Virus Detection Methods
Detecting viruses is a critical component of computer security. Various methods are employed to identify and mitigate threats.
Signature-Based Detection
This method relies on a database of known virus signatures — unique strings of data or characteristics of known malicious code — to detect viruses. When a file matches a signature in the database, it is flagged as a virus.
Issues: This approach is only effective against known viruses. Virus creators can circumvent detection by changing the virus's signature, making it unrecognized by the database.
Polymorphic Viruses
Some viruses are designed to alter their code or signature, known as polymorphic viruses, making them harder to detect using signature-based methods.
Behavior-Based Detection
Behavior-based detection monitors the behavior of programs and flags any action that resembles typical malware behavior, such as unexpected changes to system settings or files.
Machine learning can greatly improve the efficiency of this detection method by learning and predicting malware behavior patterns.
False Positives and False Negatives
A false positive occurs when legitimate software is incorrectly identified as a virus, potentially leading to disruptions in system availability. A false negative happens when actual malware is not detected by the security system, posing a greater risk as it can affect the confidentiality, integrity, and availability of data.
The effectiveness of a virus detection system is also influenced by the base rate, which is the proportion of actual viruses within the systems being monitored. If the base rate of viruses is lower than the false positive rate, most alerts are likely to be incorrect.