Sofiane Aissani’s research while affiliated with University of Technology of Troyes and other places

Network slicing is one 5G network enabler that may be used to enhance the requirements of mission-critical Machine Type Communications (mcMTC) in critical IoT applications. But, in applications with high mobility support, the network slicing will also be influenced by users’ movement, which is necessary to handle the dynamicity of the system, especially for critical slices that require fast and reliable delivery from End to End (E2E). To fulfill the desired service quality (QoS) of critical slices due to their users’ movement. This paper presents mobility awareness for such types of applications through mobility prediction, in which the network can determine which cell the user is in near real-time. Furthermore, the proposed next-cell mobility prediction framework is developed as a multi-classification task, where we exploited Long Short-Term Memory (LSTM) and the collected historical mobility profiles of moving users to allow more accurate short- and long-term predictions of the candidate next-cell. Then, within the scope of high mobility mission-critical use cases, we evaluate the effectiveness of the proposed LSTM classifier in vehicular networks. We have used a real vehicle mobility dataset that is obtained from SUMO deployed in Bejaia, Algeria urban environment. Ultimately, we conducted a set of experiments on the classifier using datasets with various history lengths, and the results have validated the effectiveness of the performed predictions on short-term mobility prediction. Our experiments show that the proposed classifier performs better on longer history datasets. While compared to traditional Machine Learning (ML) algorithms used for classification, the proposed LSTM model outperformed ML methods with the best accurate prediction results.

Connected Vehicles (CVs) are the key enabling technology for Intelligent Transportation Systems (ITSs) that offer great opportunities for improving traffic safety and efficiency. They provide several innovative safety-related applications such as traffic management and monitoring, which involve the transmission of messages from all vehicles on the road. Basic Safety Messages (BSMs) constitute an essential type of control message. However, several critical issues affect the BSM messages’ reliability. In this paper, a model-based approach for detecting discordant BSMs is proposed, which allows to avoid the vehicle disturbance. This approach consists of detecting incoherence in communication metric values, where the detection is formulated as an anomaly detection problem that is solved using the Gaussian distribution. The detection process allows the vehicles to cross their prediction to achieve more precision in deciding whether to accept or reject a message from a vehicle. The efficiency of our model for detecting an anomaly has been evaluated through simulations using our generated dataset. The obtained results indicate that the proposed model provides high performance in terms of detection rate. Moreover, we evaluate and validate the proposed approach through formal evaluation, where it demonstrates promising performances, as compare it with a concurrent approach through simulations considering important metrics.

The autonomous vehicles emergence is a significant step forward in the development of safe and dependable intelligent transportation systems. In vehicular automation, digital connectivity has been one of the most critical specifications. In this paper, we focus on the autonomous train, which is one of the most rapidly growing applications of autonomous vehicles. In this context, we address the issue of safety by the proposition of Enhanced Train-centric Communication-Based Train Control (ETcCBTC), which provides efficient control of rail traffic. To ensure the operation’s safety, we’ve implemented a new safety-checking approach based on process algebra, which aims to track and correct in real time the train behavior. The proposed ETcCBTC system’s performance is tested using extensive simulations and compared to CBTC and TcCBTC. In terms of checking success, transmission load, and response time, the obtained results demonstrate that ETcCBTC outperforms the concurrent systems.

The fast evolution in microelectronics and the emergence of wireless communication technologies, have allowed the appearance of the promising field of Internet of Things (IoT). The latter is more and more present in the human life, that is why it becomes essential to secure the communications done with the connected objects. Almost all communicating systems attach great importance to security, consequently, on the cryptographic key management. The existing key management schemes for conventional networks are relatively resource-intensive, that is why they are not adequate for resource-constrained networks like IoT, especially since the nodes’ capabilities are heterogeneous. In this paper, we focus on exchanging and updating of cryptographic keys among the IoT objects often limited in resources, where we propose a new form of key exchange based on the mechanism of concealing encryption keys, while exploiting the misused spaces in the header fields of the exchanged packets by the communication standards, such as ZigBee, BLE, WiFi.

The existing cryptographic key management mechanisms are implemented as independent modules, they generate their own messages which consumes considerable energy. The novelty of our approach is that it does not generate any specific message by dint of steganography. Indeed, the main contribution in SKMSI-CL is the concealment the key parts in the misused spaces in the packets headers of the ZigBee standard. We exploit the messages sent by the Cell-LEACH routing protocol in order to send the key parts. We set up several types of keys to support multiple types of communications and stay in step with the data aggregation paradigm. We formally analyze some of the security properties of our protocol. Finally, we validate our performance with simulations, the results show that the network lifetime and the overall remaining energy are largely better in our scheme.

Mobile Wireless Sensor Network (MWSN) is a set of interconnected mobile sensor devices forming a dynamic network without a fixed administration. MWSN is used in various domains, such as disaster detection, medical systems, military applications, vehicular communications, and in other sensitive applications. Compared to the classical sensor networks, MWSNs involve an additional constraint consisting of the topology change frequency caused by the mobility of sensor devices. This influences highly the energy consumption and consequently the network reliability. In this paper, we take in charge this important issue and we contribute by the proposition of an efficient and energy-aware routing protocol. The proposed protocol operates for both request and event oriented MWSN applications. It introduces the sensor device mobility history in order to build-up stable routing paths, and incorporates a novel technique of dissimulation in order to exchange the mobility control messages without overhead. We have evaluated the performances of the proposed protocol through simulations, in which it provides effective results in terms of energy consumption and load-balancing.

Key management is the basic building block of all the security protocols and is one of the most challenging issues in wireless sensor networks (WSNs). Centralising a trusted key management server is not an appropriate solution in such fully distributed networks. On the other hand, designing a distributed key management system is a challenging task, due to the constrained characteristics of sensor nodes, which are limited in storage, computation, communication, and energy. In the literature, there is a hot research effort on key management purpose for WSNs. The greatest part of the existing solutions focuses mainly on the optimisation of the key number, rekeying frequency and process or the encryption system of the distributed keys. Unfortunately, these systems are implemented as an additional and independent service, involving a considerable overhead. In this study, the authors propose μKMS (micro key management system) for WSNs. μKMS implements a dissimulation scheme, embedding the rekeying process messages on the unexploited coding space of the exchanged ZigBee packets. They have developed simulations, where the obtained results show the relevance of μKMS in terms of communication overhead, storage overhead, and energy consumption.