Intelligent Misbehavior Detection System for Detecting False Position Attacks in Vehicular Networks

in Hawlader, Faisal; Boualouache, Abdelwahab; Faye, Sébastien (Eds.) et al The 2021 IEEE International Conference on Communications (the 4th Workshop on 5G and Beyond Wireless Security) (2021, June)

Position falsification attacks are one of the most dangerous internal attacks in vehicular networks. Several Machine Learning-based Misbehavior Detection Systems (ML-based MDSs) have recently been proposed ... [more ▼]

Position falsification attacks are one of the most dangerous internal attacks in vehicular networks. Several Machine Learning-based Misbehavior Detection Systems (ML-based MDSs) have recently been proposed to detect these attacks and mitigate their impact. However, existing ML-based MDSs require numerous features, which increases the computational time needed to detect attacks. In this context, this paper introduces a novel ML-based MDS for the early detection of position falsification attacks. Based only on received positions, our system provides real-time and accurate predictions. Our system is intensively trained and tested using a publicly available data set, while its validation is done by simulation. Six conventional classification algorithms are applied to estimate and construct the best model based on supervised learning. The results show that the proposed system can detect position falsification attacks with almost 100% accuracy. [less ▲]

Adaptive Content Seeding for Information-Centric Networking under High Topology Dynamics: Where You Seed Matters

in IEEE Vehicular Technology Magazine (2021), 16(2),

High-fidelity content distribution and other emerging applications of 5G and beyond-5G mobile broadband networking can put massive load on the core and Radio Access Network (RAN). To address this, direct ... [more ▼]

High-fidelity content distribution and other emerging applications of 5G and beyond-5G mobile broadband networking can put massive load on the core and Radio Access Network (RAN). To address this, direct Device to Device (D2D) communication has recently become a first-class citizen of these networks. While Information-Centric Vehicular Networking (ICVN) based on fog computing can indeed exploit such D2D links to alleviate the load on the RAN by proactively seeding content in the network, it has been shown that such seeding can cause even more load if performed where not needed. In addition, trying to determine where to seed content often causes additional load, negating the benefit of seeding. In this work, we therefore propose to adaptively seed fog nodes based on a purely virtual clustering approach. Here, vehicles are unaware of clustering decisions, thus no longer requiring an explicit exchange of control messages. We show that the benefit of such an adaptive approach goes beyond simply being able to flexibly trade off performance metrics versus each other: instead, it can consistently lower the load on the RAN link. We also show that this property even holds if node location information is only available as coarsely-grained as macro-scale grid cells. [less ▲]

Software-Defined Location Privacy Protection for Vehicular Networks

in Boualouache, Abdelwahab; Soua, Ridha; Qiang, Tang (Eds.) et al Machine Intelligence and Data Analytics for Sustainable Future Smart Cities (2021)

While the adoption of connected vehicles is growing, security and privacy concerns are still the key barriers raised by society. These concerns mandate automakers and standardization groups to propose ... [more ▼]

While the adoption of connected vehicles is growing, security and privacy concerns are still the key barriers raised by society. These concerns mandate automakers and standardization groups to propose convenient solutions for privacy preservation. One of the main proposed solutions is the use of Pseudonym-Changing Strategies (PCSs). However, ETSI has recently published a technical report which highlights the absence of standardized and efficient PCSs [1]. This alarming situation mandates an innovative shift in the way that the privacy of end-users is protected during their journey. Software Defined Networking (SDN) is emerging as a key 5G enabler to manage the network in a dynamic manner. SDN-enabled wireless networks are opening up new programmable and highly-flexible privacy-aware solutions. We exploit this paradigm to propose an innovative software-defined location privacy architecture for vehicular networks. The proposed architecture is context-aware, programmable, extensible, and able to encompass all existing and future pseudonym-changing strategies. To demonstrate the merit of our architecture, we consider a case study that involves four pseudonym-changing strategies, which we deploy over our architecture and compare with their static implementations. We also detail how the SDN controller dynamically switches between the strategies according to the context. [less ▲]

Out-of-the-box Multipath TCP as a Tor Transport Protocol: Performance and Privacy Implications

in 19th IEEE International Symposium on Network Computing and Applications (IEEE NCA 2020) (2020, November 25)

Locust: Highly Concurrent DHT Experimentation Framework for Security Evaluations

in Proceedings of ICPS ICCNS 2020 (2020, November)

Distributed Hash Table (DHT) protocols, such as Kademlia, provide a decentralized key-value lookup which is nowadays integrated into a wide variety of applications, such as Ethereum, InterPlanetary File ... [more ▼]

