Statistical Watermarking for Networked Control Systems

Watermarking can detect sensor attacks in control systems by injecting a private signal into the control, whereby attacks are identified by checking the statistics of the sensor measurements and private signal. However, past approaches assume full state measurements or a centralized controller, which is not found in networked LTI systems with subcontrollers. Since generally the entire system is neither controllable nor observable by a single subcontroller, communication of sensor measurements is required to ensure closed-loop stability. The possibility of attacking the communication channel has not been explicitly considered by previous watermarking schemes, and requires a new design. In this paper, we derive a statistical watermarking test that can detect both sensor and communication attacks. A unique (compared to the non-networked case) aspect of the implementing this test is the state-feedback controller must be designed so that the closed-loop system is controllable by each sub-controller, and we provide two approaches to design such a controller using Heymann's lemma and a multi-input generalization of Heymann's lemma. The usefulness of our approach is demonstrated with a simulation of detecting attacks in a platoon of autonomous vehicles. Our test allows each vehicle to independently detect attacks on both the communication channel between vehicles and on the sensor measurements

Fast Sequence Component Analysis for Attack Detection in Synchrophasor Networks

Modern power systems have begun integrating synchrophasor technologies into part of daily operations. Given the amount of solutions offered and the maturity rate of application development it is not a matter of "if" but a matter of "when" in regards to these technologies becoming ubiquitous in control centers around the world. While the benefits are numerous, the functionality of operator-level applications can easily be nullified by injection of deceptive data signals disguised as genuine measurements. Such deceptive action is a common precursor to nefarious, often malicious activity. A correlation coefficient characterization and machine learning methodology are proposed to detect and identify injection of spoofed data signals. The proposed method utilizes statistical relationships intrinsic to power system parameters, which are quantified and presented. Several spoofing schemes have been developed to qualitatively and quantitatively demonstrate detection capabilities.Comment: 8 pages, 4 figures, submitted to IEEE Transaction

Deep Learning Applications in Industrial and Systems Engineering

Deep learning - the use of large neural networks to perform machine learning - has transformed the world. As the capabilities of deep models continue to grow, deep learning is becoming an increasingly valuable and practical tool for industrial engineering. With its wide applicability, deep learning can be turned to many industrial engineering tasks, including optimization, heuristic search, and functional approximation. In this dissertation, the major concepts and paradigms of deep learning are reviewed, and three industrial engineering projects applying these methods are described. The first applies a deep convolutional network to the task of absolute aerial geolocalization - the regression of real geographic coordinates from aerial photos - showing promising results. Next, continuing on this work, the features and characteristics of the deep aerial geolocalization model are further studied, with implications for future applications and methodological improvements. Lastly, a deep learning model is developed and applied to a difficult rare event problem of predicting failure times in oil and natural gas wells from process and site data. Practical details of applying deep learning to this sort of data are discussed, and methodological principles are proposed

Hardware-Based Authentication for the Internet of Things

Entity authentication is one of the most fundamental problems in computer security. Implementation of any authentication protocol requires the solution of several sub-problems, such as the problems regarding secret sharing, key generation, key storage and key verification. With the advent of the Internet-of-Things(IoT), authentication becomes a pivotal concern in the security of IoT systems. Interconnected components of IoT devices normally contains sensors, actuators, relays, and processing and control equipment that are designed with the limited budget on power, cost and area. As a result, incorporating security protocols in such resource constrained IoT components can be rather challenging. To address this issue, in this dissertation, we design and develop hardware oriented lightweight protocols for the authentication of users, devices and data. These protocols utilize physical properties of memory components, computing units, and hardware clocks on the IoT device. Recent works on device authentication using physically uncloneable functions can render the problem of entity authentication and verification based on the hardware properties tractable. Our studies reveal that non-linear characteristics of resistive memories can be useful in solving several problems regarding authentication. Therefore, in this dissertation, first we explore the ideas of secret sharing using threshold circuits and non-volatile memory components. Inspired by the concepts of visual cryptography, we identify the promises of resistive memory based circuits in lightweight secret sharing and multi-user authentication. Furthermore, the additive and monotonic properties of non-volatile memory components can be useful in addressing the challenges of key storage. Overall, in the first part of this dissertation, we present our research on design of low-cost, non-crypto based user authentication schemes using physical properties of a resistive memory based system. In the second part of the dissertation, we demonstrate that in computational units, the emerging voltage over-scaling (VOS)-based computing leaves a process variation dependent error signature in the approximate results. Current research works in VOS focus on reducing these errors to provide acceptable results from the computation point of view. Interestingly, with extreme VOS, these errors can also reveal significant information about the underlying physical system and random variations therein. As a result, these errors can be methodically profiled to extract information about the process variation in a computational unit. Therefore, in this dissertation, we also employ error profiling techniques along with the basic key-based authentication schemes to create lightweight device authentication protocols. Finally, intrinsic properties of hardware clocks can provide novel ways of device fingerprinting and authentication. The clock signatures can be used for real-time authentication of electromagnetic signals where some temporal properties of the signal are known. In the last part of this dissertation, we elaborate our studies on data authentication using hardware clocks. As an example, we propose a GPS signature authentication and spoofing detection technique using physical properties such as the frequency skew and drift of hardware clocks in GPS receivers

Detection and Mitigation of Cyber Attacks on Time Synchronization Protocols for the Smart Grid

The current electric grid is considered as one of the greatest engineering achievements of the twentieth century. It has been successful in delivering power to consumers for decades. Nevertheless, the electric grid has recently experienced several blackouts that raised several concerns related to its availability and reliability. The aspiration to provide reliable and efficient energy, and contribute to environment protection through the increasing utilization of renewable energies are driving the need to deploy the grid of the future, the smart grid. It is expected that this grid will be self-healing from power disturbance events, operating resiliently against physical and cyber attack, operating efficiently, and enabling new products and services. All these call for a grid with more Information and Communication Technologies (ICT). As such, power grids are increasingly absorbing ICT technologies to provide efficient, secure and reliable two-way communication to better manage, operate, maintain and control electric grid components. On the other hand, the successful deployment of the smart grid is predicated on the ability to secure its operations. Such a requirement is of paramount importance especially in the presence of recent cyber security incidents. Furthermore, those incidents are subject to an augment with the increasing integration of ICT technologies and the vulnerabilities they introduce to the grid. The exploitation of these vulnerabilities might lead to attacks that can, for instance, mask the system observability and initiate cascading failures resulting in undesirable and severe consequences. In this thesis, we explore the security aspects of a key enabling technology in the smart grid, accurate time synchronization. Time synchronization is an immense requirement across the domains of the grid, from generation to transmission, distribution, and consumer premises. We focus on the substation, a basic block of the smart grid system, along with its recommended time synchronization mechanism - the Precision Time Protocol (PTP) - in order to address threats associated with PTP, and propose practical and efficient detection, prevention, mitigation techniques and methodologies that will harden and enhance the security and usability of PTP in a substation. In this respect, we start this thesis with a security assessment of PTP that identifies PTP security concerns, and then address those concerns in the subsequent chapters. We tackle the following main threats associated with PTP: 1) PTP vulnerability to fake timestamp injection through a compromised component 2) PTP vulnerability to the delay attack and 3) The lack of a mechanism that secures the PTP network. Next, and as a direct consequence of the importance of time synchronization in the smart grid, we consider the wide area system to demonstrate the vulnerability of relative data alignment in Phasor Data Concentrators to time synchronization attacks. These problems will be extensively studied throughout this thesis, followed by discussions that highlight open research directions worth further investigations