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@article{151468, author = {Megha Nayanshi and Km Gunjan and Sony Saini and Dr. Ankit Kumar}, title = {Malware detection using ML}, journal = {International Journal of Innovative Research in Technology}, year = {}, volume = {8}, number = {1}, pages = {67-71}, issn = {2349-6002}, url = {https://ijirt.org/article?manuscript=151468}, abstract = {Malware is a set of different programs or any software which has a primary aim of trying to cause the damage/harm to a computer, computer network, client, or a server. Malware starts damaging the system after it is introduced into the target's computer and it can take any form such as scripts, so-called "active content" (Microsoft Windows), code which can directly execute and/or other forms of data. There are some malwares that are mostly referred as computer viruses, Trojan horses, scareware, ransomware, adware, spyware, and worms etc. To investigate that how we can implement machine learning technique on malware detection for the purpose of detecting any unknown malware, for developing a software that implements machine learning for detecting the unfamiliar malware & to validate that. Malware detection that uses machine learning will be capable to obtain high accuracy rate with the less false positive rate}, keywords = {}, month = {}, }
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