The Internet of Drones (IoD) has recently gained popularity in several areas, such as military operations, smart agriculture, traffic analysis and Search And Rescue (SAR). In a SAR mission, drones' localization is a key element of IoD. It is a fundamental process in Cyber-Physical Systems (CPS), where environmental and location data are intimately linked. However, the protection of the drone's localization from security attacks and threats like injection of false locations and data by malicious drones, remains a major concern. In this paper, we present a novel approach for securing drone's localization during SAR mission using Intrusion Prevention System (IPS). Our main objective is to detect any trajectory deviation using the anomaly behavior based on node's reputation and to isolate malicious drones when an alert is triggered. Our model consists of a Master Drone (MD), selected based on its high performance compared to other drones, and a Ground Control Station (GCS) that configures the drones with the necessary parameters for the mission. The MD is synchronized with GCS to analyze the behavior of other drones using our IPS and a reputation value to determine if there is a significant deviation, indicating that the planned trajectory has been modified or altered. The proposed system model is based on IPS and trust management in order to detect the deviation of drones from their already configured trajectory planning. A case study of the proposed framework is provided in this paper.

Unmanned Aerial Vehicles (UAVs) are versatile, used for tasks such as surveillance, mapping and delivery, offering cost-effective and efficient solutions in various industries. Hence, the rapid advancements of UAVs technologies increase their confrontation to substantial challenges like their constrained capacities: endurance, range, data process, etc. In addition, security and privacy of UAVs are a primary issue since attacks on UAV systems can cause loss of life and property. Ensuring drones authentication has become imperative to limit several kinds of attacks. UAVs networks management is also a challenging condition to ensure flexibility and scalability. Therefore, in this paper, we aim to ensure a secure UAV network by proposing a lightweight authentication mechanism based on Elliptic Curve Cryptographic (ECC) based on Software Defined Drone Network (SDDN). Through the proposed SDDN architecture, a secure efficient management of network resources is provided. Using this proposed authentication process, attacks such as Man-In- The-Middle, ID spoofing, replay, injection, modification, etc. are detected. To prove the effectiveness of our proposition, we validate it using two methods: A case study that illustrate the different attacks prevented and detected by our protocol. A formal security analysis using the Automated Validation of Internet Security Protocols and Applications (AVISPA) tool in order to confirm the safety of the proposal.

E-health guarantees the continuity of medical care and facilitates communication between the patient and healthcare organizations. For this reason, medical data must be accessible at all times and exchanged between stakeholders. Given the highly sensitive nature of this data and the increasing frequency of data breaches, it is crucial to implement strict privacy and security measures. Since patient is considered the owner of his medical data under laws as the Health Insurance Portability and Accountability Act HIPAA and the General Data Protection Regulation GDPR, he/she must have the right to privacy and to make decisions about sharing sensitive data. On the other hand, the stakeholders with whom the patient will share its information are not similar; each one requires specific data for different purposes. That's why the data transfer should not be performed in the same manner. In this article, we propose a framework to ensure the security and privacy of data processing in E-health systems. This framework is based on smart contracts to manage patient consent and traceability of data transfer, as well as mechanisms to classify data and apply the most suitable data masking technique to protect efficiently sensitive information.

In Vehicular Ad hoc NETworks (VANETs), vehicles exchange safety messages containing valuable information about traffic environment to increase roads’ safety. The critical nature of these messages entails securing them before considering them. In this context, the credibility and the accuracy assessment of these included safety information arises as a necessity since the consumption of false or imprecise ones by vehicles may cause hazardous consequences. To treat this requirement, we proposed the scheme [1] enabling vehicles to evaluate the credibility and the accuracy of the contents of the safety messages exchanged in VANETs. That scheme is based on three modules: a reputation module, a time and location closeness estimation module, and a majority module. A vehicle can use these modules in a separated or joint way according to the circumstances. Since that scheme is error prone, we conducted in [2], a formal validation, using inference system, to prove the soundness and the completeness of these three modules and their combination. In this paper, we complete that formal validation of [1] by handling the junctions of the three basic modules two by two. To do this, we first completed the inference system in [2] so that the junctions of the three modules two by two become incorporated. A formal verification using this holistic inference system was proposed in a second step to prove the soundness and the completeness of these junctions. This verification's obtained results confirmed the validity of the said junctions for being sound and complete.

