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Articles 31 - 60 of 552

Full-Text Articles in Information Security

A Survey Of Using Machine Learning In Iot Security And The Challenges Faced By Researchers, Khawlah M. Harahsheh, Chung-Hao Chen Jan 2023

A Survey Of Using Machine Learning In Iot Security And The Challenges Faced By Researchers, Khawlah M. Harahsheh, Chung-Hao Chen

Electrical & Computer Engineering Faculty Publications

The Internet of Things (IoT) has become more popular in the last 15 years as it has significantly improved and gained control in multiple fields. We are nowadays surrounded by billions of IoT devices that directly integrate with our lives, some of them are at the center of our homes, and others control sensitive data such as military fields, healthcare, and datacenters, among others. This popularity makes factories and companies compete to produce and develop many types of those devices without caring about how secure they are. On the other hand, IoT is considered a good insecure environment for cyber …

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A Review Of Iot Security And Privacy Using Decentralized Blockchain Techniques, Vinay Gugueoth, Sunitha Safavat, Sachin Shetty, Danda Rawat Jan 2023

A Review Of Iot Security And Privacy Using Decentralized Blockchain Techniques, Vinay Gugueoth, Sunitha Safavat, Sachin Shetty, Danda Rawat

Electrical & Computer Engineering Faculty Publications

IoT security is one of the prominent issues that has gained significant attention among the researchers in recent times. The recent advancements in IoT introduces various critical security issues and increases the risk of privacy leakage of IoT data. Implementation of Blockchain can be a potential solution for the security issues in IoT. This review deeply investigates the security threats and issues in IoT which deteriorates the effectiveness of IoT systems. This paper presents a perceptible description of the security threats, Blockchain based solutions, security characteristics and challenges introduced during the integration of Blockchain with IoT. An analysis of different …

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Social-Engineering, Bio-Economies, And Nation-State Ontological Security: A Commentary, Brandon Griffin, Keitavius Alexander, Xavier-Lewis Palmer, Lucas Potter Jan 2023

Social-Engineering, Bio-Economies, And Nation-State Ontological Security: A Commentary, Brandon Griffin, Keitavius Alexander, Xavier-Lewis Palmer, Lucas Potter

Electrical & Computer Engineering Faculty Publications

Biocybersecurity is an evolving discipline that aims to identify the gaps and risks associated with the convergence of Biology (the science of life and living organisms) and cybersecurity (the science, study, and theory of cyberspace and cybernetics) to protect the bioeconomy. The biological industries’ increased reliance on digitization, automation, and computing power has resulted in benefits for the scientific community, it has simultaneously multiplied the risk factors associated with industrial espionage and the protection of data both commercial and proprietary. The sensitive and potentially destructive power of this data and its access inherently poses a risk to the national and …

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A Reflection Of Typology And Verification Flaws In Consideration Of Biocybersecurity/Cyberbiosecurity: Just Another Gap In The Wall, Luke Potter, Kim Mossberg, Xavier Palmer Jan 2023

A Reflection Of Typology And Verification Flaws In Consideration Of Biocybersecurity/Cyberbiosecurity: Just Another Gap In The Wall, Luke Potter, Kim Mossberg, Xavier Palmer

Electrical & Computer Engineering Faculty Publications

Verification is central to any process in a functional and enduring cyber-secure organization. This verification is how the validity or accuracy of a state of being is assessed (Schlick, 1936; Balci, 1998). Conversely, breakdown in verification procedures is core to the interruption of normal operations for an organization. A key problem for organizations that utilize biology as an interlock within their systems is that personnel lack sufficient ability to verify all practically relevant biological information for procedures such as a nurse logging a blood draw, or a molecular biology technician preparing agar to culture microbes for study. This has several …

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The Rise Of Terrorism In Africa And What It Means For U.S. Policymakers, Bridget Mary Hughes Dec 2022

The Rise Of Terrorism In Africa And What It Means For U.S. Policymakers, Bridget Mary Hughes

