Computer Engineering Commons^™

Beyond Permissions: A Privacy And Security Analysis Of Sensor And Network Activity On Xr Devices Using Xrmonitor, Gayatri Sravya Siripurapu

Computer Science and Engineering Theses - Archive

Standalone virtual reality headsets integrate multiple sensors and cameras whose runtime behavior is not transparently documented, creating potential privacy and security risks that are difficult to audit using existing tools. The relationship between software feature activation and the underlying hardware engaged at runtime remains opaque, limiting the ability of users and researchers to assess what data is being collected and when.

This thesis presents XRMonitor, a unified framework for monitoring and analyzing sensor activation behavior and network traffic on Meta Quest devices. The framework is motivated by the lack of transparency in how standalone XR devices engage their hardware sensors …

Harnessing Generative Ai And Large Language Models For Revolutionizing Cybersecurity In The Internet Of Things: Ethical And Privacy Implications, Harsha Sammangi, Aditya Jagatha, Jun Liu

Research & Publications

Generative artificial intelligence (AI) and large language models (LLMs) have in- troduced transformative capabilities in cybersecurity, particularly in securing Internet of Things (IoT) environments. These technologies can synthesize vast datasets, support real-time anomaly detection, and generate predictive insights through simple prompts. However, their deployment also presents ethical and privacy-related concerns, including algorithmic bias, data leakage, and misuse for malicious content creation. This paper conducts a systematic literature review to evaluate how LLMs and generative AI contribute to IoT cybersecurity. We propose an ethical AI-IoT security framework, examine key challenges, and offer recommendations for integrating responsible AI governance. We aim to …

Artificial Intelligence In Surveillance And Privacy, Elizabeth D. Brasher

NEXUS: The Liberty Journal of Interdisciplinary Studies

This paper attempts to provide insight into the new and developing world of artificial intelligence and its integration into surveillance technologies. These technologies being implemented by the government, retail companies, healthcare organizations, and more, all raise ethical questions and implications addressed in this article; other topics, such as the integration of Christian ethics and responsibilities, are also explored.

Privacy Implications Of Data Collection In Android Automotive Os, Bulut Gözübüyük

All Theses

Modern vehicles have become sophisticated computational and sensor systems, as evidenced by advanced driver assistance systems (ADAS), in-car infotainment, and autonomous driving capabilities. They collect and process vast amounts of data through various onboard subsystems. One significant player in this landscape is Android Automotive OS (AAOS), which has been integrated into over 100 million vehicles and has become a dominant force in the in-vehicle infotainment (IVI) market. With this extensive data collection, privacy concerns have become increasingly crucial. The volume of data gathered by these systems raises questions about how this information is stored, used, and protected, making privacy a …

Privacy At Scale: A Study Of Mobile App Privacy Practices, Katherine Perez

LSU Master's Theses

What is privacy in a world where people are more connected than ever? Due to the Internet and its rapid advancement, the way information is shared and accessed has fundamentally changed. Millions of people interact with social networks, websites, and applications daily—and with each interaction, some data is collected from the user. In many cases, users cannot access a website or application without first accepting the service’s Privacy Policy. However, these policies often obscure the details of how a consumer’s data is handled, burying important information under dense legal language. In response to growing concerns about transparency, some platforms have …

Fair And Sustainable Machine Learning: A Holistic Approach To Data Quality, Efficiency, And Resource-Aware Training, Zahidur Rahim Talukder

Computer Science and Engineering Dissertations - Archive

The increasing reliance on distributed, privacy-sensitive data has driven the emergence of Federated Learning (FL) as a transformative paradigm for collaborative machine learning. By enabling multiple client devices to train a shared global model without transferring raw data, FL offers significant privacy advantages. However, real-world deployments of FL are constrained by critical challenges such as data heterogeneity, client unreliability, and hardware disparities. These factors lead to uneven model convergence, degraded global accuracy, and fairness issues that threaten FL's scalability and inclusivity in diverse environments.

