STPA-SafeSec: Safety and Security Analysis for Cyber-Physical Systems

Cyber-physical systems tightly integrate physical processes and information and communication technologies. As today’s critical infrastructures, e.g., the power grid or water distribution networks, are complex cyber-physical systems, ensuring their safety and security becomes of paramount importance. Traditional safety analysis methods, such as HAZOP, are ill-suited to assess these systems. Furthermore, cybersecurity vulnerabilities are often not considered critical, because their effects on the physical processes are not fully understood. In this work, we present STPA-SafeSec, a novel analysis methodology for both safety and security. Its results show the dependencies between cybersecurity vulnerabilities and system safety. Using this information, the most effective mitigation strategies to ensure safety and security of the system can be readily identified. We apply STPA-SafeSec to a use case in the power grid domain, and highlight its benefits.

Dynamically mechanical and nano-impact (fatigue) analysis of touch screen thin films deposited on polyethylene terephthalate substrate

Nano-scale touch screen thin film have not been thoroughly investigated in terms of dynamic impact analysis under various strain rates. This research is focused on two different thin films, Zinc Oxide (ZnO) film and Indium Tin Oxide (ITO) film, deposited on Polyethylene Terephthalate (PET) substrate for the standard touch screen panels. Dynamic Mechanical Analysis (DMA) was performed on the ZnO film coated PET substrates. Nano-impact (fatigue) testing was performed on ITO film coated PET substrates. Other analysis includes hardness and the elastic modulus measurements, atomic force microscopy (AFM), Fourier Transform Infrared Spectroscopy (FTIR) and the Scanning Electron Microscopy (SEM) of the film surface.
Ten delta of DMA is described as the ratio of loss modulus (viscous properties) and storage modulus (elastic properties) of the material and its peak against time identifies the glass transition temperature (Tg). Thus, in essence the Tg recognizes changes from glassy to rubber state of the material and for our sample ZnO film, Tg was found as 388.3 K. The DMA results also showed that the Ten delta curve for Tg increases monotonically in the viscoelastic state (before Tg) and decreases sharply in the rubber state (after Tg) until recrystallization of ZnO takes place. This led to an interpretation that enhanced ductility can be achieved by negating the strength of the material.
For the nano-impact testing using the ITO coated PET, the damage started with the crack initiation and propagation. The interpretation of the nano-impact results depended on the characteristics of the loading history. Under the nano-impact loading, the surface structure of ITO film suffered from several forms of failure damages that range from deformation to catastrophic failures. It is concluded that in such type of application, the films should have low residual stress to prevent deformation, good adhesive strength, durable and good resistance to wear.

Dynalog: an automated dynamic analysis framework for characterizing android applications

Android is becoming ubiquitous and currently has the largest share of the mobile OS market with billions of application downloads from the official app market. It has also become the platform most targeted by mobile malware that are becoming more sophisticated to evade state-of-the-art detection approaches. Many Android malware families employ obfuscation techniques in order to avoid detection and this may defeat static analysis based approaches. Dynamic analysis on the other hand may be used to overcome this limitation. Hence in this paper we propose DynaLog, a dynamic analysis based framework for characterizing Android applications. The framework provides the capability to analyse the behaviour of applications based on an extensive number of dynamic features. It provides an automated platform for mass analysis and characterization of apps that is useful for quickly identifying and isolating malicious applications. The DynaLog framework leverages existing open source tools to extract and log high level behaviours, API calls, and critical events that can be used to explore the characteristics of an application, thus providing an extensible dynamic analysis platform for detecting Android malware. DynaLog is evaluated using real malware samples and clean applications demonstrating its capabilities for effective analysis and detection of malicious applications.

Identification of Microturbine Model for Long-term Dynamic Analysis of Distribution Networks

As one of the most successfully commercialized distributed energy resources, the long-term effects of microturbines (MTs) on the distribution network has not been fully investigated due to the complex thermo-fluid-mechanical energy conversion processes. This is further complicated by the fact that the parameter and internal data of MTs are not always available to the electric utility, due to different ownerships and confidentiality concerns. To address this issue, a general modeling approach for MTs is proposed in this paper, which allows for the long-term simulation of the distribution network with multiple MTs. First, the feasibility of deriving a simplified MT model for long-term dynamic analysis of the distribution network is discussed, based on the physical understanding of dynamic processes that occurred within MTs. Then a three-stage identification method is developed in order to obtain a piecewise MT model and predict electro-mechanical system behaviors with saturation. Next, assisted with the electric power flow calculation tool, a fast simulation methodology is proposed to evaluate the long-term impact of multiple MTs on the distribution network. Finally, the model is verified by using Capstone C30 microturbine experiments, and further applied to the dynamic simulation of a modified IEEE 37-node test feeder with promising results.