Distributed Hash Table (DHT) protocols, such as Kademlia, provide a decentralized key-value lookup which is nowadays integrated into a wide variety of applications, such as Ethereum, InterPlanetary File System (IPFS), and BitTorrent. However, many security issues in DHT protocols have not been solved yet. DHT networks are typically evaluated using mathematical models or simulations, often abstracting away from artefacts that can be relevant for security and/or performance. Experiments capturing these artefacts are typically run with too few nodes. In this paper, we provide Locust, a novel highly concurrent DHT experimentation framework written in Elixir, which is designed for security evaluations. This framework allows running experiments with a full DHT implementation and around 4,000 nodes on a single machine including an adjustable churn rate; thus yielding a favourable trade-off between the number of analysed nodes and being realistic. We evaluate our framework in terms of memory consumption, processing power, and network traffic. [less ▲]

Enhancing CoAP Group Communication to Support mMTC Over Satellite Networks

in IEEE International Conference on Communications (ICC) (2020, June)

Massive MTC (mMTC) is one of the application scenarios that upcoming 5G networks are expected to support. Satellites come into play in mMTC to complement and extend terrestrial networks in under-served ... [more ▼]

Massive MTC (mMTC) is one of the application scenarios that upcoming 5G networks are expected to support. Satellites come into play in mMTC to complement and extend terrestrial networks in under-served areas, where several services can benefit from the adoption of a group communication model. The IETF has specifically standardized the usage of CoAP group communication. However, CoAP responses are still sent in unicast from each single CoAP server to the CoAP client, which results in a substantial traffic load. Such problem becomes more severe in integrated IoT-Satellite networks given the limited bandwidth of the satellite return channel and the large number of IoT devices in a mMTC scenario. To reduce network traffic overhead in group communication and improve the network responsiveness, this paper proposes an aggregation scheme for the CoAP group communication in combination with Observer pattern and proxying. Results obtained by using the openSAND emulator and CoAPthon library corroborate the merit of our optimization in terms of overhead reduction and delay. [less ▲]

SDN-based Misbehavior Detection System for Vehicular Networks

in 2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring) (2020, May)

Vehicular networks are vulnerable to a variety of internal attacks. Misbehavior Detection Systems (MDS) are preferred over the cryptography solutions to detect such attacks. However, the existing ... [more ▼]

Vehicular networks are vulnerable to a variety of internal attacks. Misbehavior Detection Systems (MDS) are preferred over the cryptography solutions to detect such attacks. However, the existing misbehavior detection systems are static and do not adapt to the context of vehicles. To this end, we exploit the Software-Defined Networking (SDN) paradigm to propose a context-aware MDS. Based on the context, our proposed system can tune security parameters to provide accurate detection with low false positives. Our system is Sybil attack-resistant and compliant with vehicular privacy standards. The simulation results show that, under different contexts, our system provides a high detection ratio and low false positives compared to a static MDS. [less ▲]

A Multi-Hop Broadcast Wave Approach for Floating Car Data Collection in Vehicular Networks

in Vehicular Communications (2020)

Inter-Vehicle Communication (IVC) is bringing connected and cooperative mobility closer to reality. Vehicles today are able to produce huge amounts of information, known in the literature as Floating Car ... [more ▼]

Inter-Vehicle Communication (IVC) is bringing connected and cooperative mobility closer to reality. Vehicles today are able to produce huge amounts of information, known in the literature as Floating Car Data (FCD), containing status information gathered from sensing the internal condition of the vehicle and the external environment. Adding networking capabilities to vehicles allows them to share this information among themselves and with the infrastructure. Collecting real-time FCD information from vehicles opens up the possibility of having access to an enormous amount of useful information that can boost the development of innovative services and applications in the domain of Intelligent Transportation System (ITS). In this paper we propose several solutions to efficiently collect real-time FCD information in Dedicated Short-Range Communication (DSRC)-enabled Vehicular Ad Hoc Networks (VANETs). The goal is to improve the efficiency of the FCD collection operation while keeping the impact on the DSRC communication channel as low as possible. We do this by exploiting a slightly modified version of a standardized data dissemination protocol to create a backbone of relaying vehicles that, by following local rules, generate a multi-hop broadcast wave of collected FCD messages. The proposed protocols are evaluated via realistic simulations under different vehicular densities and urban scenarios. [less ▲]

POSTER: Traffic Splitting to Counter Website Fingerprinting

Poster (2019, November 11)

Big Automotive Data Preprocessing: A Three Stages Approach

Poster (2019, October 08)

The automotive industry generates large datasets of various formats, uncertainties and frequencies. To exploit Automotive Big Data, the data needs to be connected, fused and preprocessed to quality ... [more ▼]

The automotive industry generates large datasets of various formats, uncertainties and frequencies. To exploit Automotive Big Data, the data needs to be connected, fused and preprocessed to quality datasets before being used for production and business processes. Data preprocessing tasks are typically expensive, tightly coupled with their intended AI algorithms and are done manually by domain experts. Hence there is a need to automate data preprocessing to seamlessly generate cleaner data. We intend to introduce a generic data preprocessing framework that handles vehicle-to-everything (V2X) data streams and dynamic updates. We intend to decentralize and automate data preprocessing by leveraging edge computing with the objective of progressively improving the quality of the dataflow within edge components (vehicles) and onto the cloud. [less ▲]