Cyber-Physical Security for IoT Systems

The advanced technology of vehicles makes them vulnerable to external exploitation. The current trend of research is to impose security measures to protect vehicles from different aspects. One of the main problems that counter Intrusion Detection Systems (IDSs) is the necessity to have a low false acceptance rate (FA) with high detection accuracy without major changes in the vehicle network infrastructure. Furthermore, the location of IDSs can be controversial due to the limitations and concerns of Electronic Control Units (ECUs). Thus, we propose a novel framework of multistage to detect abnormality in vehicle diagnostic data based on specifications of diagnostics and stacking ensemble for various machine learning models. The proposed framework is verified against the KIA SOUL and Seat Leon 2018 datasets. Our IDS is evaluated against point anomaly attacks and period anomaly attacks that have not been used in its training. The results show the superiority of the framework and its robustness with high accuracy of 99.21%, a low false acceptance rate of 0.003%, and a good detection rate (DR) of 99.63% for Seat Leon 2018, and an accuracy of 99.22%, a low false acceptance rate of 0.005%, and good detection rate of 98.59% for KIA SOUL. Full article

This paper proposes a modified sensor measurement expression for a moving target defense (MTD) strategy to detect coordinated cyber-physical attacks (CCPAs). Essentially, the MTD defense characteristics for detecting false data injection attacks (FDIAs) differ from those used to detect CCPAs. In the first case, the MTD performance in detecting FDIAs at the attack-execution stage is mainly considered, which is generally denoted by the detection probability; however, whether the construction of undetectable CCPAs is disrupted via the MTD strategy used during the attack-preparation stage is the focus of the latter case. There has been little work on the detection of undetectable CCPAs in the context of MTD post-activation. In our work, a novel approach to detecting undetectable CCPAs via a modified sensor measurement expression is proposed. First, the production mechanism for undetectable CCPAs without the application of an MTD strategy is transferred to that which occurs after MTD activation; then, based on an in-depth analysis of the CCPAs’ production mechanism after MTD activation, a novel modified sensor measurement expression is presented to detect undetectable CCPAs. Extensive simulations were conducted on three standard power systems to verify the effectiveness and simplicity of our approach to detecting CCPAs. Full article

Cluster formation and task processing are standard features for leveraging the performance of unmanned aerial vehicles (UAVs). As the UAV network is aided by sensors, functions such as clustering, reformation, and autonomous working are adaptively used for dense task processing. In consideration of the distributed nature of the UAV network coupled with wireless sensors, this article introduces a Rational Clustering Method (RCM) using dense task neighbor information exchange. The Rational Clustering Method (RCM) is an algorithm for dense task neighbor information exchange that can be used to cluster objects according to their shared properties. Each object’s task neighbors, and the similarities between them, are calculated using this method. Starting with the task density of its neighbors, the RCM algorithm gives each object in the dataset a weight. This information exchange process identifies a UAV units’ completing tasks and free slots. Using this information, high-slot UAVs within the communication range can be grouped as clusters. Unlike wireless sensor clusters, task allocation is performed on the basis of available slots and UAV longevity within the cluster; this prevents task incompletion/failures and delays in a densely populated UAV scenario. Cluster sustainability or dispersion is recommended when using distributed state learning. State learning transits between the pending task and UAV longevity; an intermediate state is defined for task reassignment amid immediate cluster deformation. This triple feature-based distributed method balances tasks between failures, overloading, and idle UAVs. The RCM was verified using task processing rate, completion ratio, reassignment, failures, and delay. Task processing rate was increased by 8.16% and completion ratio was increased by 10.3% with the proposed RCM-IE. Reassignment, failure, and delay were all reduced by 12.5%, 9.87%, and 11.99%, respectively, using this method. Full article

Cyber–physical systems (CPSs) are a new generation of intelligent system that integrate communication, control and computation functions and are widely used in traditional infrastructure networks, such as power network, transportation network and others. In order to ensure the stable operation and improve the robustness of CPSs, the studies of robustness assessment have attracted much attention from academia. However, previous models assume that the failure propagation conforms to a strongly interdependent relationship, and only consider the interaction between nodes, while ignoring the interaction between nodes and links. In this paper, we develop a novel simulation model with the consideration of both the coupling modes and the failure propagation objects. Based on the simulation model, we study how the interdependent mechanisms, failure propagation probability and protection strategies affect the robustness of CPSs. The simulations of our proposed model are demonstrated in a test CPS formed by coupling two classical complex networks. Compared with previous models, our proposed model shows different performances and comprehensively characterizes the interdependent relationship of CPSs. In detail, disassortative coupling shows the worst performance and the CPS becomes more sensitive to failure propagation when Node–Link is selected as the failure propagation object. In addition, compared to the communication network, the power network is more sensitive to failure propagation. Protecting electrical nodes is a more effective way to strengthen the robustness of CPSs when conservation resources are limited. Our work provides useful advice to operators on how to effectively design and protect a CPS. Full article

Stealthy attacks in sensor and actuator loops are the research priorities in the security of cyber-physical systems. Existing attacks define the stealthiness conditions against the Chi-square or Kullback-Leibler divergence detectors and parameterize the attack model based on additive signals. Such conditions ignore the potential anomalies of the vulnerable outputs in the control layer, and the attack sequences need to be generated online, increasing the hardware and software costs. This paper investigates a type of multiplicative attack with essential stealthiness where the employed model is a novel form. The advantage is that the parameters can be designed in a constant form without having to be generated online. An essential stealthiness condition is proposed for the first time and complements the existing ones. Two sufficient conditions for the existence of constant attack matrices are given in the form of theorems, where two methods for decoupling the unknown variables are particularly considered. A quadruple-tank process, an experimental platform for attack and defense, is developed to verify the theoretical results. The experiments indicate that the proposed attack strategy can fulfill both the attack performance and stealthiness conditions. Full article