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The increasing connectivity of restricted areas suchas Critical Infrastructures (CIs) raises major security concernsfor Supervisory Control And Data Acquisition (SCADA) systems,which are deployed to monitor their operation. Given the impor-tance of an early anomaly detection, Intrusion Detection Systems(IDSs) are introduced in SCADA systems to detect malicious ac-tivities as early as possible. Agents or probes form the cornerstoneof any IDS by capturing network packets and extracting relevantinformation. However, IDSs are facing unprecedented challengesdue to the escalation in the number, scale and diversity of attacks.Software-Defined Network (SDN) then comes into play and canprovide the required flexibility and scalability. Building on that,we introduce Traffic Agent Controllers (TACs) that monitor SDN-enabled switches via OpenFlow. By using lightweight statisticalmetrics such as Kullback-Leibler Divergence (KLD), we are ableto detect the slightest anomalies, such as stealth port scans, evenin the presence of background traffic. The obtained metrics canalso be used to locate the anomalies with precision over 90%inside a hierarchical network topology.

Automotive Ethernet (AE) is becoming more and more relevant to the automotive industry due to its support of emerging in-car applications, which have high bandwidth demands and stringent requirements in terms of latency and time synchronization. One of the standards under consideration for AE is IEEE 802.1 Audio Video Bridging (AVB)/Time Sensitive Networking (TSN) that provides deterministic data link layer and bounded latency to real-time traffic classes. So far, this protocol stack has only been evaluated using either simulations or proprietary and expensive platforms. In this paper, we design a real testbed system for AE using general-purpose single-board computers and conduct experiments to assess the real-time performance of an open-source AVB/TSN implementation. Our preliminary results show that even under heavy load, AVB/TSN can fulfil the latency requirements of AE while keeping a constant latency variation.

Beaconing is a basic communication process taking place in Vehicular Ad Hoc Networks (VANETs) to achieve cooperative awareness among vehicles on the road. It is actually a paradigm of information spreading among peer-agents, where each node of a networks sends periodically broadcast messages containing information collected by the node itself. A trade-off arises between the update frequency of the broadcast information and the congestion induced in the wireless shared channel used to send the messages, which is based on the IEEE 802.11p standard in case of a VANET. For periodic updates, the primary metric is the Age-of-Information (AoI), i.e., the age of the latest update received by neighboring nodes. We define an analytical model to evaluate the AoI of a VANET, given the connectivity graph of the vehicles. Analytical results are compared to simulation to assess the accuracy of the model. The model provides a handy tool to optimize the AoI trade-off.

In the current Intelligent Transportation Systems (ITS) traffic monitoring and incident detection are usually supported with mostly traditional and relatively slow reactivity technologies. In this paper we propose a new service, namely THOR (Traffic monitoring Hybrid ORiented service), able to combine two different wireless technologies and to provide real time information about vehicular traffic monitoring and incident detection. THOR relies on LTE (Long Term Evolution) and Dedicated Short Range Communication based VANETs (Vehicular ad-hoc NETworks) in a hybrid approach, which is compliant with ITS standards. This hybrid networking approach can be deployed today and can be ready for tomorrow VANET technology. We test THOR by simulations in a scenario with vehicle flows synthesized from real measured vehicular traffic traces. We provide an LTE load analysis and an assessment of incident detection capabilities. Our results are promising in terms of reactivity, precision and network traffic load sustainability.

Periodical collection of data from vehicles inside a target area is of interest for many applications in the context of Intelligent Transportation Systems (ITS). Long Term Evolution (LTE) has been identified as a good candidate technology for supporting such type of applications - particularly for the non-safety domain. However, a high number of vehicles intermittently reporting their information via LTE can introduce a very high load on the LTE access network. In this context, the use of heterogeneous networking technologies can yield significant offloading of LTE - here, WLAN and Dedicated Short-Range Communication (DSRC) technology can support local data aggregation. In this paper, we propose an on-the-fly distributed clustering algorithm that uses both LTE and DSRC networks in the forwarder selection process. Our results clearly indicate that it is crucial to consider parameters drawn from both networking platforms for selecting the right forwarders. In particular, we show for the first time that relying on the Channel Quality Indicator (CQI) has a substantial impact. We demonstrate that our solution is able to significantly reduce the LTE channel utilization with respect to other state of the art approaches.

Floating Car Data (FCD) applications are based on the collection of geo-localized information updates that are issued by vehicles roaming in a given area. These data are an essential source for traffic information and are widely employed by Intelligent Transportation Systems (ITS). We present and examine a hybrid networking architecture and protocol that are used for the efficient execution of such a collection process. We employ a VANET-based multihop dissemination logic to spread control messages and elect designated nodes. Those nodes are exploited to report vehicular data via LTE communications. The performance behavior of the proposed protocol is evaluated through the consideration of two real urban scenarios. In comparing with performance bounds that characterize the performance behavior attained by state-of-theart hybrid integrated VANET and LTE mechanisms, we show our approach to offer a substantial reduction in the traffic load rates induced over the LTE cellular radio access system.

Message dissemination and data collection from vehicles are two key enablers of Intelligent Transportation System services that can be offered by a Vehicular Ad-Hoc Network (VANET) technology. In this work we propose a fully distributed protocol for dissemination of query and collection of reply messages carrying information gathered from vehicles moving in a given target area, in an urban scenario. The key idea is to use the dissemination phase (forward wave) to create a network of relay nodes that are in charge of delivering reply messages back to the originating point (reverse wave). The proposed protocol is evaluated with reference to two real urban environments. Main parameters are dimensioned and an insight in the protocol working is given.