Matching Items (72)
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- All Subjects: Computer Science
- Creators: Ahn, Gail-Joon
Description
Mobile Augmented Reality (MAR) is a portable, powerful, and suitable technology that integrates 3D virtual content into the physical world in real-time. It has been implemented for multiple intents as it enhances people’s interaction, e.g., shopping, entertainment, gaming, etc. Thus, MAR is expected to grow at a tremendous rate in the upcoming years, as its popularity via mobile devices has increased. But, unfortunately, the applications that implement MAR, hereby referred to as MAR-Apps, bear security issues. Such are imaged in worldwide recorded incidents caused by MAR-Apps, e.g., robberies, authorities requesting banning MAR at specific locations, etc. To further explore these concerns, a case study analyzed several MAR-Apps available in the market to identify the security problems in MAR. As a result of this study, the threats found were classified into three categories. First, Space Invasion implies the intrusive modification through MAR of sensitive spaces, e.g., hospitals, memorials, etc. Then, Space Affectation means the degradation of users’ experience via interaction with undesirable MAR or malicious entities. Finally, MAR-Apps mishandling sensitive data leads to Privacy Leaks. SpaceMediator, a proof-of-concept MAR-App that imitates the well-known and successful MAR-App Pokémon GO, implements the solution approach of a Policy-Governed MAR-App, which assists in preventing the aforementioned mentioned security issues. Furthermore, its feasibility is evaluated through a user study with 40 participants. As a result, uncovering understandability over the security issues as participants recognized and prevented them with success rates as high as 92.50%. Furthermore, there is an enriched interest in Policy-Governed MAR-Apps as 87.50% of participants agreed with restricted MAR-Apps within sensitive spaces, and 82.50% would implement constraints in MAR-Apps. These promising results encourage adopting the Policy-Governed solution approach in future MAR-Apps.
ContributorsClaramunt, Luis Manuel (Author) / Ahn, Gail-Joon (Thesis advisor) / Rubio-Medrano, Carlos E (Committee member) / Baek, Jaejong (Committee member) / Arizona State University (Publisher)
Created2022
Description
Studies on underground forums can significantly advance the understanding of cybercrime workflow and underground economies. However, research on underground forums has concentrated on public information with little attention paid to users’ private interactions. Since detailed information will be discussed privately, the failure to investigate private interactions may miss critical intelligence and even misunderstand the entire underground economy. Furthermore, underground forums have evolved into criminal freelance markets where criminals trade illicit products and cybercrime services, allowing unsophisticated people to launch sophisticated cyber attacks. However, current research rarely examines and explores how criminals interact with each other, which makes researchers miss the opportunities to detect new cybercrime patterns proactively. Moreover, in clearnet, criminals are active in exploiting human vulnerabilities to conduct various attacks, and the phishing attack is one of the most prevalent types of cybercrime. Phishing awareness training has been proven to decrease the rate of clicking phishing emails. However, the rate of reporting phishing attacks is unexpectedly low based on recent studies, leaving phishing websites with hours of additional active time before being detected. In this dissertation, I first present an analysis of private interactions in underground forums and introduce machine learning-based approaches to detect hidden connections between users. Secondly, I analyze how criminals collaborate with each other in an emerging scam service in underground forums that exploits the return policies of merchants to get a refund or a replacement without returning the purchased products. Finally, I conduct a comprehensive evaluation of the phishing reporting ecosystem to identify the critical challenges while reporting phishing attacks to enable people to fight against phishers proactively.
ContributorsSun, Zhibo (Author) / Ahn, Gail-Joon (Thesis advisor) / Doupe, Adam (Thesis advisor) / Bao, Tiffany (Committee member) / Benjamin, Victor (Committee member) / Arizona State University (Publisher)
Created2022