniques. Our third contribution is a novel strategy for information dissemination on highways. First, we aim to prevent secondary accidents. Second, we notify drivers far away from the accident of an expected delay that gives them the option to continue or exit before reaching the incident location. A new mechanism tracks the source of the incident while notifying drivers away from the accident. The more time the incident stays, the further the information needs to be propagated. Furthermore, the denser the traffic, the faster it will backup. In high density highways, an incident may form a backup of vehicles faster than low density highways. In order to satisfy this point, we need to propagate information as a function of density and time

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

Towards Self-Protective Multi-Cloud Applications: MUSA – a Holistic Framework to Support the Security-Intelligent Lifecycle Management of Multi-Cloud Applications

The most challenging applications in heterogeneous cloud ecosystems are those that are able to maximise the benefits of the combination of the cloud resources in use: multi-cloud applications. They have to deal with the security of the individual components as well as with the overall application security including the communications and the data flow between the components. In this paper we present a novel approach currently in progress, the MUSA framework. The MUSA framework aims to support the security-intelligent lifecycle management of distributed applications over heterogeneous cloud resources. The framework includes security-by-design mechanisms to allow application self-protection at runtime, as well as methods and tools for the integrated security assurance in both the engineering and operation of multi-cloud applications. The MUSA framework leverages security-by-design, agile and DevOps approaches to enable the security-aware development and operation of multi-cloud applications.European Commission's H202

Beyond Technophobia: Lawyers’ Ethical and Legal Obligations to Monitor Evolving Technology and Security Risks

Lawyers and technology have an uneasy relationship. Although some lawyers are early adapters, others take pride in ignoring technology because they believe it is alien to the practice of law. As Jody R. Westby observed, lawyers confronted with technology and security issues tend to have their “eyes glaze over” and “want to call in their ‘IT guy’ and go back to work.” But this technophobic attitude may no longer just be harmless conservatism. In the world of growing security risks, ignorance of technology may lead to violations of lawyers’ fundamental ethical duties of competence and confidentiality