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Detecting and neutralizing encrypting Ransomware attacks by using machine-learning techniques: A literature review

Abstract:

Almost immediatelyafter the initial design and implementation of first computers systemsaccessibleto the general public and businesses, computer programs socalled viruses and malware appeabkp_redinto computing andinformatics scenario, representing a big threat to normal informaticsapplications operation, and in most cases causing lossof time, data, and huge amount of money. Thereforea lot of research has been done to produce software capable of protecting businessesan individual user fromthis terrible and annoying menace. Among theseviruses and malware threats, one has gotten a lot of attention lately, namely, ransomeware malware, which is capable of avoiding most of important and expensive antivirus and antimalware applications, and starts encrypting and modifying files and directories, with the purpose of asking for money in exchangeof some keyneeded to be able to hopefully recover the affected data in the computer system. The present researchwork is focused in investigating current literature in this field in order to determine the state of the art regarding malware prevention, detection, andrecovery (curing) when a computer system is attacked by virus and malware, and in particular by the so called ransomwareone.