At the Enigma Conference this month in San Francisco, Avast researcher Sadia Afroz answers that question
Is machine learning useful for cybersecurity?
It’s a fair question, given the significant challenges involved. Threat actors using adversarial algorithms can compete with cybersecurity programs, and building artificial intelligence programs without fairness biases is its own struggle.
So is machine learning in cybersecurity even worth it? The answer is yes. This month Avast artificial intelligence researcher Sadia Afroz will explain to San Francisco conference goers at Enigma 2020 how to build robust machine learning systems to defend against real-world attacks. “We need a systematic approach to model the adversary of a machine learning system in security. Different papers using different incomparable adversaries make it hard to track progress in this area.” In a paper written with Avast’s head of AI Rajarshi Gupta, Afroz calls for new industry-wide consistency in cybersecurity. “We need a systematic approach to model the adversary of a machine learning system in security. Different papers using different incomparable adversaries make it hard to track progress in this area.” (See more about her talk here.)
Sadia Afroz spoke to the CyberSec & AI Prague conference in October. Avast and the Czech Technical University will co-host CyberSec & AI Prague again this year. Find out more.
A research scientist at the International Computer Science Institute at UC-Berkeley (ICSI), Afroz works with the Avast team of data scientis ..
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