Final answer:
Anti-virus software primarily identifies infected files using virus signatures and heuristic analysis. It also employs behavioral detection and machine learning algorithms to adapt to new cyber threats.
Step-by-step explanation:
The main means by which anti-virus software identifies infected files is through the use of virus signatures, which are unique strings of data or characteristics that indicate the presence of a specific virus. Anti-virus programs maintain a database of virus signatures and use it to scan files and detect potential viruses. Additionally, anti-virus software may use heuristic analysis to identify new viruses or variants that have not yet been catalogued by examining how programs behave, identifying suspicious behavior that might indicate an infection. Another method employed is behavioral detection, wherein the software monitors the behavior of programs and flags those that perform actions typically associated with malware, like replicating itself or encrypting files in the manner of ransomware. As cyber threats evolve, so do the detection methods of anti-virus software, incorporating more sophisticated machine learning algorithms to anticipate and counteract novel virus strategies.
Anti-virus software identifies infected files through various means, but one of the main methods is using virus signatures. These signatures are unique patterns, or code snippets, that are associated with specific viruses. When the software scans a file, it compares the contents of the file to its extensive database of virus signatures. If it finds a match, it identifies the file as infected. For example, let's say there is a virus called 'ABC' that has a specific code pattern. The anti-virus software will have the signature for 'ABC' stored in its database. When the software scans a file and finds the same code pattern, it knows that the file is infected with the 'ABC' virus. It's important to note that anti-virus software also uses various other detection methods, such as behavior monitoring, heuristics, and machine learning algorithms, to identify and prevent infections.