This dissertation investigates these challenges and proposes three novel algorithmic frameworks to advance the state-of-the-art in …

Smartphones On Wheels In Southeast Asia: A Crossroads For Data Governance, Attamongkol Tantratian, Gunn Jiravuttipong

Journal of Law and Mobility

While the transformation of automobiles into data-generating “smartphones on wheels” has revolutionized mobility, it has also raised critical concerns over data privacy and sovereignty. Equipped with sensors and connected technologies, smart vehicles collect vast amounts of data, including personal information, driving patterns, and biometric identifiers. While auto-exporting jurisdictions such as the United States, the European Union, and China have introduced regulatory measures to address these challenges, countries importing smart vehicles remain vulnerable due to their limited influence over the auto companies’ integrated technology and data policies.

This Article examines the regulatory and economic challenges faced by developing nations integrating foreign-designed …

Framework For Identity Privacy Through Gender Based Skeletonization, Harrison Hwang

Master's Projects

The protection of one’s privacy and sensitive information is becoming increasingly difficult in the modern age full of surveillance and data collection. Through the use of image based object detection machine learning models trained for human and facial recognition, people can be identified and tracked to a terrifyingly accurate degree. On the other hand, the information present in surveillance media can play a key role in security and law enforcement. This presents a problem of how to preserve key information without compromising the privacy of any individuals present in the video. In this research project, Computer Vision techniques and a …

Integrating Authentication Schemes In Augmented And Virtual Reality Classrooms, Naheem Noah

Electronic Theses and Dissertations

Augmented Reality and Virtual Reality (AR/VR) technologies are revolutionizing educational experiences, but their widespread adoption hinges on addressing critical security and usability challenges, particularly in the domain of user authentication. This research presents an investigation into the security landscape of AR/VR and explores a graphical authentication scheme called “Things” that enhances both security and usability in immersive learning environments. Through a systematic evaluation of popular AR/VR devices and applications, potential vulnerabilities and limitations were identified, such as high usage of pin/passwords which are susceptible to shoulder-surfing attacks, lack of multi-factor authentication, and unclear data-sharing practices. A review of existing knowledge-based …

Boundary Regulation Processes And Privacy Concerns With (Non-)Use Of Voice-Based Assistants, Jessica Vitak, Priya C. Kumar, Yuting Liao, Michael Zimmer

Human-Machine Communication

An exemplar of human-machine communication, voice-based assistants (VBAs) embedded in smartphones and smart speakers simplify everyday tasks while collecting significant data about users and their environment. In recent years, devices using VBAs have continued to add new features and collect more data—in potentially invasive ways. Using Communication Privacy Management theory as a guiding framework, we analyze data from 11 focus groups with 65 US adult VBA users and nonusers. Findings highlight differences in attitudes and concerns toward VBAs broadly and provide insights into how attitudes are influenced by device features. We conclude with considerations for how to address boundary regulation …

Domain Specific Analysis Of Privacy Practices And Concerns In The Mobile Application Market, Fahimeh Ebrahimi Meymand

LSU Doctoral Dissertations

Mobile applications (apps) constantly demand access to sensitive user information in exchange for more personalized services. These-mostly unjustified-data collection tactics have raised major privacy concerns among mobile app users. Existing research on mobile app privacy aims to identify these concerns, expose apps with malicious data collection practices, assess the quality of apps' privacy policies, and propose automated solutions for privacy leak detection and prevention. However, existing solutions are generic, frequently missing the contextual characteristics of different application domains. To address these limitations, in this dissertation, we study privacy in the app store at a domain level. Our objective is to …

An Optimized And Scalable Blockchain-Based Distributed Learning Platform For Consumer Iot, Zhaocheng Wang, Xueying Liu, Xinming Shao, Abdullah Alghamdi, Md. Shirajum Munir, Sujit Biswas

