A Comparative Analysis of Deepfake Detection and Preventive Tools for Online Professional Social Networks

Sequel to the wide popularity of online social networking sites, such as Facebook, LinkedIn, Twitter, and Google plus, a number of professionals across the globe have resorted to these platforms for communication. On the other hand, some bad actors have targeted these platforms for their malicious exploits. One of the more recent challenge to professional online social networks is the Deepfake. These are synthetically generated media such as videos, images, audio or voice made-up to misrepresent reality. They present serious risks to professional online social network platforms such as LinkedIn. Typical threats include identity fraud, misinformation, and erosion of trust. This research adopts the agile approach. It explores tools and techniques that can detect the deepfake content on LinkedIn. This research adopted the agile approach. It explores tools and techniques that can detect and prevent the deepfake content on LinkedIn. An incisive review of state-of-the-art works was undertaken with a view to comparing selected detection and prevention tools, evaluating their effectiveness in conditions simulated as LinkedIn’s setting in order to obtain results and recommendations for LinkedIn and other similar professional online professional social networks. Keywords: Systems, technology, enterprise resource planning (ERP), IT, infrastructure, e-commerce. CISDI Journal Reference Format Nwaocha, V.O. (2024): A Comparative Analysis of Deepfake Detection and Preventive Tools for Online Professional Social Networks. Computing, Information Systems, Development Informatics & Allied Research Journal. Vol 10 No 2 .Pp 83-90. Available online at isteams.net dx.doi.org