Predictive malware threat mitigation

Abstract

The invention relates to predictive malware threat mitigation. The subject disclosure is directed towards protecting against malware, by classifying a user's risk level, which corresponds to a likelihood of malware being activated. To make the classification, data is collected that represents a probability of encountering malware, a probability of a user activating that malware, and the impact to the machine is activated. The classification maps to a protection level, which may be dynamically adjustable, e.g., based upon current risk conditions. The protection level determines a way to mitigate possible damage, such as by running a program as a virtualized program, running a virtualized operating system, or sandboxing a process.

Description

technical field [0001] The present invention relates to protection against malware. Background technique [0002] Via the Internet, individuals and organizations with malicious intent develop software that damages computer systems and / or is used to steal personal information from users (including individual users or entities such as corporations). Such malicious software often exploits code vulnerabilities and / or tricks the user into taking certain actions to cause the code holes to be installed on the user's computer system. [0003] One way to protect against malware is through anti-malware software. Contemporary anti-malware software uses a variety of mechanisms to catch and quarantine malware. In most cases, use signatures, behavior monitoring, and filter drivers to protect users from software that would otherwise damage their computers. [0004] Current anti-malware technology leads to a cycle in which malware authors try to outsmart anti-malware developers and vice ...

AI Technical Summary

Problems solved by technology

More specifically, many end users complain that any anti-malware application is intrusive, creates performance bottlenecks, hogs application CPU cycles, and sometimes locks certain files from use

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