School of Cybersecurity Faculty Publications

Consumer Internet of Things (CIoT) manufacturers seek customer feedback to enhance their products and services, creating a smart ecosystem, like a smart home. Due to security and privacy concerns, blockchain-based federated learning (BCFL) ecosystems can let CIoT manufacturers update their machine learning (ML) models using end-user data. Federated learning (FL) uses privacy-preserving ML techniques to forecast customers' needs and consumption habits, and blockchain replaces the centralized aggregator to safeguard the ecosystem. However, blockchain technology (BCT) struggles with scalability and quick ledger expansion. In BCFL, local model generation and secure aggregation are other issues. This research introduces a novel architecture, emphasizing …

Software Protection And Secure Authentication For Autonomous Vehicular Cloud Computing, Muhammad Hataba

Dissertations

Artificial Intelligence (AI) is changing every technology we deal with. Autonomy has been a sought-after goal in vehicles, and now more than ever we are very close to that goal. Vehicles before were dumb mechanical devices, now they are becoming smart, computerized, and connected coined as Autonomous Vehicles (AVs). Moreover, researchers found a way to make more use of these enormous capabilities and introduced Autonomous Vehicles Cloud Computing (AVCC). In these platforms, vehicles can lend their unused resources and sensory data to join AVCC.

In this dissertation, we investigate security and privacy issues in AVCC. As background, we built our …

Presenting A Method To Detect Intrusion In Iot Through Private Blockchain, Rezvan Mahmoudie, Saeed Parsa, Amir Masoud Rahmani

Turkish Journal of Electrical Engineering and Computer Sciences

Blockchain (BC) has been used as a new solution to overcome security and privacy challenges in the Internet of Things (IoT). However, recent studies have indicated that the BC has a limited scalability and is computationally costly. Also, it has significant overhead and delay in the network, which is not suitable to the nature of IoT. This article aims at implementing BC in the IoT context for smart home management, as the integration of these two technologies ensures the IoT's security and privacy. Therefore, we proposed an overlay network in private BC to optimize its compatibility with IoT by increasing …

A New Implementation Of Federated Learning For Privacy And Security Enhancement, Xiang Ma, Haijian Sun, Rose Qingyang Hu, Yi Qian

Department of Electrical and Computer Engineering: Faculty Publications

Motivated by the ever-increasing concerns on personal data privacy and the rapidly growing data volume at local clients, federated learning (FL) has emerged as a new machine learning setting. An FL system is comprised of a central parameter server and multiple local clients. It keeps data at local clients and learns a centralized model by sharing the model parameters learned locally. No local data needs to be shared, and privacy can be well protected. Nevertheless, since it is the model instead of the raw data that is shared, the system can be exposed to the poisoning model attacks launched by …

Splicecube Architecture: An Extensible Wi-Fi Monitoring Architecture For Smart-Home Networks, Namya Malik

Dartmouth College Master’s Theses

The vision of smart homes is rapidly becoming a reality, as the Internet of Things and other smart devices are deployed widely. Although smart devices offer convenience, they also create a significant management problem for home residents. With a large number and variety of devices in the home, residents may find it difficult to monitor, or even locate, devices. A central controller that brings all the home’s smart devices under secure management and a unified interface would help homeowners and residents track and manage their devices.

We envision a solution called the SPLICEcube whose goal is to detect smart devices, …

Designing Respectful Tech: What Is Your Relationship With Technology?, Noreen Y. Whysel

Publications and Research

According to research at the Me2B Alliance, people feel they have a relationship with technology. It’s emotional. It’s embodied. And it’s very personal. We are studying digital relationships to answer questions like “Do people have a relationship with technology?” “What does that relationship feel like?” And “Do people understand the commitments that they are making when they explore, enter into and dissolve these relationships?” There are parallels between messy human relationships and the kinds of relationships that people develop with technology. As with human relationships, we move through states of discovery, commitment and breakup with digital applications as well. Technology …

Estonian Internet Voting With Anonymous Credentials, İsa Sertkaya, Peter Roenne, Peter Y. A. Ryan

