Home Security An Overview of Botnet Detection Techniques

An Overview of Botnet Detection Techniques

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In the recent past, DDoS cases have been on the rise. By the last quarter of 2020, DDoS attacks saw an increase of 10% over the same period in 2019. This may seem like a win, but after the pandemic forced everyone online, botnet-related attacks sharply increased and are still on the rise. This rise is attributed to the inability and/or low detection rates for these botnet attacks. To date network, security researchers and admins still struggle with ways of detecting them. By using exploits and zero-day attacks, attackers can launch targeted attacks on victims like banks, political parties, candidates, or e-commerce sites.

Challenges To Botnet Detection

Use Of Machine Learning To Mimic Human Behavior

As discussed above, network security researchers have had a hard time detecting botnets. Because they apply AI and Machine Learning, botnets have become more intelligent at evading detection mechanisms set out. One of the critical challenges is the human-like behavior of the bots within the network. Because the hacker does not want the victim to be aware of the attack. As a result, they use techniques to evade detection and apply current technologies like machine learning to mimic human behavior.

Their Uniqueness

There is no general model of how a botnet behaves and looks. Every botnet is different depending on how it grows, its setup, and its reason for existence. This complicates detecting them. A central server controls some botnets, while others use a peer-to-peer model. Botnets also differ in how they infect or target their victims. Some use executable files downloaded via pop-up links, and others use file attachments on emails or social media. Depending on their uses, some botnets conduct DDoS attacks while others are used to mine cryptocurrencies.

Increase in Using IoT devices

There has been a sharp rise in the adoption of Internet of Things (IoT) devices. This has unfortunately widened the cybercriminal’s matrix of attack. With most of these devices having unpatched vulnerabilities, botnets have found a new haven to attack your networks. A botnet can exploit any vulnerability within a network. When one device is infected, no device is safe within the same network.

Techniques For Botnet Detection

The key idea to botnet detection is identifying the command-and-control center (where the instructions are coming from). Below are the techniques used to detect botnets.

DNS Based Techniques

Because they have no effect on the network and do not require many resources, DNS-based techniques are the widely used botnet detection method. This technique uses the analysis of the network traffic to determine the anomalies that may be present. There are four main approaches to this technique; monitoring abnormal traffic, failed requests, malicious domains, and domains with low TTLs.

Monitoring For Malicious Domains

In this technique, you check all the DNS server requests against a blacklist database and allow them if they aren’t present. While this is a foolproof method of detecting botnets, it has a drawback. It requires previous knowledge of the botnet, making it hard to detect the new ones.

Domains Having Low Time-to-live

To evade detection, botnet creators use a fast-flux technique by modifying the IP address that is associated with the domain. With constant changes in the IP addresses, detecting the botnets becomes difficult. This leads to low TTL within such domains, and repeated refreshing of the resolution by the DNS system makes them suspicious. Therefore, you can detect botnets by monitoring the low TTL domain. However, it can lead to many false positives because many other legit systems have such behavior.

Abnormal DNS Traffic

In this method, you search for a domain having abnormal behavior of the DNS requests. You achieve this by analyzing the traffic for unusual traffic surges, high traffic on unusual ports, latency, and other anomalies. These may be indicators of botnet prevalence.

Failed DNS Requests

By statistically analyzing the failed DNS requests, you can figure out if there are botnets or whether there are botnets in your network. Because botnets use unregistered domains, their DNS request will be unsuccessful. Some botnets employ mechanisms like using low entropy to avoid being detected using this method.

Using Honeypots

To detect the bots, you can have an environment where vulnerabilities have been introduced deliberately. This kind of environment is called a honeypot. Honeypots have a powerful ability to detect malware, botnet signatures and elicit the motivations behind the botnet’s attack. They can be effective at detecting botnets in a network. Monitoring the traffic in a honeypot helps you collect information absent in other network intrusion detection systems (NIDS).

Built-in IRC Servers

By checking human non-behavioral traits in the network, an IRC server can detect botnets. However, it is necessary to have another detection mechanism that checks for secondary characteristics like the spread and attack. Monitoring TCP port 6667 is a way to detect botnets because cybercriminals use it to control them over IRC.

Botnet Detection Solution

Botnet detection requires real-time analysis of signatures and traffic. A botnet detection solution combines all the techniques above to analyze your website, mobile API, or a mobile application request. They use other technologies like sophisticated artificial intelligence and Machine Learning to detect if a user is a human or a bot. Unlike some of the above mechanisms, botnet detection solutions are automated. Therefore, they do not require daily management. You only need to configure a whitelist of allowed bots and leave the rest to the system. Because the bot detection solution runs the detection and prevention of bots and botnets on autopilot, you can focus on other productive tasks. When you enlist for a botnet detection solution, the detection improves because of the sharing of information. A botnet detection solution protects thousands of clients worldwide. Therefore, they have experience in dealing with bots and other related threats.

Conclusion

Botnet detection is an essential step in fortifying the security of your online infrastructures like APIs, Websites, and Mobile applications. Botnets pose a threat to your business. Therefore, there is a need to take measures to prevent the botnets from conducting various attacks and harming your website or mobile application. The best way to ensure that you remain protected is to contract with a bot detection, prevention, and protection solution.