首页|Findings from Tallinn University of Technology Reveals New Findings on Machine L earning (Machine Learning for Android Malware Detection: Mission Accomplished? a Comprehensive Review of Open Challenges and Future Perspectives)
Findings from Tallinn University of Technology Reveals New Findings on Machine L earning (Machine Learning for Android Malware Detection: Mission Accomplished? a Comprehensive Review of Open Challenges and Future Perspectives)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators publish new report on Ma chine Learning. According to news reporting originating from Tallinn, Estonia, b y NewsRx editors, the research stated, "The extensive research in machine learni ng based Android malware detection showcases high-performance metrics through a wide range of proposed solutions. Consequently, this fosters the (mis)conception of being a solved problem, diminishing its appeal for further research." Our news editors obtained a quote from the research from the Tallinn University of Technology, "However, after surveying and scrutinizing the related literature , this deceptive deduction is debunked. In this paper, we identify five signific ant unresolved challenges neglected by the specialized research that prevent the qualification of Android malware detection as a solved problem. From methodolog ical flaws to invalid postulates and data set limitations, these challenges, whi ch are thoroughly described throughout the paper, hamper effective, long-term ma chine learning based Android malware detection." According to the news editors, the research concluded: "This comprehensive revie w of the state of the art highlights and motivates future research directions in the Android malware detection domain that may bring the problem closer to being solved."
TallinnEstoniaEuropeCybersecurityCyborgsEmerging TechnologiesMachine LearningTallinn University of Technol ogy
NETL
NSTL
