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Cooperative Intelligent Transportation Systems (C-ITS) are gaining ground and currently are almost part of our everyday life. A C-ITS environment can provide numerous services that soon will become essential to roads’ users. The latter resides in improvement of road safety, entertainment, and commercial services. However, in order to provide such services, the C-ITS environment needs an advertisement and dissemination service for them. Indeed, users have to be aware of the available services in order to request them if needed. Current standards of service announcement show their limits, especially regarding the interoperability between communication profiles. For this reason, in this paper, we describes our new service advertisement solution called CAM-Infrastructure. The latter is compliant with ETSI standards and is deployed in SCOOP@F, a nationwide scale project.

International audience; Collaborative Intelligent Transportation Systems are almost part of our everyday life. A C-ITS environment can provide numerous services that soon will become essential to roads’ users. The latter resides in improvement of road safety, entertainment, and commercial services. However to provide such services, the C-ITS environment needs an advertisement and dissemination service of the latter. Indeed, users have to be aware of the available services in order to request them if needed. Actual standards of service announcement show their limits, especially regarding the support of several communication profiles. For this reason, this paper, describes a new service advertisement message called CAM-Infrastructure. The latter is compliant with ETSI standards and is deployed in a nationwide scale project.

Since the last years, cloud computing is playing an important role in providing high quality of IT services. However, beyond a legitimate usage, the numerous advantages it presents are now exploited by attackers, and botnets supporting DDoS attacks are among the greatest beneficiaries of this malicious use. In this paper, we present an original approach that enables a collaborative egress detection of DDoS attacks leveraged by a botcloud. We provide an early evaluation of our approach using simulations that rely on real workload traces, showing our detection system effectiveness and low overhead, as well as its support for incremental deployment in real cloud infrastructures.

Part 4: Experimental Studies for Security Management; International audience; Cloud computing security is often focused on data and users security and protection against external intrusions. However, it exists an area of cloud security that is often overlooked and that can have disastrous consequences: the conversion of cloud computing into an attack vector. Beyond a legitimate usage, the numerous advantages of cloud computing are exploited by attackers. Botnets supporting Distributed Denial of Service (DDoS) attacks are among the greatest beneficiaries of this malicious use. In this paper, we propose a novel source-based detection approach that aims at detecting the abnormal virtual machines behavior. The originality of our approach resides in (1) relying only on the system’s metrics of virtual machines and (2) considering a source-based detection. Our approach is based on Principal Component Analysis to detect anomalies that can be signs of botcloud’s behavior supporting DDoS flooding attacks. We also present the results of the evaluation of our detection algorithm.

Cloud computing is gaining ground and becoming one of the fast growing segments of the IT industry. However, if its numerous advantages are mainly used to support a legitimate activity, it is now exploited for a use it was not meant for: malicious users leverage its power and fast provisioning to turn it into an attack support. Botnets supporting DDoS attacks are among the greatest beneficiaries of this malicious use since they can be setup on demand and at very large scale without requiring a long dissemination phase nor an expensive deployment costs. For cloud service providers, preventing their infrastructure from being turned into an Attack as a Service delivery model is very challenging since it requires detecting threats at the source, in a highly dynamic and heterogeneous environment. In this paper, we present the result of an experiment campaign we performed in order to understand the operational behavior of a botcloud used for a DDoS attack. The originality of our work resides in the consideration of system metrics that, while never considered for state-of-the-art botnets detection, can be leveraged in the context of a cloud to enable a source based detection. Our study considers both attacks based on TCP-flood and UDP-storm and for each of them, we provide statistical results based on a principal component analysis, that highlight the recognizable behavior of a botcloud as compared to other legitimate workloads.