Unmasking the Deepfake Threat: A Practical Guide to Detection & Defence
About This Course
In an era where Artificial Intelligence (AI) can generate hyper-realistic fake video and audio, deepfakes pose an escalating threat to individuals and organisations globally. This intensive one-day course will equip participants with a comprehensive understanding of deepfake risks, drawing on real-world incidents such as the £200 million fraud against Arup and the politically disruptive deepfake audio targeting Sadiq Khan. Participants will learn how deepfakes exploit human trust and discover how AI is both the problem and the solution in combating this evolving threat. A significant portion of the course will be dedicated to exploring a Deepfake Detector, a cutting-edge, AI-powered tool for real-time, on-device detection of deepfakes. Through practical demonstrations and discussions, attendees will gain insights into implementing robust internal policies, updating incident response plans, and fostering a zero-trust mindset to safeguard against deepfake-driven attacks and mitigate potential liability.
What You'll Learn
1. Identify and articulate the growing threat posed by deepfakes, including their exponential rise and impact on financial fraud and misinformation.
2. Understand the mechanisms by which deepfakes are created and the role of AI in both generating and detecting synthetic media.
3. Explain the core capabilities and unique advantages of the Deepfake Detector, including its real-time, on-device, application-agnostic, and Security Information and Event Management (SIEM)-integrated features.
4. Apply a zero-trust mindset to digital communications and recognise common red flags indicative of a deepfake attack.
5. Develop and update organisational incident response plans and internal policies to effectively address deepfake scenarios, emphasising verification and escalation procedures.
6. Recognise the importance of deepfake awareness training for employees and understand the potential liability and compliance exposures associated with deepfake incidents.
7. Strategise for integrating deepfake detection tools into a broader, multi-layered cybersecurity posture, including endpoint and hardware protection.
Entry Requirements
Proficiency in English