Turkish Journal of Electrical Engineering and Computer Sciences

The Estonian Internet voting (EIV) scheme is a unique example of a long-term nation-wide, legally binding electronic voting deployment. The EIV scheme is used in parallel with standard paper-based election day voting, of course invalidating an already cast i-vote. This necessarily requires careful authentication of the eligible voters and makes the Estonian identity card solution a crucial part of the scheme, however, note that Parsovs has recently drawn attention to the security flaws found in Estonian ID-cards. In this study, we propose an e-voting scheme EIV-AC that integrates the EIV scheme with anonymous credentials based on self-sovereign identity. In addition …

Privacy In Blockchain Systems, Murat Osmanoğlu, Ali̇ Aydin Selçuk

Turkish Journal of Electrical Engineering and Computer Sciences

Privacy of blockchains has been a matter of discussion since the inception of Bitcoin. Various techniques with a varying degree of privacy protection and complexity have been proposed over the past decade. In this survey, we present a systematic analysis of these proposals in four categories: (i) identity, (ii) transaction, (iii) consensus, and (iv) smart contract privacy. Each of these categories have privacy requirements of its own, and various solutions have been proposed to meet these requirements. Almost every technique in the literature of privacy enhancing technologies have been applied to blockchains: mix networks, zero-knowledge proofs, blind signatures, ring signatures, …

Permissioned Blockchain Based Remote Electronic Examination, Öznur Kalkar, İsa Sertkaya

Turkish Journal of Electrical Engineering and Computer Sciences

Recent coronavirus pandemic transformed almost all aspects of daily life including educational institutions and learning environments. As a result, this transformation brought remote electronic examination (shortly e-exam) concepts back into consideration. In this study, we revisit secure and privacy preserving e-exam protocol proposals and propose an e-exam protocol that utilizes decentralized identity-based verifiable credentials for proof of authentication and public-permissioned blockchain for immutably storing records. In regard to the previously proposed e-exam schemes, our scheme offers both privacy enhancement and better efficiency. More concretely, the proposed solution satisfies test answer authentication, examiner authentication, anonymous marking, anonymous examiner, question secrecy, question …

Book Review: This Is How They Tell Me The World Ends: The Cyberweapons Arms Race (2020) By Nicole Perlroth, Amy C. Gaudion

Dickinson Law Review (2017-Present)

No abstract provided.

A Proportionality-Based Framework For Government Regulation Of Digital Tracing Apps In Times Of Emergency, Sharon Bassan

Dickinson Law Review (2017-Present)

Times of emergency present an inherent conflict between the public interest and the preservation of individual rights. Such times require granting emergency powers to the government on behalf of the public interest and relaxing safeguards against government actions that infringe rights. The lack of theoretical framework to assess governmental decisions in times of emergency leads to a polarized and politicized discourse about potential policies, and often, to public distrust and lack of compliance.

Such a discourse was evident regarding Digital Tracing Apps (“DTAs”), which are apps installed on cellular phones to alert users that they were exposed to people who …

Efficient Yet Robust Privacy For Video Streaming, Luke Cranfill, Junggab Son

Master of Science in Computer Science Theses

MPEG-DASH is a video streaming standard that outlines protocols for sending audio and video content from a server to a client over HTTP. The standard has been widely utilized by the video streaming industry. However, it creates an opportunity for an adversary to invade users’ privacy. While a user is watching a video, information is leaked in the form of meta-data, the size and time that the server sent data to the user. This information is not protected by encryption and can be used to create a fingerprint for a video. Once the fingerprint is created, the adversary can use …

Towards A Federated Identity And Access Management Across Universities, Jameel Alsulami

Doctoral Dissertations and Master's Theses

Many research projects are too complex to yield the efforts of a single investigator and require a coordinated effort from interdisciplinary research teams across universities and industries. The research data, documents, experimental testbeds, high-end computing equipment, etc. is a critical component of any large-scale project and hence the cooperation and resource sharing across universities become very important for timely and budget-friendly execution of these projects. However, it is extremely challenging to frequently and effectively access data and other resources across universities without creating new identities for the users. In this thesis, we propose Federated Identity Management (FIM) approach for facilitating …

A Bibliometric Analysis Of Authentication Based Access Control In Cloud Using Blockchain, Yogesh Gajmal, Udayakumar R.

