As the digital landscape continues to evolve, so do the threats that lurk within it. With the rise of cyberattacks and intrusions, safeguarding networks and data has become crucial for businesses and individuals alike. In the wake of over 800,000 reported complaints of data breaches and malware-related incidents in 2021 alone, the necessity for robust cybersecurity measures has never been clearer.
Amidst the arsenal of defences against these threats stands the Intrusion Detection System (IDS), a critical component in the battle for network security.
With that in mind, here, we’ll look at the definition of Intrusion Detection System (IDS), and its five different types. Later, we’ll see which detection methods they use to keep your network safe.
Understanding Intrusion Detection System (IDS)
An Intrusion Detection System (IDS) is a vital network security tool designed to monitor network traffic and devices for any known malicious activities, suspicious behaviour, or violations of security policies.
IDSs play a crucial role in expediting and automating the detection of network threats by notifying security administrators of identified or potential threats. They may also forward alerts to centralized security tools like Security Information and Event Management (SIEM) systems. These systems amalgamate data from various sources, aiding security teams in identifying and responding to cyber threats that might bypass other security measures.
Furthermore, IDSs contribute to compliance efforts, especially in adhering to regulations like the Payment Card Industry Data Security Standard (PCI-DSS), which mandates organizations to deploy intrusion detection measures.
However, it’s important to note that an Intrusion Detection System alone cannot thwart security threats. Presently, IDS capabilities are commonly integrated with or embedded within Intrusion Prevention Systems (IPSs). IPSs identify security threats and autonomously take action to prevent them, thus providing a more comprehensive security solution.
Classification of Intrusion Detection System: 5 Types
Intrusion Detection System is categorized into five different types, each tailored to address specific security concerns:
1. Network Intrusion Detection System (NIDS): Positioned strategically within the network infrastructure, NIDS monitors traffic across the entire subnet, scanning for signs of malicious activity or unauthorized access attempts.
2. Host Intrusion Detection System (HIDS): Installed on individual hosts or devices, Host Intrusion Detection System focuses on scrutinizing incoming and outgoing traffic at the host level, thereby providing granular insights into potential threats.
3. Protocol-based Intrusion Detection System (PIDS): Operating at the forefront of server communications, PIDS oversees and interprets protocol exchanges, safeguarding critical network protocols from exploitation.
4. Application Protocol-based Intrusion Detection System (APIDS): Tailored for application-specific environments, Application Protocol-base Intrusion Detection System specializes in monitoring and analyzing communication on application protocols, such as SQL transactions, within server ecosystems.
5. Hybrid Intrusion Detection System: By amalgamating multiple detection approaches, Hybrid IDS offers comprehensive threat visibility and enhanced detection capabilities, making it a formidable defence mechanism against evolving cyber threats.
How Do Intrusion Detection System Work?
Intrusion Detection System (IDSs) operates through various implementations, including software applications installed on endpoints, dedicated hardware devices within networks, or cloud-based services. Regardless of their form, IDSs employ one or both of the following primary threat detection methodologies: signature-based detection and anomaly-based detection.
1. Signature-Based Detection:
Signature-based detection scrutinizes network packets for attack signatures, which are distinctive traits or behaviours associated with specific threats. For instance, a sequence of code indicative of a particular malware variant constitutes an attack signature.
An Intrusion Detection System utilizing signature-based detection maintains a database of attack signatures against which it evaluates network packets. Upon detecting a match to one of the signatures, the IDS raises an alert. To remain effective, signature databases necessitate regular updates with new threat intelligence to counter emerging cyber threats and evolving attack patterns. Nonetheless, newly developed attacks that lack corresponding signatures may elude signature-based IDSs.
2. Anomaly-Based Detection:
Anomaly-based detection methods leverage machine learning to establish and continuously refine a baseline model of typical network behaviour. Subsequently, it compares network activity against this model and identifies deviations, such as unusual bandwidth consumption by a process or the opening of typically closed ports by devices.
Anomaly-based IDSs often detect novel cyberattacks that evade signature-based detection, including zero-day exploits exploiting software vulnerabilities before developers can address them. However, they may also produce more false positives, as even authorized user activities, like accessing sensitive network resources for the first time, could trigger alerts.
3. Less Common Detection Methods:
Reputation-based detection blocks traffic originating from IP addresses and domains associated with malicious or suspicious activities. Stateful protocol analysis focuses on protocol behaviour, such as identifying denial-of-service (DoS) attacks by detecting a single IP address and initiating numerous simultaneous TCP connection requests within a short timeframe.
Regardless of the detection method(s) employed, when an IDS identifies a potential threat or policy breach, it alerts the incident response team for investigation. Intrusion Detection System maintain records of security incidents, either within their logs or by integrating with a Security Information and Event Management (SIEM) tool. These incident logs facilitate the refinement of IDS criteria, including the addition of new attack signatures or updates to the network behaviour model.
IDS Evasion Techniques
Despite their efficacy, Intrusion Detection System is not impervious to evasion techniques employed by sophisticated adversaries. Some common evasion strategies include:
#Fragmentation: Dividing packets into smaller fragments to evade signature-based detection.
#Flooding: Overwhelming the IDS with a barrage of traffic to mask malicious activities.
#Obfuscation: Concealing attack signatures and behaviours to thwart detection.
#Encryption: Encrypting malicious traffic to evade signature-based detection and analysis.
The Importance of Intrusion Detection System
IDSs play a pivotal role in promoting network security by:
– Identifying security incidents and anomalies in real time.
– Analyzing attack patterns and trends to refine threat intelligence.
– Assisting in regulatory compliance efforts through comprehensive log documentation.
– Enhancing incident response capabilities by providing actionable insights into network activities.
Conclusion
Intrusion Detection System represents a cornerstone of modern cybersecurity, offering proactive threat detection and mitigation capabilities essential for safeguarding critical assets and data. While IDSs serve as invaluable sentinels against cyber threats, their integration with complementary technologies, such as Intrusion Prevention Systems (IPS) and advanced threat protection mechanisms, further strengthens network defences.
As the cybersecurity landscape continues to evolve, organizations must remain alert. They have to use the collective power of IDSs and other defensive measures to stay one step ahead of malicious actors in the digital world.
