Soufiene Djahel

Mitigating Packet Dropping Problem in Mobile Ad Hoc Networks: Proposals and Challenges

In mobile ad hoc networks (MANETs), nodes usually cooperate and forward each others packets in order to enable out of range communication. However, in hostile environments, some nodes may deny to do so, either for saving their own resources or for intentionally disrupting regular communications. This type of misbehavior is generally referred to as packet dropping attack or black hole attack, which is considered as one of the most destructive attacks that leads to the network collapse. The special network characteristics, such as limited battery power and mobility, make the prevention techniques based on cryptographic primitives ineffective to cope with such attack. Rather, a more proactive alternative is required to ensure the safety of the forwarding function by staving off malicious nodes from being involved in routing paths. Once such scheme fails, some economic-based approaches can be adopted to alleviate the attack consequences by motivating the nodes cooperation. As a backup, detection and reaction schemes remain as the final defense line to identify the misbehaving nodes and punish them. In this paper, we make a comprehensive survey investigation on the state-of-the-art countermeasures to deal with the packet dropping attack. Furthermore, we examine the challenges that remain to be tackled by researchers for constructing an in-depth defense against such a sophisticated attack.

An Acknowledgment-Based Scheme to Defend Against Cooperative Black Hole Attacks in Optimized Link State Routing Protocol

In this paper, we address the problem of cooperative black hole attack, one of the major security issues in mobile ad hoc networks. The aim of this attack is to force nodes in the network to choose hostile nodes as relays to disseminate the partial topological information, thereby exploiting the functionality of the routing protocol to retain control packets. In optimized link state routing (OLSR) protocol, if a cooperative black hole attack is launched during the propagation of topology control (TC) packets, the topology information will not be disseminated to the whole network which may lead to routing disruption. In this paper, we investigate the effects of the cooperative black hole attack against OLSR, in which two colluding MPR nodes cooperate in order to disrupt the topology discovery. Then we propose an acknowledgment based technique that overcomes the shortcomings of the OLSR protocol, and makes it less vulnerable to such attacks by identifying and then isolating malicious nodes in the network. The simulation results of the proposed scheme show high detection rate under various scenarios.

Adaptive traffic management for secure and efficient emergency services in smart cities

Rapid increase in number of vehicles on the roads as well as growing size of cities have led to a plethora of challenges for road traffic management authorities such as traffic congestion, accidents and air pollution. The work presented in this paper focuses on the particular problem of traffic management for emergency services, for which a delay of few minutes may cause human lives risks as well as financial losses. The goal is to reduce the latency of emergency services for vehicles such as ambulances and police cars, with minimum unnecessary disruption to the regular traffic, and preventing potential misuses. To this end, we propose to design a framework in which the Traffic Management System (TMS) may adapt by dynamically adjusting traffic lights, changing related driving policies, recommending behavior change to drivers, and applying essential security controls. The choice of an adaptation depends on the emergency severity level announced by the emergency vehicle(s). The severity level may need to be verified by corresponding authorities to preserve security measures. We discuss the details of our proposed framework and the potential challenges in the paper.

A comparative study of vehicles' routing algorithms for route planning in smart cities

Vehicle routing problem (VRP) is a generic name referring to optimization problems in transportation, distribution and logistics industry. They mainly focus on serving a number of customers by a number of vehicles. Route planning techniques is one of the main tasks of VRP which aims to find an optimal route from a starting point to a destination on a road map. As road traffic conditions may change during the car journey (e.g., increase/decrease of the congestion level, road incidents etc), the optimal route should be re-evaluated as soon as an update in traffic conditions is available. Choosing an appropriate route planning algorithm among the existing algorithms in the literature to apply it in real road networks is an important task for any transportation application. In this paper, we first present a classification of the different route planning algorithms, and then explain how we compare and analyze their performance when they are applied in real road networks. For the purpose of comparison, we simulate the behavior of these algorithms during runtime using Simulation of Urban Mobility (SUMO) package and TRACI. We have chosen Dijkstra, the most wellknown shortest path algorithm, to be the first algorithm to be implemented in SUMO. Upon reception of any traffic conditions update that affects the current optimal route of a car, we use TRACI to re-apply the algorithm and change this cars route accordingly. In the near future, our target is to simulate other algorithms and compare their performance based on the quality of the obtained best route.

Toward energy-efficient and trustworthy eHealth monitoring system

The rapid technological convergence between Internet of Things (IoT), Wireless Body Area Networks (WBANs) and cloud computing has made e-healthcare emerge as a promising application domain, which has significant potential to improve the quality of medical care. In particular, patient-centric health monitoring plays a vital role in e-healthcare service, involving a set of important operations ranging from medical data collection and aggregation, data transmission and segregation, to data analytics. This survey paper firstly presents an architectural framework to describe the entire monitoring life cycle and highlight the essential service components. More detailed discussions are then devoted to {\em data collection} at patient side, which we argue that it serves as fundamental basis in achieving robust, efficient, and secure health monitoring. Subsequently, a profound discussion of the security threats targeting eHealth monitoring systems is presented, and the major limitations of the existing solutions are analyzed and extensively discussed. Finally, a set of design challenges is identified in order to achieve high quality and secure patient-centric monitoring schemes, along with some potential solutions.