Library Philosophy and Practice (e-journal)

Access Control is mentioned to as the imprisonment of particular activities of an individual to carry out an action. Cloud storing similar to any other untrusted surroundings wants the capacity to protect the shared data. The one of the apparatus of access mechanism is ciphertext-policy attribute-based encryption system over and done with dynamic characteristics. With a blockchain based distributed ledger, the scheme offers immutable log of whole significant safety events, for example key generation, change or revocation, access policy assignment, access request etc. Number of different problems similar to single point of failure, security and privacy etc. were targeted through …

Fedoram: A Federated Oblivious Ram Scheme, Alexandre Pujol, Liam Murphy, Christina Thorpe

Articles

Instant messaging (IM) applications, even with end-to-end encryption enabled, pose privacy issues due to metadata and pattern leakage. Our goal is to develop a model for a privacy preserving IM application, by designing an IM application that focuses on hiding metadata and discussion patterns. To solve the issue of privacy preservation through the obfuscation of metadata, cryptographic constructions like Oblivious Random Access Machines (ORAM) have been proposed in recent years. However, although they completely hide the user access patterns, they incur high computational costs, often resulting in excessively slow performance in practice. We propose a new federated model, FedORAM, which …

Icts For Surveillance And Suppression: The Case Of The Indian Emergency 1975-1977, Ramesh Subramanian

Journal of International Technology and Information Management

Information and Communications technologies (ICT) pervade society. The Internet, wireless communication, and social media are ubiquitous in and indispensable in society today. As they continue to grow and mushroom, there are new and increased calls from various segments of the society such as technologists, activists, sociologists, and legal experts, who issue warnings on the more nefarious and undesirable uses of ICTs, especially by governments. In fact, government control and surveillance using ICTs is not a new phenomenon. By looking at history, we are able to see several instances when ICTs have been used by governments to control, surveil, and infringe …

The Law Of Black Mirror - Syllabus, Yafit Lev-Aretz, Nizan Packin

Open Educational Resources

Using episodes from the show Black Mirror as a study tool - a show that features tales that explore techno-paranoia - the course analyzes legal and policy considerations of futuristic or hypothetical case studies. The case studies tap into the collective unease about the modern world and bring up a variety of fascinating key philosophical, legal, and economic-based questions.

Private Face Detection Based On Random Sub-Images In Cloud, Yuan Peng, Jin Xin, Xiaodong Li, Zhao Geng, Yaming Wu, Mingxin Ma, Yulu Tian, Yingya Chen

Journal of System Simulation

Abstract: In order to detect faces of terminal face image in the cloud at the same time protect both privacy of data,a method of face images privacy detection based on random sub-Images representation was proposed. Terminal divided original image into 2 value sub-images weighted sum based on random sub-images generation algorithm and randomly arranges weights of sub-images. Terminal sent sub-images according to the weights of random sequence to the cloud server. Cloud server detected sub-images with its face detection algorithm. Terminal merges test results based on random sub were exploded. Two random vectors were leveraged to protect the parameters …

Traffic Privacy Study On Internet Of Things – Smart Home Applications, Ayan Patel

Master's Theses

Internet of Things (IoT) devices have been widely adopted in many different applications in recent years, such as smart home applications. An adversary can capture the network traffic of IoT devices and analyze it to reveal user activities even if the traffic is encrypted. Therefore, traffic privacy is a major concern, especially in smart home applications. Traffic shaping can be used to obfuscate the traffic so that no meaningful predictions can be drawn through traffic analysis. Current traffic shaping methods have many tunable variables that are difficult to optimize to balance bandwidth overheads and latencies. In this thesis, we study …