Crossword Cybersecurity PLC introduces Nixer CyberML – A New Approach to Machine Learning Based Cybersecurity and Fraud Detection
November 2019 by Patrick LEBRETON
Crossword Cybersecurity Plc announce the launch of Nixer CyberML, a new family of machine-learning based security and anti-fraud software products, that help organisations easily and quickly build these capabilities into applications.
Nixer CyberML is a new tool for businesses that want to solve advanced security and cybercrime problems, such as detecting and dealing with compromised accounts, fraud and in-application denial of service attacks.
Many of today’s security and fraud problems occur within applications and are difficult, if not impossible, to detect externally to the applications. For example, if a fraudster has obtained a user’s login details via a credential attack, their access to the site while logging in can appear normal – but once inside the site, can start to behave maliciously. Nixer CyberML allows development teams to rapidly add machine learning based detection to online applications (online banking, ecommerce systems, ticket sites, critical business apps, etc.) that can learn to accurately distinguish between good and bad user behaviour.
This initial release designed for developers, includes the Nixer CyberML architecture, code libraries for Spring framework based applications, and a local Nixer CyberML Engine designed to help with credential protection functionality. The Nixer CyberML Engine, stores and processes anonymous application event data, and contains the machine learning algorithms which determine whether events are normal or potentially malicious. Future versions of Nixer CyberML will give developers access to cloud-based machine learning algorithms.
The benefits of using Nixer CyberML include:
Detecting, mitigating and preventing fraud and other user-based attacks that Web Application Firewalls (WAFs) and Distributed Denial of Service (DDoS) tools cannot mitigate, by using advanced machine-learning integrated into business applications
Quick and reliable deployment by using existing code and architecture, and, where needed, working with a specialist partner familiar with machine-learning, cyber security and cyber-crime prevention to provide support with data science and algorithm creation.
To find out more about Nixer CyberML, visit www.nixer.io or download the code libraries from Github.