In today’s world, targeted attacks by hackers are quite common. To protect systems from such attacks, a method called signature-based detection is used. If you’re curious about what this detection system is, you’ve come to the right place. In this guide, we will explain what it is, how signature-based virus detection works, and provide an example of its usage. So, let’s begin without any delay.
What is Signature-Based Detection?
Signature-based detection helps scan data for attacks. It works by creating special identifiers for known attacks, so that similar future attacks can be quickly stopped. This method relies on a preprogrammed list of known signs of compromise. These signs may include harmful IP addresses and warnings about network traffic. Keep reading our guide to know how it works.
How Does Signature-Based Virus Detection Work?
This is how this scanning method works:
1. Detects the malware which is already in the database: It scans the file then the antivirus software compares the code in the file to all the signatures it has in its database. If the signature matches the database signatures, malware is detected. After that, the file is considered to be malware. Then, to prevent the attack from the virus that the file has, it deletes the file. Thus, protecting the user from known threats and keeping the network safe.
2. Detects malware that is not in the database: A signature of a new malware pattern is added to the database. To include the pattern, the antivirus scanner is updated. When the antivirus program detects a piece of software containing the same pattern, the antivirus scanner takes that piece of software as malware.
What is an Example of Signature-Based Detection?
Buffer overflow can be considered an example of signature-based detection. It keeps a list of shellcodes; whenever any request contains that shellcode, it alerts the user. SNORT is another software that uses a signature-based detection method.
Also Read: How to Remove a Virus from an Android Phone (Guide)
What are Signature Based Detection Advantages and Disadvantages
Here, we will tell you the signature-based detection advantages and disadvantages. Following are some of the perks of using this detection system:
- For known attacks, it has a high-processing speed. As a result, it can identify nefarious activity quickly.
- It has a low false positive rate. So, you can rely on it as it is accurate.
- As hackers usually use the known and defined attack method. Therefore, it can easily prevent your system from hackers.
- Apart from this, signatures can be shared. So, a shared library of attacks can be created to help prevent the maximum number of threats.
- It protects computers against cyber attacks.
- Moreover, it is conceptually simple.
Despite its advantages, there are some disadvantages. And you should know about it. So please keep reading to learn about its cons:
- Trained staff is required to maintain it.
- It can tackle only known attacks.
- The database needs to be updated regularly.
- Apart from this, it will not be able to detect zero-day exploits.
- If the variant does not match the signature, it might not detect known attack variants.
- Signature-based detection is a time-consuming process as the database is enormous.
- Non-state actors usually come up with a new method to target the system. So, it is not a reliable technique to prevent such attacks.
- The attacker can adapt their attack to prevent the pattern from getting matched.
Also Read: How do I Run a Virus Scan on my Computer?
What is Non Signature Based Malware Detection?
To give protection against malicious code for which signatures are either not yet available or may not be effective, non-signature-based malware detection is used. Heuristics are a type of non signature-based detection method that can be used to identify, characterize, and describe the traits or behavior of malicious code.
We hope this article helped you understand what is signature-based detection. Feel free to reach out to us with your queries and suggestions via the comments section below. Also, let us know what you want to learn about next.