Master's Theses

This thesis utilizes three case studies to measure the rise of terrorism in Africa. This qualitative data leads the reader to one ultimate question: what does the rise in terrorism in Africa mean for the United States (U.S.) and U.S. policymakers, National Security academia, students in National Security, if anything at all? The answer is: if civilian and military compounds are being targeted by these violent extremists, as these three case studies demonstrate, it is my recommendation that U.S. policymakers cease sending troops to the African theater and, instead, allocate funding to the citizens and nonprofits of the countries whom …

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Control Implemented On Quantum Computers: Effects Of Noise, Nondeterminism, And Entanglement, Kip Nieman, Keshav Kasturi Rangan, Helen Durand Jul 2022

Control Implemented On Quantum Computers: Effects Of Noise, Nondeterminism, And Entanglement, Kip Nieman, Keshav Kasturi Rangan, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Quantum computing has advanced in recent years to the point that there are now some quantum computers and quantum simulators available to the public for use. In addition, quantum computing is beginning to receive attention within the process systems engineering community for directions such as machine learning and optimization. A logical next step for its evaluation within process systems engineering is for control, specifically for computing control actions to be applied to process systems. In this work, we provide some initial studies regarding the implementation of control on quantum computers, including the implementation of a single-input/single-output proportional control law on …

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Actuator Cyberattack Handling Using Lyapunov-Based Economic Model Predictive Control, Keshav Kasturi Rangan, Henrique Oyama, Helen Durand Jun 2022

Actuator Cyberattack Handling Using Lyapunov-Based Economic Model Predictive Control, Keshav Kasturi Rangan, Henrique Oyama, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Cybersecurity has gained increasing interest as a consequence of the potential impacts of cyberattacks on profits and safety. While attacks can affect various components of a plant, prior work from our group has focused on the impact of cyberattacks on control components such as process sensors and actuators and the development of detection strategies for cybersecurity derived from control theory. In this work, we provide greater focus on actuator attacks; specifically, we extend a detection and control strategy previously applied for sensor attacks and based on an optimization-based control technique called Lyapunov-based economic model predictive control (LEMPC) to detect attacks …

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Test Methods For Image-Based Information In Next-Generation Manufacturing, Henrique Oyama, Dominic Messina, Renee O'Neill, Samantha Cherney, Minhazur Rahman, Keshav Kasturi Rangan, Govanni Gjonaj, Helen Durand Jun 2022

Test Methods For Image-Based Information In Next-Generation Manufacturing, Henrique Oyama, Dominic Messina, Renee O'Neill, Samantha Cherney, Minhazur Rahman, Keshav Kasturi Rangan, Govanni Gjonaj, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Typical control designs in the process systems engineering literature have assumed that the primary sensing methodologies are traditional instruments such as thermocouples. Dig- italization is changing the landscape for manufacturing, and data-based sensing modalities (e.g., image-based sensing) are becoming of greater interest for plant control. These considerations require novel test/evaluation solutions. For example, process systems engineering researchers may wish to test image-based sensors in simulation. In this work, we provide preliminary thoughts on how image-based technologies might be evaluated via simulation for process systems.

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Quantum Computing And Resilient Design Perspectives For Cybersecurity Of Feedback Systems, Keshav Kasturi Rangan, Jihan Abou Halloun, Henrique Oyama, Samantha Cherney, Ilham Azali Assoumani, Nazir Jairazbhoy, Helen Durand, Simon Ka Ng Jun 2022

Quantum Computing And Resilient Design Perspectives For Cybersecurity Of Feedback Systems, Keshav Kasturi Rangan, Jihan Abou Halloun, Henrique Oyama, Samantha Cherney, Ilham Azali Assoumani, Nazir Jairazbhoy, Helen Durand, Simon Ka Ng

