CYBER ATTACKS ON SCADA BASED TRAFFIC LIGHT CONTROL SYSTEMS IN THE SMART CITIES

There are regular developments and changes in cities. Developments in cities have affected transportation, and traffic control tools have changed. Traffic signs and traffic lights have been used to direct pedestrians and vehicles correctly. Traffic light control systems are used to ensure the safety of vehicles and pedestrians, increase the fluency in traffic, guide them in transportation, warn pedestrians and drivers, and regulate and control transportation disruptions. In order to facilitate people's lives, it is desired to control the traffic components autonomously with the developments in autonomous systems. Cyber threats arise due to the active use of the internet and signals or frequencies in the use of modules that will provide communication with traffic lights, traffic signs, and vehicles, which are traffic components at the inter-sections of many roads in the control of central systems. The study is limited to smart traffic lights, which are traffic components. If we examine the cyber-attacks, we can see that Malware Attacks, Buffer Overflow Attacks, DoS attacks, and Jamming Attacks can be made. Network-Based Intrusion Detection Systems and Host-Based Intrusion Detection Systems can be used to detect and stop Malware Attacks, Buffer Overflow Attacks, DoS attacks, and Jamming Attacks. Intrusion detection systems tell us whether the data poses a threat or does not pose after the data passing through the system is examined. In this way, system protection is ensured by controlling the data traffic in the system.

Distributed Event-Triggered Consensus Control of Multi-Agent Systems under Denial-of-Service Jamming Attacks

This work focuses on the consensus problem of multi-agent systems (MASs) under event-triggered control (ETC) subject to denial-of-service (DoS) jamming attacks. To reduce the cost of communication networks, a novel event-triggering mechanism (ETM) is applied to the sleeping interval to determine whether the sampled signal should be transmitted or not. Unlike periodic DoS attacks model, the DoS attacks occurrence are irregular, where attack attributes such as attack frequency and attack duration are taken into account. Moreover, compared with the fixed topological graph, the communication topologies may change due to DoS jamming attacks in this work. In view of this, based on the piecewise Lyapunov functional, sufficient conditions are derived to guarantee that consensus problem of the MASs can be solved. Finally, the effectiveness and correctness of the theoretical results are verified by a numerical example.

RF Jamming Classification Using Relative Speed Estimation in Vehicular Wireless Networks

Wireless communications are vulnerable against radio frequency (RF) interference which might be caused either intentionally or unintentionally. A particular subset of wireless networks, Vehicular Ad-hoc NETworks (VANET), which incorporate a series of safety-critical applications, may be a potential target of RF jamming with detrimental safety effects. To ensure secure communications between entities and in order to make the network robust against this type of attacks, an accurate detection scheme must be adopted. In this paper, we introduce a detection scheme that is based on supervised learning. The k-nearest neighbors (KNN) and random forest (RaFo) methods are used, including features, among which one is the metric of the variations of relative speed (VRS) between the jammer and the receiver. VRS is estimated from the combined value of the useful and the jamming signal at the receiver. The KNN-VRS and RaFo-VRS classification algorithms are able to detect various cases of denial-of-service (DoS) RF jamming attacks and differentiate those attacks from cases of interference with very high accuracy.