Flying Ad hoc Network (FANET) is a new resource-constrained breed and instantiation of Mobile Ad hoc Network (MANET) employing Unmanned Aerial Vehicles (UAVs) as communicating nodes. These latter follow a predefined path called ’mission’ to provide a wide range of applications/services. Without loss of generality, the services and applications offered by the FANET are based on data/content delivery in various forms such as, but not limited to, pictures, video, status, warnings, and so on. Therefore, a content-centric communication mechanism such as Information Centric Networking (ICN) is essential for FANET. ICN addresses the problems of classical TCP/IP-based Internet. To this end, Content-centric networking (CCN), and Named Data Networking (NDN) are two of the most famous and widely-adapted implementations of ICN due to their intrinsic security mechanism and Interest/Data-based communication. To ensure data security, a signature on the contents is appended to each response/data packet in transit. However, trusted communication is of paramount importance and currently lacks in NDN-driven communication. To fill the gaps, in this paper, we propose a novel trust-aware Monitor-based communication architecture for Flying Named Data Networking (FNDN). We first select the monitors based on their trust and stability, which then become responsible for the interest packets dissemination to avoid broadcast storm problem. Once the interest reaches data producer, the data comes back to the requester through the shortest and most trusted path (which is also the same path through which the interest packet arrived at the producer). Simultaneously, the intermediate UAVs choose whether to check the data authenticity or not, following their subjective belief on its producer’s behavior and thus-forth reducing the computation complexity and delay. Simulation results show that our proposal can sustain the vanilla NDN security levels exceeding the 80% dishonesty detection ratio while reducing the generated end-to-end delay to less than 1 s in the worst case and reducing the average consumed energy by more than two times.

Named Data Networking (NDN) is a prominent realization of the vision of Information-Centric Networking. The NDN architecture adopts name-based routing and location-independent data retrieval. Among other important features, NDN integrates security mechanisms and focuses on protecting the content rather than the communications channels. Along with a new architecture come new threats, and NDN is no exception. NDN is a potential target for new network attacks such as Interest Flooding Attacks (IFAs). Attackers take advantage of IFA to launch (D)DoS attacks in NDN. Many IFA detection and mitigation solutions have been proposed in the literature. However, there is no comprehensive review study of these solutions that has been proposed so far. Therefore, in this article, we propose a survey of the various IFAs with a detailed comparative study of all the relevant proposed solutions as counter-measures against IFAs. We also review the requirements for a complete and efficient IFA solution and pinpoint the various issues encountered by IFA detection and mitigation mechanisms through a series of attack scenarios. Finally, in this survey, we offer an analysis of the open issues and future research directions regarding IFAs.

Vehicular cloud (VC) is a promising environment, where intelligent transport applications can be developed relying on mobile vehicles, which can be both cloud users and cloud service providers. It enables vehicles that have sufficient resources to act as mobile cloud servers by offering a variety of services to users' vehicles. In this context, to consume a cloud service on the move, a user vehicle must first identify the most stable vehicles, relative to his/her motion, which are able to provide the service, and then select the most suitable service according to his/her preferences, while both provider vehicles and their services are described by attributes or quality constraints. Therefore, we introduce a generic relative motion model, as a generic link stability metric, upon which vehicles can form a stable cloud, and we address the VC service selection by using linguistic quantifiers and fuzzy quantified propositions, to define our flexible quantified service selection (FQSS) scheme, which aggregates efficiently both user preferences and service constraints and ranks service providers from the most to the least satisfactory. To break ties among the top-ranked service providers, we make use of our parameters for ranking refinement, called least satisfactory proportion (lsp) and greatest satisfactory proportion (gsp). The simulation results show that our link stability achieves generic motion, by modeling a wider range of vehicle motion types, and our FQSS scheme allows a good successful service consumption rate while reducing latency.

By leveraging the conventional Vehicular Ad-hoc Networks (VANETs), the Internet of Vehicles (IoV) paradigm has attracted the attention of different research and development bodies. However, IoV deployment is still at stake as many security and privacy issues are looming; location tracking using overheard safety messages is a good example of such issues. In the context of location privacy, many schemes have been deployed to mitigate the adversary’s exploiting abilities. The most appealing schemes are those using the silent period feature, since they provide an acceptable level of privacy. Unfortunately, the cost of silent periods in most schemes is the trade-off between privacy and safety, as these schemes do not consider the timing of silent periods from the perspective of safety. In this paper, and by exploiting the nature of public transport and role vehicles (overseers), we propose a novel location privacy scheme, called OVR, that uses the silent period feature by letting the overseers ensure safety and allowing other vehicles to enter into silence mode, thus enhancing their location privacy. This scheme is inspired by the well-known war strategy “Give up a Pawn to Save a Chariot”. Additionally, the scheme does support road congestion estimation in real time by enabling the estimation locally on their On-Board Units that act as mobile edge servers and deliver these data to a static edge server that is implemented at the cell tower or road-side unit level, which boosts the connectivity and reduces network latencies. When OVR is compared with other schemes in urban and highway models, the overall results show its beneficial use.

Vehicular cloud is a promising paradigm in which mobile vehicles can be both cloud users and service providers. It enables vehicles that have sufficient resources to act as mobile cloud servers by offering a wide range of services to user's vehicles. However, user vehicles need to discover provider vehicles along with their services, and request targeted services from them, especially with the high mobility of vehicles. Moreover, provider vehicles and their services are characterized by specific quality criteria and consumer vehicles need to select the most suitable services. In this paper, we design a new protocol that enables vehicles to discover and consume services of mobile cloud servers that are moving nearby. The protocol harnesses public buses, which provide a stability in terms of time (regular timetables) and space (fixed lines in an urban area), making them act as cloud directories, where provider vehicles can register their services. Public buses spread service registration information to the buses within the same bus line, and to buses of connected lines, as well. A consumer vehicle can discover the available services, along with their constraints, by querying the buses in their vicinity. To ensure service consumption, the buses provide also a routing protocol allowing communication between the provider and the consumer. Furthermore, we extend our protocol to enable, on the one hand, vehicle providers to select the most appropriate public bus for an efficient service registration, and users to select, on the other hand, the most satisfactory service, which satisfies both provider constraints and user preferences. Simulation results showed the efficiency of our protocol in terms of service discovery and service consuming delays, as well as its ability to select both the most suitable cloud directory and service provider for both providers and consumers, respectively.