Using AI To Detect Network Anomalies

Traditional methods to detect malware and cyber security threats are failing; How artificial intelligence (AI) is used to detect network anomalies and cyber-attacks.

Behavioral Anomaly Recognition

In today’s corporate environments, we are seeing a steady increase in the sophistication of attacks on the customer’s data. Sophisticated worm viruses, ransomware, crypto-jacking, unsecure IoT, and shadow IT are the most prevalent we are seeing. All these attack vectors share a common behavior that can be detected on a network but is often missed in the confusion of log clutter.  Utilizing an Autonomous response is there when you can’t be – artificial intelligence that knows what to do and when in order to stop a cyber-threat in its tracks. Having a tool that can detect network behavior to baseline what is normal and what is an upward trend or anomaly is becoming more prevalent in the security in-depth architectures.

Network Behavior Anomaly Detection

Network behavior anomaly detection (NBAD) is the real-time monitoring of a network for any unusual activity, trends, or events utilizing Artificial Intelligence (AI) and Machine Learning (ML). The tools can detect threats and stop suspicious activities in situations where traditional security software is ineffective. NBAD systems sweep the entire network for threat actors. When it detects network behavior that appears out of the ordinary – for example, excessive traffic usage during non-peak hours – it alerts the network team and prompts them to investigate it.

Artificial intelligence and machine learning present a significant opportunity for the cyber security industry.

Today, most of the fruitful research and advancements have come from the sub-discipline of AI called machine learning (ML), which focuses on teaching machines to learn by applying algorithms to data. Artificial intelligence (AI) is a system that has been taught or learned how to carry out specific tasks without being explicitly programmed how to do so. Often, the terms AI and ML are used interchangeably.