How AI Models and Rich Datasets Can Improve Detection RatesSonicWall's Debasish Mukherjee on Training Generative AI to Improve Cybersecurity
Artificial intelligence has become a major talking point for cybersecurity vendors since the release of ChatGPT a year ago. But AI and ML are nothing new, and the real power behind using them to detect cyberthreats comes from the richness of datasets used to train the AI algorithm, said Debasish Mukherjee, vice president of sales for the Asia-Pacific and Japan region at SonicWall.
"The fundamental of AI is data. At SonicWall, we have 30 years' of data that we are using to train our AI tool for real-time, deep-memory inspection," Mukherjee said.
SonicWall focuses on providing a complete cybersecurity platform to help customers simplify the management of tools across the enterprises, and it has incorporated AI to help improve threat detection rates, suggest remediation measures and support software configuration.
In this video interview with Information Security Media Group at the Mumbai Summit, Mukherjee discussed:
- Today's enterprise security challenges;
- Harnessing AI and machine learning for security;
- SonicWall's road map and plans.
Mukherjee has diverse sales, business and partner leadership experience in the IT industry and has worked with Dell and SonicWall. He translates customer insights into integrated business strategies to drive profitable sales and increased wallet share.