What is the difference between the rule-based detection when compared to behavioral detection?

Home » Cisco » 200-201 v.2 » What is the difference between the rule-based detection when compared to behavioral detection?

What is the difference between the rule-based detection when compared to behavioral detection?
A. Rule-Based detection is searching for patterns linked to specific types of attacks, while behavioral is identifying per signature.
B. Rule-Based systems have established patterns that do not change with new data, while behavioral changes.
C. Behavioral systems are predefined patterns from hundreds of users, while Rule-Based only flags potentially abnormal patterns using signatures.
D. Behavioral systems find sequences that match a particular attack signature, while Rule-Based identifies potential attacks.

Correct Answer: D Explanation/Reference:

Explanation:

Intrusion detection systems (IDS) are the lifeblood of network monitoring, and a critical component of any organization’s network security strategy today. In addition to monitoring the network for malicious activity and policy violations, an IDS reports that information to determine if unusual activity is a security risk or another type of anomaly.

Most legacy IDS solutions employ some type of signature-based intrusion detection. While this approach is effective at finding sequences and patterns that may match a particular known attacker IP address, file hash or malicious domain, it has limits when it comes to uncovering unknown attacks.

Behavior-based IDS offerings on the other hand, also known as anomaly-based threat detection, use AI and machine learning as well as other statistical methods to analyze data on a network to detect malicious behavior patterns as well as specific behaviors that may be linked to an attack.

Both approaches have merits when it comes to detecting and mitigating malicious behavior. Below we will outline the differences between the two types of IDS systems and explain which is better suited to today’s complex network architectures.

Signature-based IDS

Originally used by antivirus developers, the “attack signature” was employed to scan system files for evidence of malicious activity. A signature-based IDS solution typically monitors inbound network traffic to find sequences and patterns that match a particular attack signature. These may be found within network packet headers as well as in sequences of data that match known malware or other malicious patterns. An attack signature can also be found within destination or source network addresses as well as in specific sequences of data or series of packets.

Signature-based detection uses a known list of indicators of compromise (IOCs). These may include specific network attack behaviors, known byte sequences and malicious domains. They may also include email subject lines and file hashes.

One of the biggest limitations of signature-based IDS solutions is their inability to detect unknown attacks. Malicious actors can simply modify their attack sequences within malware and other types of attacks to avoid being detected. Traffic may also be encrypted in order to completely bypass signature-based detection tools. Also, APTs usually involve threat actors that change their signature over 60% of the time.

Behavior-based IDS

A behavior or anomaly-based IDS solution goes beyond identifying particular attack signatures to detect and analyze malicious or unusual patterns of behavior. This type of system applies Statistical, AI and machine learning to analyze giant amounts of data and network traffic and pinpoint anomalies.

Instead of searching for patterns linked to specific types of attacks, behavior-based IDS solutions monitor behaviors that may be linked to attacks, increasing the likelihood of identifying and mitigating a malicious action before the network is compromised.

By intelligently analyzing data using AI and machine learning, behavior-based IDS solutions offer the best line of defense against network breaches. They provide holistic views of today’s complex, sprawling networks from the premises to the data center and cloud. That means malicious and anomalous traffic will be detected across the entire physical and virtual network attack surfaces.

Many next-generation IDS systems use network traffic analysis to intelligently analyze network traffic behavior. This includes analyzing behavior patterns attributed to all entities associated with the network. Attributes like source and destination IP addresses, TCP flags, source and destination ports and bytes-in, bytes-out are used to monitor and build behavior baselines. All new activity of each entity is then compared to its baseline to identify anomalous behavior and deviations from the historical norm.

Behavior-based IDS solutions are critical for networks that experience a large amount of traffic. When used in tandem with perimeter protection, these offerings provide full visibility over network traffic as well as alerts if suspicious behavior is detected.

Choosing the right IDS solution

When it comes to selecting the proper IDS solution for today’s complex networks, the choice is clear. A whopping 80 percent of alerts generated by signature and policy-based IDS solutions are unreliable. Signature-based IDS offerings typically cannot detect malware and other unknown threats. This results in resources being taken away from other critical alerts, putting the network at risk.

A comprehensive next-generation IDS solution does typically includes signature-based detection as one component of its many advanced analytics features. When combined with statistical data and anomaly threat and behavior detection, the result is a powerful tool that generates alerts as well as intelligent guidance about which issues need to be further investigated.

According to Cyber Defense magazine, “No organization with sensitive data or critical operations to protect should be without behavior-based malware detection to augment the capabilities of existing security tools.”

Our Next Generation Intrusion Detection Guide offers additional information about how next-generation IDS solutions use sophisticated behavior analysis to collect, detect, investigate and respond to network anomalies. By analyzing all network traffic, these tools offer the visibility and protection necessary to secure today’s complex and evolving networks.