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- W3122692018 abstract "Contemporaneously, Security is a major mission in technological world, irrespective of domains, fields and technologies. Like other areas, Big Data and IOT too experiencing security issues, threats and attacks in every single minute. These attacks can be on different components of Big Data and IOT, like data stored on various nodes, clusters, propagated through networks, and via various components of the system or sensors. Big data security deals with the measures, techniques and tools used to protect both the data and analytics methods from attacks, threats, or other unauthorized activities. In this paper, To apply Security measures to overcome vulnerability of infrastructure, proposed a method called Malware Detection Kit (MDK). MDK comprises of static and dynamic analysis. Malware detection kit identifies attacks and threats. To detect attacks analysis is performed in two iterations. Whenever a new data enters into system, data undergoes first iteration of MDK, by static analysis it identifies threats if any. In the second iteration, file is submitted to automated dynamic analysis tools. The tool reports whether the file is malware on benign. Static Analysis is done by using Random Forest classifier, it produced high accuracy and low error rate for Malgenome dataset. Dynamic analysis is done by using automated sandboxes. Finally, this method recognises whether the file is benign or malware." @default.
- W3122692018 created "2021-02-01" @default.
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- W3122692018 date "2021-01-01" @default.
- W3122692018 modified "2023-09-27" @default.
- W3122692018 title "Malware Detection Kit for Malware Analysis of Big Data" @default.
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- W3122692018 doi "https://doi.org/10.1007/978-981-15-9293-5_17" @default.
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