Are cyberattackers working on ways to counter artificial intelligence-augmented security? And will the bad guys ever use AI-driven attacks? Adi Ashkenazy of XM Cyber offers an analysis.
Data science is playing a fundamental role in a more dynamic approach to cybersecurity, says Jim Routh, CISO of Aetna, who stresses the importance of applying machine learning to front-line data security controls. Routh will be a featured speaker at the ISMG Security Summit in New York Aug. 14-15.
To mitigate the insider threat, organizations should apply user behavior analytics powered by artificial intelligence, says Mark Bower of Egress Software Technologies.
To have any hope of keeping up "with the exponential rise in variants in malware," organizations must reduce their attack surface, in part by using technology designed to learn what attacks look like and respond as quickly as possible, says Cylance's Anton Grashion.
Security experts warn that hackers could one day make use of machine learning and AI to make their attacks more effective. Thankfully, says Cybereason's Ross Rustici, that doesn't appear to have happened yet, although network-penetration attacks are getting more automated than ever.
Incident response challenge: How to deliver actionable information to security analysts to enable them to better triage? "The quicker you can detect and respond to an incident, the more you're likely to be able to contain and minimize the risk associate with it," says IBM's Mike Spradbery.
Security alert fatigue is a growing concern, leading to difficulties sorting out false positives from alerts worth investigating, says Robert Hamilton of Imperva.
Leading the latest edition of the ISMG Security Report: Our exclusive report on an Australian criminal investigation into a company that apparently swiped cryptocurrency using a software backdoor. Also, cutting through the hype on artificial intelligence and machine learning.
Organizations in various industries are under increased pressure to identify subtle patterns that indicate fraud before customers are targeted by threats including account takeover, identity theft, and application fraud.
Companies have turned to Machine Learning (ML) to stay ahead of the next generation of...
Companies offering cybersecurity products are using the terms "artificial intelligence" and "machine learning" in many different ways. But the real meanings of the terms are far more nuanced than marketing hyperbole would lead us to believe, says Grant Wernick of Insight Engines.
The annual Infosecurity Europe conference returns to London this week, with a focus on the latest cybersecurity trends and essential practices for organizations. Hot topics range from artificial intelligence and breach response to GDPR and battling cybercriminals and nation-states.
The American Civil Liberties Union has launched a broadside against Amazon, warning that Amazon Rekognition - mixing big data, machine learning and facial recognition - could be abused by authoritarian regimes. Amazon has countered by saying that all users must "comply with the law."
Finding out your organization has been breached can be devastating news. Knowing how to deal with an intruder that's broken through your cyber defenses can be even more challenging.
This whitepaper offers practical steps IT and security professionals should take after a cyberattack occurs. You'll receive guidance...
One of the biggest challenges in stopping data breaches lies in sifting through vast amounts of data to find the proverbial "needle in the haystack" - the subtle clues that indicate an attack is imminent or underway. As modern computer systems generate billions of events daily, the amount of data to analyze can reach...
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