Chemical Engineering and Materials Science Faculty Research Publications

Cybersecurity of control systems is an important issue in next-generation manufac- turing that can impact both operational objectives (safety and performance) as well as process designs (via hazard analysis). Cyberattacks differ from faults in that they can be coordinated efforts to exploit system vulnerabilities to create otherwise unlikely hazard scenarios. Because coordination and targeted process manipulation can be characteristics of attacks, some of the tactics previously analyzed in our group from a control system cybersecurity perspective have incorporated randomness to attempt to thwart attacks. The underlying assumption for the generation of this randomness has been that it can be achieved …

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Challenges And Opportunities For Next-Generation Manufacturing In Space, Kip Nieman, A. F. Leonard, Katie Tyrell, Dominic Messina, Rebecca Lopez, Helen Durand Jun 2022

Challenges And Opportunities For Next-Generation Manufacturing In Space, Kip Nieman, A. F. Leonard, Katie Tyrell, Dominic Messina, Rebecca Lopez, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

With commercial space travel now a reality, the idea that people might spend time on other planets in the future seems to have greater potential. To make this possible, however, there needs to be flexible means for manufacturing in space to enable tooling or resources to be created when needed to handle unexpected situations. Next-generation manufacturing paradigms offer significant potential for the kind of flexibility that might be needed; however, they can result in increases in computation time compared to traditional control methods that could make many of the computing resources already available on earth attractive for use. Furthermore, resilience …

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On-Line Process Physics Tests Via Lyapunov-Based Economic Model Predictive Control And Simulation-Based Testing Of Image-Based Process Control, Henrique Oyama, A. F. Leonard, Minhazur Rahman, Govanni Gjonaj, Michael Williamson, Helen Durand Jun 2022

On-Line Process Physics Tests Via Lyapunov-Based Economic Model Predictive Control And Simulation-Based Testing Of Image-Based Process Control, Henrique Oyama, A. F. Leonard, Minhazur Rahman, Govanni Gjonaj, Michael Williamson, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Next-generation manufacturing involves increasing use of automation and data to enhance process efficiency. An important question for the chemical process industries, as new process systems (e.g., intensified processes) and new data modalities (e.g., images) are integrated with traditional plant automation concepts, will be how to best evaluate alternative strategies for data-driven modeling and synthesizing process data. Two methods which could be used to aid in this are those which aid in testing data-based techniques on-line, and those which enable various data-based techniques to be assessed in simulation. In this work, we discuss two techniques in this domain which can be …

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Framework Of Hardware Trojan Detection Leveraging Structural Checking Tool, Rafael Dacanay Del Carmen May 2022

Framework Of Hardware Trojan Detection Leveraging Structural Checking Tool, Rafael Dacanay Del Carmen

Graduate Theses and Dissertations

Since there is a significant demand for obtaining third-party soft Intellectual Property (IP) by first-party integrated circuit (IC) vendors, it is becoming easier for adversaries to insert malicious logic known as hardware Trojans into designs. Due to this, vendors need to find ways to screen the third-party IPs for possible security threats and then mitigate them. The development of the Structural Checking (SC) tool provides a solution to this issue. This tool analyzes the structure of an unknown soft IP design and creates a network of all the signals within the design and how they are connected to each other. …

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Lyapunov-Based Economic Model Predictive Control For Detecting And Handling Actuator And Simultaneous Sensor/Actuator Cyberattacks On Process Control Systems, Henrique Oyama, Dominic Messina, Keshav Kasturi Rangan, Helen Durand Apr 2022

Lyapunov-Based Economic Model Predictive Control For Detecting And Handling Actuator And Simultaneous Sensor/Actuator Cyberattacks On Process Control Systems, Henrique Oyama, Dominic Messina, Keshav Kasturi Rangan, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

The controllers for a cyber-physical system may be impacted by sensor measurement cyberattacks, actuator signal cyberattacks, or both types of attacks. Prior work in our group has developed a theory for handling cyberattacks on process sensors. However, sensor and actuator cyberattacks have a different character from one another. Specifically, sensor measurement attacks prevent proper inputs from being applied to the process by manipulating the measurements that the controller receives, so that the control law plays a role in the impact of a given sensor measurement cyberattack on a process. In contrast, actuator signal attacks prevent proper inputs from being applied …

