Sidi Mohammed Senouci

A New Architecture for Data Collection in Vehicular Networks

Vehicular Sensor Networks (VSNs) are an emerging paradigm in vehicular networks. This new technology uses different kind of sensing devices available in new vehicles, to gather information about the drivers environment (speed, acceleration, temperature, seats occupations, etc.) in order to provide a safer, more efficient and more comfortable driving experience. In this paper, we focus on a particular VSN architecture, where the ad hoc network is operated by a telecommunication/service provider (WiMax access point, 2.5/3G base station) to combine non-valuable individual sensed data and extract from them effective feedbacks about the situation of the road in a geographical area (traffic density, unusual traffic behavior, etc.). In operated VSNs, providers tend to reduce the traffic load on their network, using unlicensed spectrum communication medium (IEEE 802.11p, for example). To do so, we propose CGP (Clustered Gathering Protocol), a cross layer protocol based on hierarchical and geographical data collection, aggregation and dissemination mechanisms. We analyze the performances of CGP using a simulation environment and realistic mobility models. We demonstrate the feasibility of such solution and show that CGP offers the operator precious information without overloading his network.

An accurate and efficient collaborative intrusion detection framework to secure vehicular networks

Display Omitted We design and implement an accurate and lightweight intrusion detection framework, called AECFV.AECFV aims to protect the vehicular ad hoc networks (VANETs) against the most dangerous attacks that could occurred on this network.AECFV take into account the VANETs characteristics such as high nodes mobility and rapid topology change.AECFV exhibits a high detection rate, low false positive rate, faster attack detection, and lower communication overhead. The advancement of wireless communication leads researchers to develop and conceive the idea of vehicular networks, also known as vehicular ad hoc networks (VANETs). Security in such network is mandatory due to a vital information that are managed by the vehicle. Therefore, in this paper we design and implement an accurate and lightweight intrusion detection framework, called AECFV, that aims to protect the network against the most dangerous attacks that could occur on such network. AECFV is suitable for VANETs characteristics such as high nodes mobility and rapid topology change. This is achieved with a help of the proposed secured clustering algorithm that considers both nodes mobility and network vulnerability during cluster formation. Clusters are constructed with a high stability and good connectivity. Cluster-Heads (CHs) are elected based on both nodes mobility and the vehicles trust-level. The simulation performed using NS-3 simulator shows, AECFV exhibits a high detection rate, low false positive rate, faster attack detection, and lower communication overhead compared to current detection frameworks.

An Efficient and Lightweight Intrusion Detection Mechanism for Service-Oriented Vehicular Networks

Vehicular ad hoc networks (VANETs) are wireless networks that provide high-rate data communication among moving vehicles and between the vehicles and the road-side units. VANETs are considered as the main wireless communication platforms for the intelligent transportation systems (ITS). Service-oriented vehicular networks are special categories for VANETs that support diverse infrastructure-based commercial infotainment services including, for instance, Internet access, real-time traffic monitoring and management, video streaming. Security is a fundamental issue for these service networks due to the relevant business information handled in these networks. In this paper, we design and implement an efficient and light-weight intrusion detection mechanism, called efficient and light-weight intrusion detection mechanism for vehicular network (ELIDV) that aims to protect the network against three kinds of attacks: denial of service (DoS), integrity target, and false alerts generation. ELIDV is based on a set of rules that detects malicious vehicles promptly and with high accuracy. We present the performance analysis of our detection mechanism using NS-3 simulator. Our simulation results show that ELIDV exhibits a high-level security in terms of highly accurate detection rate (detection rate more than 97%), low false positive rate (close to 1%), and exhibits a lower overhead compared to contemporary frameworks.

A novel secure aggregation scheme for wireless sensor networks using stateful public key cryptography

Wireless sensor networks (WSNs) are nowadays considered as an important part of the Internet of Things (IoT). In these networks, data aggregation plays an essential role in energy preservation. However, WSNs are usually deployed in hostile and unattended environments (e.g. military applications) in which the confidentiality and integrity security services are widely desired. Recently, homomorphic encryptions have been applied to conceal sensitive information during aggregation such that algebraic operations are done directly on ciphertexts without decryption. The main benefit is that they offer the end-to-end data confidentiality and they do not require expensive computation at aggregator nodes since no encryption and decryption are performed. However, existing solutions either incur a considerable overhead or have limited applicability to certain types of aggregate queries. This paper presents a novel secure data aggregation protocol for WSNs. The scheme employs Stateful Public Key Encryption (StPKE) and some previous techniques in order to provide an efficient end-to-end security. Moreover, our solution does not impose any bound on the aggregation functions nature (Maximum, Minimum, Average, etc.). We present and implement our scheme on TelosB as well as MicaZ sensor network platforms and measure the execution time of our various cryptographic functions. Simulations are also conducted to show how our scheme can achieve a high security level (by providing the above security services) with a low overhead (in terms of computation and communication) in large-scale scenario.

