Brute force is a type of attack used by malicious actors to gain unauthorized access to a system or network. This attack method uses a trial-and-error approach, attempting to guess passwords or encryption keys by systematically entering every possible combination until a successful result is achieved (Kumar, Gupta, & Chaudhary, 2017). Brute force attacks are commonly used against web applications, where the attacker can attempt to gain access by repeatedly entering user names and passwords until one is accepted (Liu & Li, 2018).

Brute force attacks can be difficult to detect, as they often take a long time to complete and may appear to be legitimate traffic (Liu & Li, 2018). In addition, many attackers will attempt to hide their attack by using multiple IP addresses or by varying the time between attempts (Kumar et al., 2017). However, there are some methods that can be used to identify brute force attacks. These include monitoring authentication attempts for excessive requests from a single IP address or user account, detecting large numbers of failed logins from a single IP address, and tracking trends in login attempts over time (Liu & Li, 2018).

Organizations can take several steps to protect against brute force attacks. These include using strong passwords and changing them regularly, implementing two-factor authentication, and limiting the number of failed login attempts (Kumar et al., 2017). Additionally, organizations should consider using an intrusion detection system to help detect any brute force attack attempts (Liu & Li, 2018).

In conclusion, brute force attacks are a common method used by malicious actors to gain unauthorized access to a system or network. While these attacks can be difficult to detect, organizations can take steps to protect against them, such as using strong passwords and two-factor authentication.


Kumar, S., Gupta, V. K., & Chaudhary, S. (2017). A Survey on Different Techniques for Protection against Brute Force Attack. International Journal of Computer Applications, 170(3), 17-21.

Liu, X., & Li, Y. (2018). Detection of Brute Force Attack Using Machine Learning Algorithms. International Journal of Grid and Distributed Computing, 11(4), 8-16.

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