Deep Fake Detection, Deterrence and Response: Challenges and Opportunities

Afterward, we offer a solution that is capable of 1) making our AI systems robust against deepfakes during development and deployment phases; 2) detecting video, image, audio, and textual deepfakes; 3) identifying deepfakes that bypass detection (deepfake hunting); 4) leveraging available intelligence for timely identification of deepfake campaigns launched by state-sponsored hacking teams; 5) conducting in-depth forensic analysis of identified deepfake payloads. Our proposed solution can be used as a technical guide for developing detection, deterrence, and forensics investigation solutions for deepfakes. Our solution would address important elements of Canada's National Cyber Security Action Plan (2019-2024) in increasing the trustworthiness of our critical services [5]. Following actions can be taken based on this research findings: Raising public awareness about risks of deepfakes: increasing the understanding of deepfake threats and empowering Canadian public to do their part in keeping our society and critical services safe from deepfake-based attacks is the most important and effective step in reducing risk of deepfakes. Cybersecurity should always be considered as a shared responsibility. While this paper is focused on development of technical solutions for early detection and deterrence of deepfakes, the effectiveness of our solutions (or any technical solution in cybersecurity) are limited without regular and systemic public awareness campaigns. Supporting development of public training programs in this domain should be considered as a top priority. Developing AI robustness monitoring solutions: there is a growing trend in using AI to detect deepfakes. However, more recently, adversaries made attempts to create adversarial deepfake payloads that are capable of deceiving humans while bypassing AI-based detection systems!