Hong Kong – Cybersecurity company Trend Micro has recently unveiled the latest advancements to its enterprise platform and consumer cybersecurity products, designed to safeguard against the threat of AI-driven attacks and fraud across
This new solution will soon be available on the Trend Vision One platform, with a new deepfake detection technology feature that utilises various methods to detect AI-generated content. The said capability will also be available for consumers in Trend Micro Deepfake Inspector.
Aside from this feature, the platform will also analyse user behavioural elements to provide a stronger approach to detecting and stopping deepfakes. Upon threat detection, Trend Micro will notify enterprise security teams, enabling them to learn from the incident, educate their team, and take measures to prevent similar attacks in the future.
The Trend Micro Deepfake Inspector can further help verify if a party in a live video conversation is using deepfake technology, alerting users that the person or persons with whom they are conversing may not be who they appear to be.
In addition, these new solutions in the Trend Vision One platform offer key features including centralized management of employees’ GenAI access and usage, inspection prompts to prevent data leaks and malicious injections, filter of GenAI content to meet compliance requirements, and lastly, defence against large language model attacks.
Kevin Simzer, COO at Trend Micro, said, “Our latest research reveals several new deepfake tools that make it easy for cybercriminals at all skill levels to launch damaging scams, social engineering, and security bypass attempts.”
“We are leading the industry in fighting back for both our enterprise and consumer customers with new capabilities to detect deepfakes and other forms of AI fraud. Like past shifts in the threat and IT landscape, we’ve seen the challenge of securing AI and risen to it,” concluded Simzer.
Dan Ayoub, analyst at Gartner, also shared, “Readily available, high-quality GenAI applications are now capable of creating photo-realistic video content that can deceive or mislead an audience. Given the low barriers to entry in using these tools and their increasing sophistication, developing a methodological approach to detecting GenAI deepfake content has become necessary.”
