A secure trust-aware cross-layer routing protocol for Vehicular Ad hoc Networks

International audienceVANETs currently represent one of the most prominent solutions that aim to reduce the number of road accident victims and congestion problems while improving the quality of driving. VANETs form a very dynamic open network in which vehicles exchange information and warnings about road situations and other traffic information through several routing protocols, without any intermediate control. However, the absence of a central control makes such a network vulnerable to several types of attack, not only from the outside but also, and mostly, from the interior. This makes their detection by classical security techniques more difficult and requires the development of new techniques to control the information circulating in the network. In this context, a proposed routing protocol called TDMA-aware Routing Protocol for Multi hop communication in Vehicular networks, is vulnerable to security threats, such as Black Hole and Gray Hole attacks, as well as MAC attacks such as Denial of Service (DoS), which lead to a considerable deterioration in the network's performance in terms of packet delivery ratio, end-to-end delays, channel access rate, etc. To mitigate the effect of those attacks, we propose a trust-based model in which each node will establish a trust relationship with its neighbors based on their behaviors during the channel access and packet forwarding process. The simulation results show a significant decrease in the effect of attacks on the performance of the TRPM protocol

Performance Impact Analysis of Security Attacks on Cross-Layer Routing Protocols in Vehicular Ad hoc Networks

International audienceRecently, several cross-layer protocols have been designed for vehicular networks to optimize data dissemination by ensuring internal communications between routing and MAC layers. In this context, a cross-layer protocol, called TDMA-aware Routing Protocol for Multi-hop communications (TRPM), was proposed in order to efficiently select a relay node based on time slot scheduling information obtained from the MAC layer. However, due to the constant evolution of cyber-attacks on the routing and MAC layers, data dissemination in vehicular networks is vulnerable to several types of attack. In this paper, we identify the different attack models that can disrupt the cross-layer operation of the TRPM protocol and assess their impact on performance through simulation. Several new vulnerabilities related to the MAC slot scheduling process are identified. Exploiting of these vulnerabilities would lead to severe channel capacity wastage where up to half of the free slots could not be reserved

An Efficient Cross-Layer Design for Multi-hop Broadcast of Emergency Warning Messages in Vehicular Networks

International audienceThe main objective of Vehicular ad hoc networks (VANETs) is to make road transportation systems more intelligent in order to anticipate and avoid dangerous, potentially life-threatening situations. Due to its promising safety applications, this type of network has attracted a lot of attention in the research community. The dissemination of warning messages, such as DENMs (Decentralized Environmental Notification Messages), requirse an efficient and robust routing protocol. In previous studies, the active signaling mechanism has shown its ability to prevent collisions between users trying to allocate the same resource. In this paper, we propose an original message forwarding strategy based on the active signaling mechanism. Our proposal disseminates warning messages from a source vehicle to the rest of the network while minimizing the access delay and the number of relay nodes. For this purpose, a special time slot is dedicated to forwarding emergency warning messages. To avoid access collisions on this slot, the active signaling scheme we propose favours the selection of the furthest node as the forwarder. We carry out a number of simulations and comparisons to evaluate the performances of the scheme

MAC-aware Routing Protocols for Vehicular Ad Hoc Networks: A Survey

International audienceThe constantly growing number of vehicles on our roads has become an increasing major cause of serious injury and death. Efficient data dissemination in Vehicular Ad hoc Networks (VANETs) inevitably requires an efficient and robust routing protocol. In this context, several categories of routing protocols have been proposed in the literature to meet VANETs application requirements in terms of delay, packet loss and throughput. In this paper, we focus on cross layer routing protocols. We present a survey of state-of-the-art MAC aware routing protocols designed for VANETs. These solutions can broadly be divided into two categories: contention-free and contention-based MAC-aware routing. In this paper we carryout a comprehensive comparison of these approaches. Finally, we identify open research issues that should be addressed in order to improve MAC aware routing techniques in VANETs

SVM-based indoor localization in Wireless Sensor Networks

International audienceThe need to locate objects and to be situated in the space, whether inside or outside, has long been the focus of a substantial amount of research. Especially in Wireless Sensor Networks, indoor localization has become an important issue in many fields of applications. In this paper, we propose an indoor location solution based on Support Vector Machine (SVM). SVM is a class of learning algorithms defined to resolve discrimination and regression problems. In fact, with many works, it turned out that it is very difficult to properly locate a target with only the RSSI measurements. Thus, the idea is to use multi-class SVM with RSSI measurements to propose a zoning localization approach. The performed experiments using different datasets, collected from two real world environments in both a hospital and a laboratory building, and the comparison with Artificial Neural Networks (ANN) confirm the effectiveness of our SVM-based localization proposal. Experimental results show that the system achieves a correct classification rate of around 90% with misclassification is in rooms where there is no wall separating them

Stacked Auto-Encoder for Scalable Indoor Localization in Wireless Sensor Networks

