>
'Higher Pregnancy Rate for the Unvaccinated' Compared to COVID-19 Jabbed in IVF Study:
Enemies of the State D.C. Bash - Fri, May 24, 2024 - Washington Hilton - Doors open 9:00 PM EDT
The 'Deep State' Is Far Deeper Than Anyone Imagined
$300,000 robotic micro-factories pump out custom-designed homes
$300,000 robotic micro-factories pump out custom-designed homes
Skynet Has Arrived: Google Follows Apple, Activates Worldwide Bluetooth LE Mesh Network
The Car Fueled Entirely by the Sun Takes Huge Step Towards Production
A new wave of wearable devices will collect a mountain on information on us...
Star Trek's Holodeck becomes reality thanks to ChatGPT and video game technology
Blazing bits transmitted 4.5 million times faster than broadband
Scientists Close To Controlling All Genetic Material On Earth
Doodle to reality: World's 1st nuclear fusion-powered electric propulsion drive
In the wake of a Hong Kong fraud case that saw an employee transfer US$25 million in funds to five bank accounts after a virtual meeting with what turned out to be audio-video deepfakes of senior management, the biometrics and digital identity world is on high alert, and the threats are growing more sophisticated by the day.
A blog post by Chenta Lee, chief architect of threat intelligence at IBM Security, breaks down how researchers from IBM X-Force successfully intercepted and covertly hijacked a live conversation by using LLM to understand the conversation and manipulate it for malicious purposes – without the speakers knowing it was happening.
"Alarmingly," writes Lee, "it was fairly easy to construct this highly intrusive capability, creating a significant concern about its use by an attacker driven by monetary incentives and limited to no lawful boundary."
Hack used a mix of AI technologies and a focus on keywords
By combining large language models (LLM), speech-to-text, text-to-speech and voice cloning tactics, X-Force was able to dynamically modify the context and content of a live phone conversation. The method eschewed the use of generative AI to create a whole fake voice and focused instead on replacing keywords in context – for example, masking a spoken real bank account number with an AI-generated one. Tactics can be deployed through a number of vectors, such as malware or compromised VOIP services. A three second audio sample is enough to create a convincing voice clone, and the LLM takes care of parsing and semantics.