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.
Machine learning is one of the tools that you should be using as part of a multifaceted fraud strategy at financial institutions. To get value out of ML, you need to have multiple inputs. You have to have an intelligence network and the location to gather all that network intelligence.
Download this eBook on the...
Application fraud losses are projected to top $1.3B in the US by 2020. Understanding the trends behind these staggering numbers is critical if institutions are to prevent crippling financial and reputational losses.
Join Aite's Senior Analyst, Shirley Inscoe, and DataVisor's Director of Solution Engineering, Alex...
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...
Machine learning models and artificial intelligence are
transforming the way email is secured.
Download this eBook to learn more about:
The state of email security today;
The role AI and ML play in securing email infrastructures;
Why humans need not be a weak link.
AI will enable breakthrough advances in areas like healthcare, agriculture, education and transportation; it's already happening in many ways. But new technology also inevitably raises complex questions and broad societal concerns. As we look to a future powered by a partnership between computers and humans, it's...
Banks can drive real value to their fraud prevention strategies with machine learning and analytics if they cut through the hype. Machine learning can be made intuitive and available directly to fraud experts. A multi-faceted strategy can turn fraud prevention expertise into a revenue generator for the...
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.
Our website uses cookies. Cookies enable us to provide the best experience possible and help us understand how visitors use our website. By browsing careersinfosecurity.eu, you agree to our use of cookies.
