Biblio

We consider the problem of security for unmanned aerial vehicle flight control systems. To provide a concrete setting, we consider the security problem in the context of a helicopter which is compromised by a malicious agent that distorts elevation measurements to the control loop. This is a particular example of the problem of the security of stochastic control systems under erroneous observation measurements caused by malicious sensors within the system. In order to secure the control system, we consider dynamic watermarking, where a private random excitation signal is superimposed onto the control input of the flight control system. An attack detector at the actuator can then check if the reported sensor measurements are appropriately correlated with the private random excitation signal. This is done via two specific statistical tests whose violation signifies an attack. We apply dynamic watermarking technique to a 2-rotor-based 3-DOF helicopter control system test-bed. We demonstrate through both simulation and experimental results the performance of the attack detector on two attack models: a stealth attack, and a random bias injection attack.

Security maintenance of Supervisory Control and Data Acquisition (SCADA) systems has been a point of interest during recent years. Numerous research works have been dedicated to the design of intrusion detection systems for securing SCADA communications. Nevertheless, these data-driven techniques are usually dependant on the quality of the monitored data. In this work, we propose a novel feature selection approach, called MSFS, to tackle undesirable quality of data caused by feature redundancy. In contrast to most feature selection techniques, the proposed method models each class in a different subspace, where it is optimally discriminated. This has been accomplished by resorting to ensemble learning, which enables the usage of multiple feature sets in the same feature space. The proposed method is then utilized to perform intrusion detection in smaller subspaces, which brings about efficiency and accuracy. Moreover, a comparative study is performed on a number of advanced feature selection algorithms. Furthermore, a dataset obtained from the SCADA system of a gas pipeline is employed to enable a realistic simulation. The results indicate the proposed approach extensively improves the detection performance in terms of classification accuracy and standard deviation.

The paper discusses the use of virtual (VR) and augmented (AR) reality for visual analytics in information security. Paper answers two questions: “In which areas of information security visualization VR/AR can be useful?” and “What is the difference of the VR/AR from similar methods of visualization at the level of perception of information?”. The first answer is based on the investigation of information security areas and visualization models that can be used in VR/AR security visualization. The second answer is based on experiments that evaluate perception of visual components in VR.

Notions like security, trust, and privacy are crucial in the digital environment and in the future, with the advent of technologies like the Internet of Things (IoT) and Cyber-Physical Systems (CPS), their importance is only going to increase. Trust has different definitions, some situations rely on real-world relationships between entities while others depend on robust technologies to gain trust after deployment. In this paper we focus on these robust technologies, their evolution in past decades and their scope in the near future. The evolution of robust trust technologies has involved diverse approaches, as a consequence trust is defined, understood and ascertained differently across heterogeneous domains and technologies. In this paper we look at digital trust technologies from the point of view of security and examine how they are making secure computing an attainable reality. The paper also revisits and analyses the Trusted Platform Module (TPM), Secure Elements (SE), Hypervisors and Virtualisation, Intel TXT, Trusted Execution Environments (TEE) like GlobalPlatform TEE, Intel SGX, along with Host Card Emulation, and Encrypted Execution Environment (E3). In our analysis we focus on these technologies and their application to the emerging domains of the IoT and CPS.

Cyber-physical systems (CPS) can potentially benefit a wide array of applications and areas. Here, the authors look at some of the challenges surrounding CPS, and consider a feasible solution for creating a robust, secure, and cost-effective architecture.

A key question that arises in rigorous analysis of cyberphysical systems under attack involves establishing whether or not the attacked system deviates significantly from the ideal allowed behavior. This is the problem of deciding whether or not the ideal system is an abstraction of the attacked system. A quantitative variation of this question can capture how much the attacked system deviates from the ideal. Thus, algorithms for deciding abstraction relations can help measure the effect of attacks on cyberphysical systems and to develop attack detection strategies. In this paper, we present a decision procedure for proving that one nonlinear dynamical system is a quantitative abstraction of another. Directly computing the reach sets of these nonlinear systems are undecidable in general and reach set over-approximations do not give a direct way for proving abstraction. Our procedure uses (possibly inaccurate) numerical simulations and a model annotation to compute tight approximations of the observable behaviors of the system and then uses these approximations to decide on abstraction. We show that the procedure is sound and that it is guaranteed to terminate under reasonable robustness assumptions.