International audienceIn this paper, we propose a Deep Neural Network model based on WiFi-fingerprinting to improve the accuracy of zone location in a multi-building, multi-floor indoor environment. The proposed model is presented as a Stacked AutoEncoder (SAE) to allow efficient reduction of the feature space in order to achieve robust and precise classification. The multi-label classification is used to simplify and reduce the complexity of the learning classification task during the training phase. To achieve a hierarchical classification, we applied an argmax function on the multi-label output to convert the multi-label classification into multi-class classification ones to estimate the building, the floor and the zone identifier. Experimental results show that the proposed model achieves an accuracy of 100% for building, 99.66% for floor and 83.47% for zone location with a test time that does not exceed 10.21s

UAV-GCS Centralized Data-Oriented Communication Architecture for Crowd Surveillance Applications

International audienceIn recent years, a large number of researchers investigate the conception of systems that use a unique Unmanned Ariel Vehicles (UAV) or multiple independent UAVs to conduct civil or military missions, with minimal human intervention. In this paper we focus on using multiple UAVs to cooperatively monitor a crowded area. Communication in such UAVs network is an ongoing project. Due to the lack of proper communication standards and rules, designing a reliable communication model is essential for: (i) multi-UAV coordination, (ii) efficient bandwidth sharing according to data priority and urgency and (iii) avoiding useless transmission of the same data by multiple UAVs. To address the above challenges, we propose a centralized data-oriented communication architecture for crowd surveillance allocations using an UAV fleet. The Ground Control Station (GCS) is used as a central coordinator to manage bandwidth usage for the UAV fleet in its coverage area. To allow UAVs to send priority messages urgently to the GCS, we define two classes of urgent messages: critical state and important result. The class of the data as well as other relevant information about the detected event will be used by the GCS to authorize or not UAV data transmission and hence to optimize the bandwidth usage efficiency

UAV-based Surveillance System: an Anomaly Detection Approach

International audienceRecent advancements in avionics and electronics systems led to the increased use of Unmanned Aerial Vehicles (UAVs) in several military and civilian missions. One of the main advantages that makes UAVs attractive is their ability to reach remote regions that are inaccessible to human operators, i.e. provide new aerial perspective in visual surveillance. Autonomous visual surveillance systems require real time anomalies detection. However, there are many difficulties associated with automatic anomalies detection by an UAV, as there is a lack in the proposed contributions describing abnormal events detection in videos recorded by a drone. In this paper, we propose an anomaly detection approach in a surveillance mission where videos are acquired by an UAV. We combine deep features extracted using a pretrained Convolutional Neural Network (CNN) with an unsupervised classification method, namely One Class Support Vector Machine (OCSVM). The quantitative results obtained on the used dataset show that our proposed method achieves good results in comparison to existing technique with an Area Under Curve (AUC) of 0.93

Centralized Cognitive Radio Based Frequency Allocation for UAVs Communication

International audienceUnmanned Aerial Vehicles (UAVs) have known much popularity for dangerous missions for human operators or for applications which do not need human intervention (such as monitoring and surveillance of physical infrastructures and interest areas). They operate in frequency bands (IEEE L-Band, IEEE S-Band, and ISM band) shared with other users. Accordingly, these frequency bands have become overcrowded and UAVs may face the issue of spectrum scarcity. Furthermore, there are particular difficulties associated with aeronautical communication links. Cognitive radio (CR) has emerged as a promising strategy for resolving the problems caused by scarce spectrum. It checks the spectrum availability and allows the adjustment of the transmission parameters. The aim is to opportunistically use spectral bands with minimum interference to applications or other users. In this paper, we present a centralized CR based frequency allocation scheme for UAV-Ground Control Station (GCS) communication in surveillance applications within an urban environment. In the proposed model, the GCS monitors and allocates available WiMAX frequencies using CR and Software Defined Radio (SDR). If no WiMAX frequency is available at a given time, the Wi-Fi will be used. Therefore in the worst case, our approach will have the same performance as when the Wi-Fi is only used for UAV-GCS communication

FANET: Communication, mobility models and security issues

International audienceIn the last decades, technological progress in electronic and avionic systems, mainly device miniaturization and cost reduction, has boosted the performance of the UAV (Unmanned Ariel Vehicles). In addition to the military area, UAVs are nowadays very widespread in the field of civil application. Multiples UAVs system can cooperatively carry out missions more economically and efficiently compared to one UAV systems. Therefore, this choice lead to the development of new networking technologies between UAVs and ground control station. The UAVs network is known as FANET (Flying Ad-Hoc Network), and it is a subset of the MANET (Mobile Ad-Hoc Network). There are many problems to be addressed before effective use of FANET can be made in order to provide reliable and stable context specific networks. In this paper, a view of FANETs is presented from the networking communication challenges perspective. The scope of this survey is to give a comprehensive overview about the existing communications architectures proposed for the FANET networks. We expose the routing protocols, mobility and trajectory optimization models that have been used in FANET to solve communication and collaboration issues between UAVs, we outline the security challenges that need to be overcome and discuss FANET networking open issues. Our goal is to provide a general idea to the researchers about the different topics to be addressed in this area