In Vehicular Ad hoc NETworks (VANETs), vehicles exchange safety related messages in order to improve the driving experience. However, it is not realistic to presume the absence of attackers intending to subvert the proper operation of the network. While message authentication enables the receiver to make sure of the received message's integrity and to verify its originator, it does not permit the verification of the message's credibility and accuracy. The main contribution of this paper is then the proposition of a scheme to assess the credibility and the accuracy of safety related messages exchanged in VANETs. Three modules constitute our proposal: a reputation module to evaluate the respective reputations of vehicles, a time and location closeness estimation module to judge the accuracy of a reported event and a majority module to decide the trueness of a received traffic information. These modules can be used in a separated or a combined way enabling a more flexibility in front of different circumstances confronted in VANETs. An in-depth security analysis is performed to demonstrate the efficiency of our proposal. Case studies that illustrate the different modules are also presented.

MANETs (Mobile Ad hoc Networks) are described assets of mobile nodes connected with wireless links. To be efficient, routing protocols in MANETs should, in fact, manage mobility, handle nodes energy dissipation and ensure security. We argue in this paper that trust negotiation is appropriate in such context to enhance the network performances. Trust concept is of concern to communication and network protocol designers. Thus, building trust relationships among participating nodes is critical to enabling collaborative optimization of system metrics. The main contribution of this paper is an extension of our previous proposition DTMCA (Delegation Trust Mobility-based Clustering Approach) which defines a new clustering approach, a trust management process and a delegation process. This environment allows the localization and the isolation of malicious nodes in MANETs. The extension proposed in this paper extends the trust management process by adding a trust negotiation module used in order to minimize the risk that malicious nodes join the MANETs.

Recently, we proposed a reputation based trust management scheme built upon a Mobility-based Clustering Approach (MCA) organizing Mobile Ad hoc Network MANET and detecting and isolating malicious behaviors. The whole scheme was called TMCA (Trust based MCA) and was extended in a second time with a delegation process resulting a proposition baptized DTMCA (Delegation TMCA based process). However, deploying such scheme is error prone and it appears necessary to validate it before its real implementation. In fact, scheme specification and validation constitute two fundamental challenges in the development of secure communication systems ensuring that the scheme is correctly enforced and complete. Hence, the main contribution of this paper concerns a validation framework for DTMCA scheme. The first step towards validation process is its formal specification. This is our first concern in this paper: a formal specification language called SCMSL (Secured Clustered MANET Specification Language) defined through a syntax based on authorization and obligation rules and a clear semantics. The second part of this paper proves the two major characteristics that must be guaranteed in such case: consistency and completeness. Consistency is proved by showing that there is no conflict in our scheme whereas completeness is proved by assessing that all potential situations are handled. The proof of consistency and completeness is made using automated systems through the definition of adequate algorithms.

MANETs (Mobile Ad hoc Networks) are self organized networks with mobile and collaborating nodes without any pre-established infrastructure. Because of these characteristics, securing MANETs constitute a hard and challenging task. Consequently, new mechanisms may be of interest to secure such networks. To this end, we have found that trust management can be a support for MANET security. In fact, the reputation concept and the establishment of trustful relation between collaborating nodes can be meaningful to express security aspects in such environment. From there, we proposed in previous works a Mobility-based Clustering Algorithm (MCA) and a Trust management scheme for MCA (TMCA) to secure routing behaviors. MCA organizes nodes into clusters managed by a cluster-head (CH) and TMCA detects malicious routing behavior based on CHs direct observations and exchanged alerts. A delegation based process was also defined on TMCA and was called DTMCA. Although DTMCA meets security objectives, it may unfortunately be faced with various threats from malicious nodes: Several nodes can in fact collude in order to increase or decrease other reputation values to damage the QoS and even the MANET functioning. Our objective in this paper is then to secure DTMCA against collusion attacks. The mechanism proposed here is based on colluding nodes detection through cluster members behavior monitoring and by comparing this behavior with the received reputation value in the alert message. Detected colluder nodes are then discarded from further communication.

A Mobile Ad hoc NETwork (MANET) is a collection of mobile nodes having no fixed topology and cooperating with each other. Due to these particularities, classical routing protocols cannot be used and some specific ones have been proposed. Because routing process is fundamental in a MANET deployment, it constitutes a privileged target of attackers. In this paper we propose a novel reputation-based clustering mechanism to locate malicious nodes and isolate them. In order to reduce network overhead and to handle network topology dynamicity, the proposed mechanism is based on a specific clustering environment. The clustering maintenance complexity is for its part reduced by the use of a reputation based delegation process allowing the cluster-head to delegate its privileges to a chosen cluster member in case of displacement or lack of energy. Moreover, node's reputation handling allows the detection and isolation of malicious nodes. Five modules constitute this mechanism: a monitoring module to detect malicious nodes, a reputation module to update reputation values, an isolation module to discard malicious nodes, an identity recognition module to assess alerts sources and a delegation module to allow clusterhead privileges delegation.