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Technical Analysis Of Thanos Ransomware, Ikuromor Ogiriki, Christopher Beck, Vahid Heydari Mar 2022

Technical Analysis Of Thanos Ransomware, Ikuromor Ogiriki, Christopher Beck, Vahid Heydari

College of Science & Mathematics Departmental Research

Ransomware is a developing menace that encrypts users’ files and holds the decryption key hostage until the victim pays a ransom. This particular class of malware has been in charge of extortion hundreds of millions of dollars every year. Adding to the problem, generating new variations is cheap. Therefore, new malware can detect antivirus and intrusion detection systems and evade them or manifest in ways to make themselves undetectable. We must first understand the characteristics and behavior of various varieties of ransomware to create and construct effective security mechanisms to combat them. This research presents a novel dynamic and behavioral …

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Malware Detection Using Electromagnetic Side-Channel Analysis, Matthew A. Bergstedt Mar 2022

Malware Detection Using Electromagnetic Side-Channel Analysis, Matthew A. Bergstedt

Theses and Dissertations

Many physical systems control or monitor important applications without the capacity to monitor for malware using on-device resources. Thus, it becomes valuable to explore malware detection methods for these systems utilizing external or off-device resources. This research investigates the viability of employing EM SCA to determine whether a performed operation is normal or malicious. A Raspberry Pi 3 was set up as a simulated motor controller with code paths for a normal or malicious operation. While the normal path only calculated the motor speed before updating the motor, the malicious path added a line of code to modify the calculated …

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A Probabilistic Perspective Of Human-Machine Interaction, Mustafa Canan, Mustafa Demir, Samuel Kovacic Jan 2022

A Probabilistic Perspective Of Human-Machine Interaction, Mustafa Canan, Mustafa Demir, Samuel Kovacic

Engineering Management & Systems Engineering Faculty Publications

Human-machine interaction (HMI) has become an essential part of the daily routine in organizations. Although the machines are designed with state-of-the-art Artificial Intelligence applications, they are limited in their ability to mimic human behavior. The human-human interaction occurs between two or more humans; when a machine replaces a human, the interaction dynamics are not the same. The results indicate that a machine that interacts with a human can increase the mental uncertainty that a human experiences. Developments in decision sciences indicate that using quantum probability theory (QPT) improves the understanding of human decision-making than merely using classical probability theory (CPT). …

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Detecting The Presence Of Electronic Devices In Smart Homes Using Harmonic Radar, Beatrice Perez, Gregory Mazzaro, Timothy J. Pierson, David Kotz Jan 2022

Detecting The Presence Of Electronic Devices In Smart Homes Using Harmonic Radar, Beatrice Perez, Gregory Mazzaro, Timothy J. Pierson, David Kotz

Dartmouth Scholarship

Data about users is collected constantly by phones, cameras, Internet websites, and others. The advent of so-called ‘Smart Things' now enable ever-more sensitive data to be collected inside that most private of spaces: the home. The first step in helping users regain control of their information (inside their home) is to alert them to the presence of potentially unwanted electronics. In this paper, we present a system that could help homeowners (or home dwellers) find electronic devices in their living space. Specifically, we demonstrate the use of harmonic radars (sometimes called nonlinear junction detectors), which have also been used in …

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Defensive Distillation-Based Adversarial Attack Mitigation Method For Channel Estimation Using Deep Learning Models In Next-Generation Wireless Networks, Ferhat Ozgur Catak, Murat Kuzlu, Evren Catak, Umit Cali, Ozgur Guler Jan 2022

Defensive Distillation-Based Adversarial Attack Mitigation Method For Channel Estimation Using Deep Learning Models In Next-Generation Wireless Networks, Ferhat Ozgur Catak, Murat Kuzlu, Evren Catak, Umit Cali, Ozgur Guler

