Anti-attack malicious software identification method and system

Abstract

The invention discloses an anti-attack malicious software identification method and a system and is invented to aim at the defect that a traditional identification system is easily influenced by malicious attack in the prior art. The method includes the steps of setting parameters of an identifying device, converting software into vector quantity, utilizing the identifying device to identify the software, and outputting identification results. The method and the system can achieve intelligent identification for resisting impersonation attack of malicious software, and achieve technical effect of stable identification performance.

Description

technical field [0001] The invention relates to the technical field of computer communication, in particular to an anti-attack malicious software identification method and system. Background technique [0002] Malware is a computer program into which malicious code has been inserted. Computer malware is used to destroy computer systems and destroy important information without the user's knowledge, making the system unusable. It may also be used to collect private information, such as passwords, credit card accounts, etc., and even used to publish pornography and other bad information. With more and more users quickly connecting to the Internet through sophisticated computers, the widespread spread of these malicious software in the future will be very harmful. [0003] There are already many excellent technologies used to detect existing malicious programs, and anti-virus software has been applied quite maturely, such as McAfee, Norton and other anti-virus software have b...

AI Technical Summary

Problems solved by technology

Antivirus software usually detects executable code through known patterns, but this approach is problematic

One of the big disadvantages is that before malware can be detected, there must be a sample of this malware

That is to say, traditional malware identification systems cannot identify unknown malware

In order to identify unknown malware, people have proposed malware identification methods based on statistical methods, but such methods and systems are extremely vulnerable to malicious attacks, so they cannot be used normally

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