Watch this brief video interview to learn more about how the city of Westland achieved their security goals by harnessing AI to gain the most real-time visibility into their environment.
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...
In recent years, Las Vegas has become a prototypical smart city. Between its fully autonomous vehicles and its array of IoT sensors, the city aims to embrace innovation without compromising the security of its 650,000 residents and 42 million annual tourists.
Yet local governments know that internet-connected...
Much like private companies, state and local governments of all kinds are going through a digital transformation at an unprecedented pace: migrating sensitive data to the cloud, installing internet-connected infrastructure, and offering services powered by smart devices.
At the same time, cyber-criminals are also...
You've heard the AI evangelists, but how can you ensure the AI solution you invest in is an intelligent, cognitive solution that can make your job easier?
The no-hype answer centers around making sure it can learn and can be proactive. It should automate your repeatable tasks to mitigate fatigue and solve what...
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.
Overwhelmed by the number of vulnerabilities your team faces? Uncertain which cyber threats pose the greatest risk to your business? You're not alone. Cybersecurity leaders have been grappling with these challenges for years - and the problem keeps getting worse.
On average, enterprises find 870 vulnerabilities per...
Entrusted with protecting the personal information of their residents, with securing critical infrastructure, and with overseeing fair elections, local governments face few challenges more pivotal than cyber security. Yet most cities and counties rely on an outdated approach to defending their networks: relying on...
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.
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.
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