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Command injection and replay attacks are key threats in Cyber Physical Systems (CPS). We develop a novel actuator fingerprinting technique named Time Constant. Time Constant captures the transient dynamics of an actuator and physical process. The transient behavior is device-specific. We combine process and device transient characteristics to develop a copy-resistant actuator fingerprint that resists command injection and replay attacks in the face of insider adversaries. We validated the proposed scheme on data from a real water treatment testbed, as well as through real-time attack detection in the live plant. Our results show that we can uniquely distinguish between process states and actuators based on their Time Constant.

We study a binary mixture of disk-shaped {\it active run and tumble } particles (${ARNPs}$) and passive particles on a two-dimensional substrate. Both types of particles are athermal. The particles interact through the soft repulsive potential. The activity of $ARNPs$ is controlled by tuning their tumbling rate. The system is studied for various sizes of passive particles keeping size of $ARNPs$ fixed. Hence the variables are, size ratio (S) of passive particles and $ARNPs$, and activity of $ARNPs$ is $v$. The characterstics dynamics of both $ARNPs$ and passive particles show a crossover from early time ballistic to later time diffusive. Furthermore, we observed that passive particles dynamics changes from diffusive to subdiffusive with respect to their size. Moreover, late time effective diffusivity $D_{eff}$ of passive particles decreases with increasing their size as in the corresponding equilibrium Stokes systems. We calculated the effective temperatures, using $D_{eff}$, $T_{a,eff}(\Delta)$ and also using speed distribution $T_{a,eff}(v)$ and compared them. The both $T_{a,eff}(\Delta)$ and $T_{a,eff}(v)$ increases linearly with activity and are in agreement with each other. Hence we can say that an effective equilibrium can be establish in such binary mixture. Our study can be useful to study the various biological systems like; dynamics of passive organels in cytoplasm, colloids etc.

In an Industrial Control System (ICS), its complex network of sensors, actuators and controllers have raised security concerns for critical infrastructures and industrial production units. This opinion paper strives to initiate discussion on the design algorithms which can segregate attacks from faults. Most of the proposed anomaly detection mechanisms are not able to differentiate between an attack and an anomaly due to a fault. We argue on the need of solving this important problem form our experiences in CPS security research. First, we motivate using analysis of studies and interviews though economical and psychological aspects. Then main challenges are highlighted. Further, we propose multiple directions of approach with suitable reasoning and examples from ICS systems.

The number of active users of Wi-Fi Direct Device-to-Device file sharing applications on Android has exceeded 1.8 billion. Wi-Fi Direct, also known as Wi-Fi P2P, is commonly used for peer-to-peer, high-speed file transfer between mobile devices, as well as a close proximity connection mode for wireless cameras, network printers, TVs and other IoT and mobile devices. For its end users, such type of direct file transfer does not incur cellular data charges. However, despite the popularity of such applications, we observe that the software vendors tend to prioritize the ease of user flow over the security in their implementations, which leads to serious security flaws. We perform a comprehensive security analysis in the context of security and usability and report our findings in the form of 17 Common Vulnerabilities and Exposures (CVE) which have been disclosed to the corresponding vendors. To address the similar flaws at the early stage of the application design, we propose a joint consideration of security and usability for such applications and their protocols that can be visualized in form of a customised User Journey Map (UJM).

Direct-sequence spread spectrum (DSSS) has been recognized as an effective jamming resilient technique. However, the effectiveness of DSSS relies on the use of either pre-shared unique secret keys or a bank of public codes, which can be prohibitively expensive in future large-scale decentralized wireless networks, e.g., the Internet of Things. To tackle this problem, in this work we develop a new framework for self-controlled physical-layer-security-based spreading sequence generation. Specifically, we exploit the shared randomness inherent in wireless channels to generate and refresh secret seeds at each communicating node using shared randomness extraction, entropy pooling and random seed generation. The generated secret seeds are then utilized to perform DSSS. To evaluate the performance, we implement our framework on software defined radio platform and examine the successful transmission probability of the system under various models of broadband jamming along with an special case wherein adversary is assumed to have leaked information on key rate. Both our analysis and real-world measurements confirm that communication systems based on our framework can achieve jamming-resilient communications without requiring pre-shared sequences.