There has been a rise in internet usage, which has contributed to an equally alarming upsurge of cyber-crimes. Botnets are one of the most common Distribution denials of service attacks, and they aren?t easy to detect.
As much as the internet eases and simplifies our lives, it also increases the chances of cyber insecurities, making it a very profitable criminal activity. When networks of different computer devices are used in cyber-attacks and scams, it’s called a botnet. A botnet army activation causes your system to be overwhelmed by many botnet devices, eventually taking your applications down.
What are botnets used for?
The motives behind creating a botnet are similar to those of other cybercrimes whereby the attackers are after the theft of just creating trouble. Bots are used as gears to systematize mass attacks like distribution of malware, data theft, and server crashing. Their creators are mostly after financial theft, information theft to access sensitive and confidential information, sabotage websites activities and services by taking them down, and peddling access to other cybercriminals, thereby allowing more scams on clueless users; and for cryptocurrency, scams using the users processing ability.
What is Botnet detection?
Botnets can be very serious cybersecurity threats, even to enterprise systems. As botnet attacks become more common and threatening DDoS attacks in cybersecurity today, there’s a need for botnet detection tools and strategies. However, it can be hard to detect the presence of botnets as they are non-threatening till a command is made to attack. Therefore, it is challenging but not completely impossible to detect botnets in your system. Botnet detection tools are used to ensign and notify uncommon activity patterns among your system devices.
Botnet detection strategies
As botnets gain thrust in terms of spambots, DDoS attacks, click-fraud, and large-scale identity thefts, there’s a need for organizations to defend their systems against these intrusive programs. Various Bot detection strategies aim to identify irregular transmission of data among your server devices through analytics of data packets. Some of the botnet detection tools and techniques are:
1. Anomaly-based botnet detection technique
2. Signature-based botnet detection technique
3. DNS-based botnet detection technique
4. Mining-based botnet detection technique
There are two commonly used detection and identification strategies at both the host and network levels.
Network-based detection
In a network-based detection, an analysis of the network traffic is done after capturing to detect any infected hosts. After encryption of the network traffic, it’s quite tedious to detect a Botnet, and observing the traffic in the network may bring about some concerns regarding data privacy. You can also use traffic flow analysis to detect the presence of botnets using tools to measure traffic patterns.
Host-based detection
On the other hand, in host-based detection, each host’s system behavior is observed to check for any botnet-related behaviors. However, these host-based detection techniques are disadvantageous in that they are vulnerable to stealthy and host-resident malware, and there is a lot of difficulty in installing the monitored systems in every host in the network. You can also break down and analyze the malware code to detect the command and control server (C2s), which is used for bots communication. The most effective way to detect botnets in your system is to track and analyze the attacks using ordinary security solutions to provide visibility to determine which have a botnet origin.
Why botnet detection is important
Botnet armies can infect thousands of devices before they are detected as they are intelligent, large, and evolve continually. In addition, they have a distributed and hard-to-spot nature which makes them ideal for denial of service attacks, which are very potent threats to organizations. Botnets put the compromised host under the control of the botmaster, which leads to a series of commands for malicious activities. These activities include click fraud, spamming, phishing attacks, distributed denial of service (DDoS) attacks, and identity theft.
The increasing large-scale attacks in private enterprises and government operations systems necessitate botnet detection to prevent service losses. These attacks cause losses in terms of money and time, and the end-user applications are shut down indefinitely when the system becomes overcome with botnets. In addition, the attack leads to terminating communications with many infected devices, which is very difficult and time-consuming. Therefore, botnet prevention tools are used in small and large enterprises to avert this service loss.
