Businesses of all sizes need robust cybersecurity. Nobody is too big or too small to be a potential target. For many businesses, IDS security is a mainstay of their overall cybersecurity framework. Here is a quick guide to what you need to know about it.
An IDS (intrusion detection system) is designed to detect and respond to potential security threats. IDS focuses specifically on monitoring and analyzing network and system activities.
Unlike firewalls or antivirus software that primarily control access or remove malware, an IDS is dedicated to identifying anomalous patterns and behaviors indicative of potential threats.
IDS security is a crucial part of modern cybersecurity systems as it provides real-time alerts and insights into suspicious activities that might evade traditional security measures.
IDS security is basically the digital equivalent of real-world intrusion detection security. Just like its real-world counterparts, an IDS monitors for signs of suspicious activity. If it detects any, it raises an alert. It is then the job of other security tools and/or human agents to decide what action, if any, to take.
IDS security can be divided into three main stages.
The first stage in IDS security is collecting the data to be analyzed. Unlike its close counterpart an IPS (intrusion prevention system), an IPS sits apart from network traffic. The IDS receives a copy of all traffic while the original data continues on its way.
This does mean that there is the potential for the traffic to do harm before it is neutralized. On the other hand, it also means that using an IDS avoids creating latency in a network. By contrast, using an IPS can lead to unnecessary delays in traffic delivery.
The data collected for the IDS will usually be passed through an audit data processor. Essentially, this is just a check that ensures the data is valid (e.g. that it’s not corrupted).
Assuming the data passes the audit check, it will then be passed onto a detection engine. This will analyze both the volume and the content of the data.
Analyzing the volume of data is simply a matter of tracking flow rates and comparing them to expected behavior. Analyzing the content of the data requires checking the packet headers and evaluating them using one or more detection models. The main ones currently in use are signature-, anomaly- and heuristic-based detection.
This involves comparing observed network traffic or system activity against a database of predefined signatures or patterns associated with known cyber threats. Signature-based detection is effective for detecting known threats with established signatures.
This focuses on identifying deviations from established baselines or normal behavior within the network or system. Instead of relying on predefined signatures, this approach observes and learns what is considered normal, triggering alerts when activities fall outside the expected parameters.
Anomaly-based detection is particularly valuable for detecting previously unknown or zero-day attacks, as it doesn’t rely on prior knowledge of specific threats.
This involves identifying patterns or behaviors that may indicate a potential threat based on general rules and algorithms. While not as specific as signature-based detection, heuristics enable the detection of novel attack patterns without relying on predefined signatures. This approach adds a layer of flexibility by analyzing the behavior of network traffic or system activities for suspicious patterns that may not fit known threat profiles.
Other detection forms include behavior-based detection and network behavior analysis. These are also ways of detecting threats without knowledge of signatures or network patterns.
All detection models rely on a knowledge base. Keeping this knowledge base up to date is an essential part of IDS maintenance. Generally, the IDS vendor will provide ongoing updates. It is, however, usually down to the client to ensure that these are applied promptly.
The final step in IDS security is to put the analysis through a decision engine. This will use pre-defined rules (a decision table) to decide whether or not the traffic is safe. If it is not safe, the IDS will create an alert. These alerts can often be customized by using further pre-defined rules.
The two main types of IDS are hardware-based IDS and software-based IDS. Hardware-based IDS uses standalone appliances to run IDS security. These devices have their own resources. This means they can reliably turn around high volumes of data at fast speeds. Unfortunately, hardware-based IDS is relatively expensive and time-consuming to maintain.
As a result, smaller companies tend to opt for software-based IDS. This uses existing hardware and hence is a drain on the system. When traffic volumes are lower, however, this can be a fair trade-off for its cost-effectiveness and ease of maintenance.
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