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Ransomware dataset based on dynamic analysis

Abstract:

Ransomware attacks have become a serious threat to the security of information worldwide, so that the scientific community makes great efforts to detect and prevent this type of attack. A fundamental part of this process is the collection of attack information through tools such as Cuckoo Sandbox. Currently, there are no public databases with information on this type of attack, or failing that, they are not described in detail. In this context, this work proposes the creation of a public Dataset and indicates the parameters that have been selected. A statistical analysis of the selected characteristics such as network behavior and use of processes of the victim system during the infection phase of a system (Windows XP and Windows 7) is presented. Finally, the information is processed, and a Dataset that associates the five samples of ransomware used (CryptoLocker, CryptoWall, PetrWrap, Petya and WannaCry) is created.