Biblio
With the advances in the areas of mobile computing and wireless communications, V2X systems have become a promising technology enabling deployment of applications providing road safety, traffic efficiency and infotainment. Due to their increasing popularity, V2X networks have become a major target for attackers, making them vulnerable to security threats and network conditions, and thus affecting the safety of passengers, vehicles and roads. Existing research in V2X does not effectively address the safety, security and performance limitation threats to connected vehicles, as a result of considering these aspects separately instead of jointly. In this work, we focus on the analysis of the tradeoffs between safety, security and performance of V2X systems and propose a dynamic adaptability approach considering all three aspects jointly based on application needs and context to achieve maximum safety on the roads using an Internet of vehicles. Experiments with a simple V2V highway scenario demonstrate that an adaptive safety/security approach is essential and V2X systems have great potential for providing low reaction times.
Crowd management in urban settings has mostly relied on either classical, non-automated mechanisms or spontaneous notifications/alerts through social networks. Such management techniques are heavily marred by lack of comprehensive control, especially in terms of averting risks in a manner that ensures crowd safety and enables prompt emergency response. In this paper, we propose a Markov Decision Process Scheme MDP to realize a smart infrastructure that is directly aimed at crowd management. A key emphasis of the scheme is a robust and reliable scalability that provides sufficient flexibility to manage a mixed crowd (i.e., pedestrian, cyclers, manned vehicles and unmanned vehicles). The infrastructure also spans various population settings (e.g., roads, buildings, game arenas, etc.). To realize a reliable and scalable crowd management scheme, the classical MDP is decomposed into Local MDPs with smaller action-state spaces. Preliminarily results show that the MDP decomposition can reduce the system global cost and facilitate fast convergence to local near-optimal solution for each L-MDP.
Security issues in vehicular communication have become a huge concern to safeguard increasing applications. A group signature is one of the popular authentication approaches for VANETs (Vehicular ad hoc networks) which can be implemented to secure the vehicular communication. However, securely distributing group keys to fast-moving vehicular nodes is still a challenging problem. In this paper, we propose an efficient key management protocol for group signature based authentication, where a group is extended to a domain with multiple road side units. Our scheme not only provides a secure way to deliver group keys to vehicular nodes, but also ensures security features. The experiment results show that our key distribution scheme is a scalable, efficient and secure solution to vehicular networking.
Building the Internet of Things requires deploying a huge number of objects with full or limited connectivity to the Internet. Given that these objects are exposed to attackers and generally not secured-by-design, it is essential to be able to update them, to patch their vulnerabilities and to prevent hackers from enrolling them into botnets. Ideally, the update infrastructure should implement the CIA triad properties, i.e., confidentiality, integrity and availability. In this work, we investigate how the use of a blockchain infrastructure can meet these requirements, with a focus on availability. In addition, we propose a peer-to-peer mechanism, to spread updates between objects that have limited access to the Internet. Finally, we give an overview of our ongoing prototype implementation.
Vehicular ad-hoc networks (VANETs) provides infrastructure less, rapidly deployable, self-configurable network connectivity. The network is the collection vehicles interlinked by wireless links and willing to store and forward data for their peers. As vehicles move freely and organize themselves arbitrarily, message routing is done dynamically based on network connectivity. Compared with other ad-hoc networks, VANETs are particularly challenging due to the part of the vehicles' high rate of mobility and the numerous signal-weakening barrier, such as buildings, in their environments. Due to their enormous potential, VANET have gained an increasing attention in both industry and academia. Research activities range from lower layer protocol design to applications and implementation issues. A secure VANET system, while exchanging information should protect the system against unauthorized message injection, message alteration, eavesdropping. The security of VANET is one of the most critical issues because their information transmission is propagated in open access (wireless) environments. A few years back VANET has received increased attention as the potential technology to enhance active and preventive safety on the road, as well as travel comfort Safekeeping and privacy are mandatory in vehicular communications for a grateful acceptance and use of such technology. This paper is an attempt to highlight the problems occurred in Vehicular Ad hoc Networks and security issues.
Road In this paper, we focus on both the road vehicle and pedestrians detection, namely obstacle detection. At the same time, a new obstacle detection and classification technique in dynamical background is proposed. Obstacle detection is based on inverse perspective mapping and homography. Obstacle classification is based on fuzzy neural network. The estimation of the vanishing point relies on feature extraction strategy, which segments the lane markings of the images by combining a histogram-based segmentation with temporal filtering. Then, the vanishing point of each image is stabilized by means of a temporal filtering along the estimates of previous images. The IPM image is computed based on the stabilized vanishing point. The method exploits the geometrical relations between the elements in the scene so that obstacle can be detected. The estimated homography of the road plane between successive images is used for image alignment. A new fuzzy decision fusion method with fuzzy attribution for obstacle detection and classification application is described. The fuzzy decision function modifies parameters with auto-adapted algorithm to get better classification probability. It is shown that the method can achieve better classification result.
Aside from massive advantages in safety and convenience on the road, Vehicular Ad Hoc Networks (VANETs) introduce security risks to the users. Proposals of new security concepts to counter these risks are challenging to verify because of missing real world implementations of VANETs. To fill this gap, we introduce VANETsim, an event-driven simulation platform, specifically designed to investigate application-level privacy and security implications in vehicular communications. VANETsim focuses on realistic vehicular movement on real road networks and communication between the moving nodes. A powerful graphical user interface and an experimentation environment supports the user when setting up or carrying out experiments.
Outsourcing spatial databases to the cloud provides an economical and flexible way for data owners to deliver spatial data to users of location-based services. However, in the database outsourcing paradigm, the third-party service provider is not always trustworthy, therefore, ensuring spatial query integrity is critical. In this paper, we propose an efficient road network k-nearest-neighbor query verification technique which utilizes the network Voronoi diagram and neighbors to prove the integrity of query results. Unlike previous work that verifies k-nearest-neighbor results in the Euclidean space, our approach needs to verify both the distances and the shortest paths from the query point to its kNN results on the road network. We evaluate our approach on real-world road networks together with both real and synthetic points of interest datasets. Our experiments run on Google Android mobile devices which communicate with the service provider through wireless connections. The experiment results show that our approach leads to compact verification objects (VO) and the verification algorithm on mobile devices is efficient, especially for queries with low selectivity.
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