We all have heard the expression “Data is the new currency”. More personal and proprietary data is available online than ever before. Protecting this valuable information from the malicious players trying to get ahold of it is the main goal of every intrusion detection system (IDS) in place in your network and on-premises devices.

Intrusion detection systems are designed to identify suspicious and malicious activity through network traffic. In simple words, an IDS enables you to discover whether your network is being attacked.

An intrusion detection system (IDS) is software specifically built to monitor network traffic and discover irregularities. Unwarranted or unexplained network changes could indicate malicious activity at any stage, whether it be the beginnings of an attack or a full-blown breach. There are two main kinds of intrusion detection system (IDS):

  • A network intrusion detection system (NIDS) enacts intrusion detection across your entire network, using all packet metadata and contents to determine threats.
  • A host-based intrusion detection system (HIDS) enacts intrusion detection through a particular endpoint, and monitors network traffic and system logs to and from a particular device.

How Does an Intrusion Detection System Work?


After data collection, an IDS is designed to observe network traffic and match traffic patterns to known attacks. Through this method, sometimes called pattern correlation, an intrusion prevention system could determine if unusual activity is a cyberattack. Once suspicious or malicious activity is discovered, an intrusion detection system will send an alarm to specified technicians or IT administrators. IDS alarms enable you to quickly begin troubleshooting and identify root sources of issues, or discover and stop harmful agents in their tracks.

Intrusion detection systems primarily use two key intrusion detection methods: signature-based intrusion detection and anomaly-based intrusion detection. Signature-based intrusion detection is designed to detect possible threats by comparing given network traffic and log data to existing attack patterns. Anomaly-based intrusion detection is the opposite—it’s designed to pinpoint unknown attacks, such as new malware, and adapt to them on the fly using machine learning. Combinations of these two methods exists as hybrid intrusion detection systems.


If this information is helpful to you read our blog for more interesting and useful content, tips and guildelines on similar topics. Contact the team of COMPUTER 2000 Bulgaria now if you have a specific question. Our specialists will be asiisting you with your query.

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