An efficient intrusion detection framework in cluster-based wireless sensor networks

In the last few years, the technological evolution in the field of wireless sensor networks was impressive, which made them extremely useful in various applications (military, commercial, etc.). In such applications, it is essential to protect the network from malicious attacks. This presents a demand for providing security mechanisms in these vulnerable networks. In this paper, we design a new framework for intrusion detection in cluster-based wireless sensor networks. Our detection framework is composed of different protocols that run at different levels. The first protocol is a specification-based detection protocol that runs at intrusion detection system (IDS) agents (low level). The second one is a binary classification detection protocol that runs at cluster head (CH) node (medium level). In addition, a reputation protocol is used at each CH to evaluate the trustworthiness level of its IDSs agents. Each CH monitors its CH neighbors on the basis of a specification detection protocol with the help of a vote mechanism applied at the base station (high level). We evaluated the performances of our framework in the presence of four well-known attacks: hello flood, selective forwarding, black hole, and wormhole attacks. We evaluated specifically the detection rate, false positive rate, energy consumption, and efficiency. Simulation results show that our detection framework exhibits high detection rate (almost 100%), low number of false positives, less time to detect the attack, and less energy consumption. Our intrusion detection framework outperforms other schemes proposed in the literature in terms of detection, false positive rate, and energy consumption. Copyright

A new Intrusion Detection Framework for Vehicular Networks

In this paper, we design and implement a new Intrusion Detection Framework for Vehicular Networks (IDFV). These networks are vulnerable to various security attacks due to the lack of centralized infrastructure. The aim of our framework is then to secure them against the most dangerous routing attacks that have a high severity damage such as selective forwarding, black hole, wormhole, packets duplication and resource exhaustion attacks that can target such networks. IDFV relies on a set of detection and eviction techniques to detect, in a short delay, malicious vehicles with a high accuracy and eject them. Furthermore, IDFV applies a robust reputation schema to evaluate vehicles trust level. We analyze the performances of our framework using NS-3. Simulation results show that IDFV exhibits a high level of security i.e. high detection rate, low false positive rate and a fast attacks detection compared to detection frameworks proposed in current literature.

Sustainable Transportation Management System for a Fleet of Electric Vehicles

In the last few years, significant efforts have been devoted to developing intelligent and sustainable transportation to address pollution problems and fuel shortages. Transportation agencies in various countries, along with several standardization organizations, have proposed different types of energy sources (such as hydrogen, biodiesel, electric, and hybrid technologies) as alternatives to fossil fuel to achieve a more ecofriendly and sustainable environment. However, to achieve this goal, there are significant challenges that still need to be addressed. We present a survey on sustainable transportation systems that aim to reduce pollution and greenhouse gas emissions. We describe the architectural components of a future sustainable means of transportation, and we review current solutions, projects, and standardization efforts related to green transportation with particular focus on electric vehicles. We also highlight the main issues that still need to be addressed to achieve a green transportation management system. To address these issues, we present an integrated architecture for sustainable transportation management systems.

Detection and prevention from misbehaving intruders in vehicular networks

In this paper, we design and implement a new intrusion detection and prevention schema for vehicular networks. It has the ability to detect and predict with a high accuracy a future malicious behavior of an attacker. This is unlike the current detection schémas, where there is no prevention technique since they aim to detect only current attackers that occur in the network. We used game theory concept to predict the future behavior of the monitored vehicle and categorize it into the appropriate list (White, White & Gray, Gray, and Revocation_Black) according to its predicted attack severity. In this paper, our aim is to prevent from the most dangerous attack that targets a vehicular network, which is false alerts generation attack. Simulation results show that our intrusion detection and prevention schema exhibits a high detection rate and generates a low false positive rate. In addition, it requires a low overhead to achieve a high-level security.

A new framework of self-organization of vehicular networks

Vehicular networks are drawing a great attention from the research community and the automotive industry, where they are beneficial in providing ITS (Intelligent Transportation System) services as well as assisting the drivers on the road. In this context, vehicular networks are based on V2I (Vehicle to Infrastructure) and V2V (Vehicle to Vehicle) communications. The special characteristics of these networks such as high mobility, potentially large scale, and network partitioning introduce several challenges, which greatly impact the deployment of these networks. An efficient solution to these problems is to define a robust self-organizing architecture. Thus, the function of these dynamic networks can be quite improved. In this paper, we introduce a new proactive self-organizing protocol called CSP (Cluster-based Self-organizing Protocol) that uses the geographic clustering and the virtual backbone to structure intelligently the vehicular network. We compare CSP to other self-organizing solution by analyzing its performances using Qualnet simulator. Simulation results show good performance of CSP in terms of architecture stability, overhead and delivery ratio.

COL: A data collection protocol for VANET

In this paper, we present a protocol to collect data within a vehicular ad hoc network (VANET). In spite of the intrinsic dynamic of such network, our protocol simultaneously offers three relevant properties: (1) It allows any vehicle to collect data beyond its direct neighborhood (i.e., vehicles within direct communication range) using vehicle-to-vehicle communications only (i.e., the infrastructure is not required); (2) It tolerates possible network partitions; (3) It works on demand and stops when the data collection is achieved. To the best of our knowledge, this is the first collect protocol having these three characteristics. All that is chiefly obtained thanks to a specific tool, namely Operator ant, borrowed from the self-stabilization area which confers to our algorithm the nice property to recover by itself from topology changes. In addition to a theoretical proof of correctness, our protocol has been implemented and tested through the Airplug Software Distribution: Road and lab experiments are presented and discussed.