Smart adaptation of beacons transmission rate and power for enhanced vehicular awareness in VANETs

In this work, we are interested in periodic beacons transmission, the main cause of the Control Channel (CCH) congestion and the major obstacle delaying the progress of safety messages dissemination in VANETs. In order to offload the network, solutions that range from transmit rate to transmit power adaptations including hybrid solutions have been proposed. Although some of these solutions have managed to successfully reduce the load on the wireless channel, none, to the best of our knowledge, have considered the impact of the applied adaptation scheme on the overall level of awareness among vehicles and its quality. ETSI TS released a technical specification stating a limit for the minimum beacons transmit rate in order to maintain a good level of awareness among vehicles and ensure a certain accuracy in VANET applications. In this paper, we propose to jointly adapt both transmit rate and power in a new smart way that guarantees a strict beaconing frequency as well as a good level of awareness in closer ranges, while maintaining a marginal beacons collision rate and a good level of channel utilisation. First, the transmit rate is adapted to meet the channel requirements in terms of collision rate and channel load; then, once the minimum beacon transmit rate, set by ETSI, has been reached, transmit power is adapted in a way that guarantees a good level of awareness for closer neighbours. The simulation results show a significant enhancement in terms of the quality as well as the level of awareness.

A Multi-Agent Based Vehicles Re-routing System for Unexpected Traffic Congestion Avoidance

As urbanization has been spreading across the world for decades, the traffic congestion problem becomes increasingly serious in most of the major cities. Among the root causes of urban traffic congestion, en route events are the main source of the sudden increase of the road traffic load, especially during peak hours. The current solutions, such as on-board navigation systems for individual vehicles, can only provide optimal routes using current traffic data without considering any traffic changes in the future. Those solutions are thus unable to provide a better alternative route quickly enough if an unexpected congestion occurs. Moreover, using the same alternative routes may lead to new bottlenecks that cannot be avoided. Thus a global traffic load balance cannot be achieved. To deal with these problems, we propose a Multi Agent System (MAS) that can achieve a trade-off between the individual and global benefits by giving the vehicles optimal turn suggestions to bypass a blocked road ahead. The simulation results show that our strategy achieves a substantial gain in average trip time reduction under realistic scenarios. Moreover, the negative impact of selfish re-routing is investigated to show the importance of altruistic re-routing applied in our strategy.

A Hidden Markov Model based scheme for efficient and fast dissemination of safety messages in VANETs

Nowadays, Vehicle to Vehicle (V2V) communication is attracting an increasing attention from car manufacturers due to its expected impact in improving driving safety and comfort. IEEE 802.11P is the primary channel access scheme used by vehicles; however it does not provide sufficient spectrum to ensure reliable exchange of safety information. To overcome this issue, many efforts have been devoted to enhance the frequency spectrum utilization efficiency. To this end, the Cognitive Radio (CR) principle has been applied to assist the vehicles to gain extra bandwidth through an opportunistic use of the unused spectrums in their surrounding. In this paper, we focus on safety messages for which we propose an original scheme that makes their exchange among the nearby vehicles more reliable with a significant reduce in their dissemination delay. This improvement is due to the use of a Hidden Markov Model that enables the prediction of the available channels for the subsequent time slots, leading to faster channel allocation for the vehicles. The obtained simulation results confirm the efficiency of our scheme.

Fast and Efficient Countermeasure for MAC Layer Misbehavior in MANETs

In this paper, we deal with backoff cheating technique in IEEE802.11 based MANETs and propose a novel scheme, dubbed HsF-MAC (Hash Function based MAC protocol), to cope with it. In contrast to the existing solutions, HsF-MAC allows MANET nodes to re-calculate the backoff value used by their 1-hop neighbors and immediately detect the misbehaving ones. Moreover, the colluding behavior of two cheating nodes is also considered along with effective countermeasures. A reconciliation based reaction mechanism is finally designed. The simulation results, under different topologies and network conditions, have validated the effectiveness of HsF-MAC.

Defending against packet dropping attack in vehicular ad hoc networks

Vehicular ad hoc networks (VANETs) are becoming very popular and a promising application of the so-called mobile ad hoc networks (MANET) technology. It has attracted recently an increasing attention from many car manufacturers as well as the wireless communication research community. Despite its tremendous potential to enhance road safety and to facilitate traffic management, VANET suffers from a variety of security and privacy issues which may dramatically limit their applications. In this paper, we address the problem of packet dropping attack launched against routing protocols control packets, which represents one of the most aggressive attacks in MANET. The aim of this attack is to force nodes in the network to choose hostile nodes as relays to disseminate the partial topological information, thereby exploiting the functionality of the routing protocol to retain control packets. In particular, in optimized link state routing (OLSR) protocol, if a collusive packet dropping attack is launched during the propagation of the topology control (TC) packets, the topology information will fail in being disseminated to the entire network, which finally results in routing disruption. This paper focuses on the packet dropping attack, launched against OLSR, where two malicious multipoint relay (MPR) nodes collude to disrupt the topology discovery process. Based on the analysis of the attackers behavior and the attacks consequence, we propose an acknowledgement-based mechanism as a countermeasure to enhance the security of OLSR. This mechanism helps the OLSR protocol to be less vulnerable to such attack by detecting and then isolating malicious nodes in the network. The simulation results of the proposed scheme show high detection rate under various scenarios. Copyright