The rapid advancement of deepfake technology, utilizing Artificial Intelligence (AI) to create convincing, but manipulated audio and video content, presents significant challenges to cybersecurity, privacy, and information integrity. This study explores the complex cybersecurity threats posed by deepfakes and evaluates effective strategies, to prepare organizations and individuals for these risks. Employing a qualitative research approach, semi-structured interviews with cybersecurity- and AI experts were conducted to gain insights into the current threat landscape, the technological evolution of deepfakes, and strategies for their detection and prevention. The findings reveal that while deepfakes offer opportunities in various sectors, they predominantly also pose threats such as misinformation, identity theft, and fraud. This study highlights the dual-use nature of deepfake technology, where improvements in creation and detection are continually evolving in a technological arms race. Ethical and societal implications are examined, emphasizing the need for enhanced public awareness and comprehensive regulatory frameworks to manage these challenges. The conclusions drawn from this research underscore the urgency of developing robust, AI-driven detection tools, advocating for a balanced approach that considers both technological advancements and the ethical dimensions of these innovations. Recommendations for policymakers and cybersecurity professionals include investing in detection technologies, promoting digital literacy, and fostering international collaboration to establish standards for ethical AI use. This thesis contributes to the broader discourse on AI ethics and cybersecurity, providing a foundation for future research and policy development in the era of digital manipulation.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:his-24105 |
| Date | January 2024 |
| Creators | Brandqvist, Johan |
| Publisher | Högskolan i Skövde, Institutionen för informationsteknologi |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
Page generated in 0.0145 seconds