Machine learning systems adapt their behavior on the basis of a feedback loop, so they can overlearn and develop blind spots, which if not understood by practitioners can lead to dangerous situations, says Sam Curry of Cybereason.
Automation is the first step toward full-blown machine learning and artificial intelligence. But unfortunately, automation already is being weaponized for malicious purposes, says Fortinet's Derek Manky.
In a keynote address at the RSA Conference 2019, RSA President Rohit Ghai encouraged attendees to work in the coming years to "implement a security program with machines and humans working together. Humans asking questions; machines hunting answers."
As the use of artificial intelligence tools and robotics continues to grow, it's crucial for organizations to assess the potential security risks posed, says attorney Stephen Wu, who reviews key issues in an interview.
For decades, IT professionals have been fighting malware, hackers, and other threats. Data protection, confidentiality, integrity and availability have long been threatened not only by amateur hackers, but by profit-oriented, well-organised criminals. Victims can usually only react because many of the usual methods...
Around the world, many CIOs at various levels of governments expect an increase in cybersecurity spending in 2019, according to new research from Gartner. Alia Mendonsa, co-author of the report, analyzes the results of a global survey.
The data being used to drive effective anti-fraud efforts can be rich in context and useful for other activities. Jim Apger of Splunk describes emerging fraud schemes and solutions, highlighting the role of machine learning.
The easy availability of tools for designing face-swapping deep-fake videos drove Symantec security researchers Vijay Thaware and Niranjan Agnihotri to design a tool for spotting deep fakes, which they described in a briefing at the Black Hat Europe 2018 conference in London.