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Due to the critical importance of Industrial Control Systems (ICS) to the operations of cities and countries, research into the security of critical infrastructure has become increasingly relevant and necessary. As a component of both the research and application sides of smart city development, accurate and precise modeling, simulation, and verification are key parts of a robust design and development tools that provide critical assistance in the prevention, detection, and recovery from abnormal behavior in the sensors, controllers, and actuators which make up a modern ICS system. However, while these tools have potential, there is currently a need for helper-toolsmore »Free, publicly-accessible full text available December 6, 2022
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The concern regarding users’ data privacy has risen to its highest level due to the massive increase in communication platforms, social networking sites, and greater users’ participation in online public discourse. An increasing number of people exchange private information via emails, text messages, and social media without being aware of the risks and implications. Researchers in the field of Natural Language Processing (NLP) have concentrated on creating tools and strategies to identify, categorize, and sanitize private information in text data since a substantial amount of data is exchanged in textual form. However, most of the detection methods solely rely onmore »
Free, publicly-accessible full text available September 18, 2022 -
In order to create user-centric and personalized privacy management tools, the underlying models must account for individual users’ privacy expectations, preferences, and their ability to control their information sharing activities. Existing studies of users’ privacy behavior modeling attempt to frame the problem from a request’s perspective, which lack the crucial involvement of the information owner, resulting in limited or no control of policy management. Moreover, very few of them take into the consideration the aspect of correctness, explainability, usability, and acceptance of the methodologies for each user of the system. In this paper, we present a methodology to formally model,more »Free, publicly-accessible full text available August 17, 2022
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To account for privacy perceptions and preferences in user models and develop personalized privacy systems, we need to understand how users make privacy decisions in various contexts. Existing studies of privacy perceptions and behavior focus on overall tendencies toward privacy, but few have examined the context-specific factors in privacy decision making. We conducted a survey on Mechanical Turk (N=401) based on the theory of planned behavior (TPB) to measure the way users’ perceptions of privacy factors and intent to disclose information are affected by three situational factors embodied hypothetical scenarios: information type, recipients’ role, and trust source. Results showed amore »
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The electrical power system is the backbone of our nations critical infrastructure. It has been designed to withstand single component failures based on a set of reliability metrics which have proven acceptable during normal operating conditions. However, in recent years there has been an increasing frequency of extreme weather events. Many have resulted in widespread long-term power outages, proving reliability metrics do not provide adequate energy security. As a result, researchers have focused their efforts resilience metrics to ensure efficient operation of power systems during extreme events. A resilient system has the ability to resist, adapt, and recover from disruptions.more »
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Motivated by decreased cost and climate change concerns, the penetration of solar photovoltaic (PV) energy generation and battery energy storage has been continually increasing. The variability in solar PV power generation has led to many new challenges for utilities and researchers. One challenge is the quantification of the resilience contribution to the grid from its assets and is the topic of this paper. In this work, we propose a framework for evaluating the resilience contribution of solar generation and battery storage assets on the grid. The metric provides a quantifiable adaptive capacity measure in terms of real and reactive powermore »
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Industrial Control Systems (ICS) are used to control physical processes in critical infrastructure. These systems are used in a wide variety of operations such as water treatment, power generation and distribution, and manufacturing. While the safety and security of these systems are of serious concern, recent reports have shown an increase in targeted attacks aimed at manipulating physical processes to cause catastrophic consequences. This trend emphasizes the need for algorithms and tools that provide resilient and smart attack detection mechanisms to protect ICS. In this paper, we propose an anomaly detection framework for ICS based on a deep neural network.more »
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Data and information privacy is a major concern of today’s world. More specifically, users’ digital privacy has become one of the most important issues to deal with, as advancements are being made in information sharing technology. An increasing number of users are sharing information through text messages, emails, and social media without proper awareness of privacy threats and their consequences. One approach to prevent the disclosure of private information is to identify them in a conversation and warn the dispatcher before the conveyance happens between the sender and the receiver. Another way of preventing information (sensitive) loss might be tomore »
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This paper focuses on the design and development of attack models on the sensory channels and an Intrusion Detection system (IDS) to protect the system from these types of attacks. The encoding/decoding formulas are defined to inject a bit of data into the sensory channel. In addition, a signal sampling technique is utilized for feature extraction. Further, an IDS framework is proposed to reside on the devices that are connected to the sensory channels to actively monitor the signals for anomaly detection. The results obtained based on our experiments have shown that the one-class SVM paired with Fourier transformation wasmore »
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Abstract Thermostatically Controlled Loads (TCLs) have shown great potential for Demand Response (DR) events. The focus of this study is to investigate the effects of adding communication throughout a population of TCLs on the resilience of the system. A Metric for resilience is calculated on varying populations of TCLs and verified with agent based modeling simulations. At the core of this study is an added thermostat criterion created from the combination of a proportional gain and the average compressor operating state of neighboring TCLs. Differing connection architectures are also analyzed. Resilience of the systems under different connection topologies, are calculatedmore »