The latest edition of the ISMG Security Report analyzes the security and privacy implications of Facebook's new digital currency - Libra. Also featured: Discussions on the rise of machine learning and IT and OT collaboration on cybersecurity.
Why does everyone keep mislabeling machine learning - a proven technique for helping organizations to improve their security posture - as artificial intelligence? "I'm so tired of the AI buzzword bingo," says John Matthews, CIO of ExtraHop Networks.
After years of organizations being stuck in a reactive security posture, proactive prevention is finally possible thanks to machine learning backed by AI math models, says BlackBerry Cylance's John McClurg.
Artificial Intelligence is coming of age as a key tool in the security analyst's arsenal, says David Atkinson, founder and CEO of Senseon, who highlights key benefits of the technology.
The annual Infosecurity Europe conference this year returned to London. Here are visual highlights from the event, which featured over 240 sessions and more than 400 exhibitors, 19,500 attendees and keynotes covering data breaches, darknets, new regulations and more.
Carelessness, a lack of security awareness, unclear data ownership and poor toolsets are root causes of insider breaches, says Tony Pepper, CEO of Egress, which recently surveyed CISOs and employees to trace the cause of insider breaches resulting from both intentional and unintentional loss.
Traditionally, enterprises have built networks and then added security elements. But in what he describes as "the third generation of security," Fortinet's John Maddison promotes a model of security-driven networking. Hear how this can improve an organization's security posture.
Using artificial intelligence and machine learning in cybersecurity has pitfalls, says McAfee's Steve Grobman, who describes appropriate steps to take.
Multi-stage attacks use diverse and distributed methods to circumvent existing defenses and evade detection - spanning endpoints, networks, email and other vectors in an attempt to land and expand. Meanwhile, individual tools including DLP, EDR, CASBs, email security and advanced threat protection are only designed to...
Organizations may have great cybersecurity intentions, but translating those desires into a robust security reality is often challenging, says Ratinder Ahuja, CEO of ShieldX Networks. That's why he advocates automation to ensure intention equals reality.
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.
"Security by design" is at an inflection point as a result of advances in automation, orchestration, artificial intelligence and machine learning, says Lee Waskevich of ePlus Technology.
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.
Machine learning can play an important role in fraud prevention at financial institutions, says Marc Trepanier of ACI Worldwide, who addresses the challenges involved.
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