Detecting Cyber Crime With Artificial Intelligence

Author: Cyberseer.Net

Security professionals face a difficult task in keeping enterprise networks safe. Cyber-attacks continue to grow as criminals find new ways to infiltrate and compromise networks. When breaches occur, Security teams must identify them, limit the damage and track them. Investigations can be a hugely time consuming and manual process, whilst false positives are all too common.

Man and Machine Working Collaboratively

Leveraging machine learning as artificial intelligence (AI) to spot unusual patterns of behaviour in the deluge of available data can be an effective way to empower Security Analysts. A machine learning solution can parse large quantities of data faster than any human, which is significant in protecting corporate data and assets. They can condense a Security Analysts volume of triage work, providing focus on serious and sophisticated incidents. However, a machine learning algorithm cannot achieve 100% accuracy rate in spotting unknown malware. Merging man’s ingenuity with machine learning technology is key to identifying and fighting against polymorphic threats which change behaviour from one victim to another.

Trends Which Are Driving Demand For An A.I. Fuelled Threat Hunting Approach:

  • Number & severity of cyber-attacks rising.
  • Zero day attacks rising
  • Demand for cyber security talent outstripping supply of qualified professionals.
  • Volume of information generated

Using intelligent defences, Cyberseer detect anomalous behaviour using machine learning technologies and apply research-driven knowledge of sophisticated threats to determine the root cause and severity of the anomalous activity detected.

> See also: Cyberseer MSSP Service & Cyber Security Resources

> See also: Cyberseer Discoveries: Analyst Threat Findings


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