Organizations around the world have become increasingly reliant on machine learning systems. Many are utilizing machine learning to automate the detection of cyber-threats such as phishing, malware, malicious emails, and more.
AppGate is positioned as a “Strong Performer” in the Forrester Wave™ Q2 2020 Risk-Based Authentication report. Read it complimentary here.
As the world grapples with the Coronavirus pandemic, self-isolation and stay-at-home-orders have increasingly become the norm.
Fraud attacks are now on the rise, with malicious actors launching targeted phishing and malware attacks, capitalizing on the Coronavirus pandemic. Having a strong cybersecurity strategy in place has never been more critical.
After more than a decade of high-profile data breaches – in which the sensitive personal data of hundreds of millions of people were exposed to hackers – it’s clear that password-based authentication alone, albeit convenient, is not secure enough.
The majority of financial institutions have made the digital transformation – offering online banking through their website or on mobile applications.
Cyber threats of all types evolve frequently to become more elaborate and complex.
Over the past year there have been some incredible advancements in cybersecurity.
It has never been clearer that organizations are aware of the risks of fraud: in 2019 100% of financial institutions surveyed in the Faces of Fraud Report reported increasing or maintaining their budgets for fraud prevention.
It’s no secret that a layered approach is the key to a successful anti-fraud strategy.