Engineering Technology Faculty Publications

Future wireless networks (5G and beyond), also known as Next Generation or NextG, are the vision of forthcoming cellular systems, connecting billions of devices and people together. In the last decades, cellular networks have dramatically grown with advanced telecommunication technologies for high-speed data transmission, high cell capacity, and low latency. The main goal of those technologies is to support a wide range of new applications, such as virtual reality, metaverse, telehealth, online education, autonomous and flying vehicles, smart cities, smart grids, advanced manufacturing, and many more. The key motivation of NextG networks is to meet the high demand for those …

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Deeppose: Detecting Gps Spoofing Attack Via Deep Recurrent Neural Network, Peng Jiang, Hongyi Wu, Chunsheng Xin Jan 2022

Deeppose: Detecting Gps Spoofing Attack Via Deep Recurrent Neural Network, Peng Jiang, Hongyi Wu, Chunsheng Xin

Electrical & Computer Engineering Faculty Publications

The Global Positioning System (GPS) has become a foundation for most location-based services and navigation systems, such as autonomous vehicles, drones, ships, and wearable devices. However, it is a challenge to verify if the reported geographic locations are valid due to various GPS spoofing tools. Pervasive tools, such as Fake GPS, Lockito, and software-defined radio, enable ordinary users to hijack and report fake GPS coordinates and cheat the monitoring server without being detected. Furthermore, it is also a challenge to get accurate sensor readings on mobile devices because of the high noise level introduced by commercial motion sensors. To this …

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"Mystify": A Proactive Moving-Target Defense For A Resilient Sdn Controller In Software Defined Cps, Mohamed Azab, Mohamed Samir, Effat Samir Jan 2022

"Mystify": A Proactive Moving-Target Defense For A Resilient Sdn Controller In Software Defined Cps, Mohamed Azab, Mohamed Samir, Effat Samir

Electrical & Computer Engineering Faculty Publications

The recent devastating mission Cyber–Physical System (CPS) attacks, failures, and the desperate need to scale and to dynamically adapt to changes, revolutionized traditional CPS to what we name as Software Defined CPS (SD-CPS). SD-CPS embraces the concept of Software Defined (SD) everything where CPS infrastructure is more elastic, dynamically adaptable and online-programmable. However, in SD-CPS, the threat became more immanent, as the long-been physically-protected assets are now programmatically accessible to cyber attackers. In SD-CPSs, a network failure hinders the entire functionality of the system. In this paper, we present MystifY, a spatiotemporal runtime diversification for Moving-Target Defense (MTD) to secure …

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A Channel State Information Based Virtual Mac Spoofing Detector, Peng Jiang, Hongyi Wu, Chunsheng Xin Jan 2022

A Channel State Information Based Virtual Mac Spoofing Detector, Peng Jiang, Hongyi Wu, Chunsheng Xin

Electrical & Computer Engineering Faculty Publications

Physical layer security has attracted lots of attention with the expansion of wireless devices to the edge networks in recent years. Due to limited authentication mechanisms, MAC spoofing attack, also known as the identity attack, threatens wireless systems. In this paper, we study a new type of MAC spoofing attack, the virtual MAC spoofing attack, in a tight environment with strong spatial similarities, which can create multiple counterfeits entities powered by the virtualization technologies to interrupt regular services. We develop a system to effectively detect such virtual MAC spoofing attacks via the deep learning method as a countermeasure. …

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Analysis Of Deep Learning Methods For Wired Ethernet Physical Layer Security Of Operational Technology, Lucas Torlay Dec 2021

Analysis Of Deep Learning Methods For Wired Ethernet Physical Layer Security Of Operational Technology, Lucas Torlay

