A zero-day resistant malware detection method for securing Cloud using SVM and Sandboxing Techniques

被引:0
|
作者
Kumar, Saket [1 ]
Singh, Chandra Bhim Bhan [1 ]
机构
[1] Natl Inst Technol Kurukshetra, Dept Comp Engn, Kurukshetra, Haryana, India
关键词
Cloud Computing; Machine Learning; SVM; n-class SVM; Zero-day resistance;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Cloud now a day has become the backbone of the IT infrastructure. Whole of the infrastructure is now being shifted to the clouds, and as the cloud involves all of the networking schemes and the OS images, it inherits all of the vulnerabilities too. And hence securing them is one of our very prior concerns. Malwares are one of the many other problems that have ever growing and hence need to be eradicated from the system. The history of malwares go long back in time since the advent of computers and hence a lot of techniques has also been already devised to tackle with the problem in some or other way. But most of them fall short in some or other way or are just too heavy to execute on a simple user machine. Our approach devises a 3 - phase exhaustive technique which confirms the detection of any kind of malwares from the host. It also works for the zero-day attacks that are really difficult to cover most times and can be of really high-risk at times. We have thought of a solution to keep the things light weight for the user.
引用
收藏
页码:1397 / 1402
页数:6
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