All Theses

The cybersecurity of power systems is jeopardized by the threat of spoofing and man-in-the-middle style attacks due to a lack of physical layer device authentication techniques for operational technology (OT) communication networks. OT networks cannot support the active probing cybersecurity methods that are popular in information technology (IT) networks. Furthermore, both active and passive scanning techniques are susceptible to medium access control (MAC) address spoofing when operating at Layer 2 of the Open Systems Interconnection (OSI) model. This thesis aims to analyze the role of deep learning in passively authenticating Ethernet devices by their communication signals. This method operates at …

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Integration Of Blockchain Technology Into Automobiles To Prevent And Study The Causes Of Accidents, John Kim Dec 2021

Integration Of Blockchain Technology Into Automobiles To Prevent And Study The Causes Of Accidents, John Kim

Electronic Theses, Projects, and Dissertations

Automobile collisions occur daily. We now live in an information-driven world, one where technology is quickly evolving. Blockchain technology can change the automotive industry, the safety of the motoring public and its surrounding environment by incorporating this vast array of information. It can place safety and efficiency at the forefront to pedestrians, public establishments, and provide public agencies with pertinent information securely and efficiently. Other industries where Blockchain technology has been effective in are as follows: supply chain management, logistics, and banking. This paper reviews some statistical information regarding automobile collisions, Blockchain technology, Smart Contracts, Smart Cities; assesses the feasibility …

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Forensic Artifact Finder (Forensicaf): An Approach & Tool For Leveraging Crowd-Sourced Curated Forensic Artifacts, Tyler Balon, Krikor Herlopian, Ibrahim Baggili, Cinthya Grajeda-Mendez Aug 2021

Forensic Artifact Finder (Forensicaf): An Approach & Tool For Leveraging Crowd-Sourced Curated Forensic Artifacts, Tyler Balon, Krikor Herlopian, Ibrahim Baggili, Cinthya Grajeda-Mendez

Electrical & Computer Engineering and Computer Science Faculty Publications

Current methods for artifact analysis and understanding depend on investigator expertise. Experienced and technically savvy examiners spend a lot of time reverse engineering applications while attempting to find crumbs they leave behind on systems. This takes away valuable time from the investigative process, and slows down forensic examination. Furthermore, when specific artifact knowledge is gained, it stays within the respective forensic units. To combat these challenges, we present ForensicAF, an approach for leveraging curated, crowd-sourced artifacts from the Artifact Genome Project (AGP). The approach has the overarching goal of uncovering forensically relevant artifacts from storage media. We explain our approach …

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Forensicast: A Non-Intrusive Approach & Tool For Logical Forensic Acquisition & Analysis Of The Google Chromecast Tv, Alex Sitterer, Nicholas Dubois, Ibrahim Baggili Aug 2021

Forensicast: A Non-Intrusive Approach & Tool For Logical Forensic Acquisition & Analysis Of The Google Chromecast Tv, Alex Sitterer, Nicholas Dubois, Ibrahim Baggili

Electrical & Computer Engineering and Computer Science Faculty Publications

The era of traditional cable Television (TV) is swiftly coming to an end. People today subscribe to a multitude of streaming services. Smart TVs have enabled a new generation of entertainment, not only limited to constant on-demand streaming as they now offer other features such as web browsing, communication, gaming etc. These functions have recently been embedded into a small IoT device that can connect to any TV with High Definition Multimedia Interface (HDMI) input known as Google Chromecast TV. Its wide adoption makes it a treasure trove for potential digital evidence. Our work is the primary source on forensically …

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Duck Hunt: Memory Forensics Of Usb Attack Platforms, Tyler Thomas, Mathew Piscitelli, Bhavik Ashok Nahar, Ibrahim Baggili Aug 2021

Duck Hunt: Memory Forensics Of Usb Attack Platforms, Tyler Thomas, Mathew Piscitelli, Bhavik Ashok Nahar, Ibrahim Baggili

Electrical & Computer Engineering and Computer Science Faculty Publications

To explore the memory forensic artifacts generated by USB-based attack platforms, we analyzed two of the most popular commercially available devices, Hak5's USB Rubber Ducky and Bash Bunny. We present two open source Volatility plugins, usbhunt and dhcphunt, which extract artifacts generated by these USB attacks from Windows 10 system memory images. Such artifacts include driver-related diagnostic events, unique device identifiers, and DHCP client logs. Our tools are capable of extracting metadata-rich Windows diagnostic events generated by any USB device. The device identifiers presented in this work may also be used to definitively detect device usage. Likewise, the DHCP logs …

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Another Brick In The Wall: An Exploratory Analysis Of Digital Forensics Programs In The United States, Syria Mccullough, Stella Abudu, Ebere Onwubuariri, Ibrahim Baggili Aug 2021

Another Brick In The Wall: An Exploratory Analysis Of Digital Forensics Programs In The United States, Syria Mccullough, Stella Abudu, Ebere Onwubuariri, Ibrahim Baggili

Electrical & Computer Engineering and Computer Science Faculty Publications

We present a comprehensive review of digital forensics programs offered by universities across the United States (U.S.). While numerous studies on digital forensics standards and curriculum exist, few, if any, have examined digital forensics courses offered across the nation. Since digital forensics courses vary from university to university, online course catalogs for academic institutions were evaluated to curate a dataset. Universities were selected based on online searches, similar to those that would be made by prospective students. Ninety-seven (n = 97) degree programs in the U.S. were evaluated. Overall, results showed that advanced technical courses are missing from curricula. We …

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Data Forgery Detection In Automatic Generation Control: Exploration Of Automated Parameter Generation And Low-Rate Attacks, Yatish R. Dubasi May 2021

Data Forgery Detection In Automatic Generation Control: Exploration Of Automated Parameter Generation And Low-Rate Attacks, Yatish R. Dubasi

Computer Science and Computer Engineering Undergraduate Honors Theses

Automatic Generation Control (AGC) is a key control system utilized in electric power systems. AGC uses frequency and tie-line power flow measurements to determine the Area Control Error (ACE). ACE is then used by the AGC to adjust power generation and maintain an acceptable power system frequency. Attackers might inject false frequency and/or tie-line power flow measurements to mislead AGC into falsely adjusting power generation, which can harm power system operations. Various data forgery detection models are studied in this thesis. First, to make the use of predictive detection models easier for users, we propose a method for automated generation …

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A Framework To Detect The Susceptibility Of Employees To Social Engineering Attacks, Hashim H. Alneami May 2021

A Framework To Detect The Susceptibility Of Employees To Social Engineering Attacks, Hashim H. Alneami

Doctoral Dissertations and Master's Theses

Social engineering attacks (SE-attacks) in enterprises are hastily growing and are becoming increasingly sophisticated. Generally, SE-attacks involve the psychological manipulation of employees into revealing confidential and valuable company data to cybercriminals. The ramifications could bring devastating financial and irreparable reputation loss to the companies. Because SE-attacks involve a human element, preventing these attacks can be tricky and challenging and has become a topic of interest for many researchers and security experts. While methods exist for detecting SE-attacks, our literature review of existing methods identified many crucial factors such as the national cultural, organizational, and personality traits of employees that enable …

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Achieving Differential Privacy And Fairness In Machine Learning, Depeng Xu May 2021

Achieving Differential Privacy And Fairness In Machine Learning, Depeng Xu

Graduate Theses and Dissertations

Machine learning algorithms are used to make decisions in various applications, such as recruiting, lending and policing. These algorithms rely on large amounts of sensitive individual information to work properly. Hence, there are sociological concerns about machine learning algorithms on matters like privacy and fairness. Currently, many studies only focus on protecting individual privacy or ensuring fairness of algorithms separately without taking consideration of their connection. However, there are new challenges arising in privacy preserving and fairness-aware machine learning. On one hand, there is fairness within the private model, i.e., how to meet both privacy and fairness requirements simultaneously in …

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