Loading...
Please wait, while we are loading the content...
Similar Documents
Malware Classification using Naïve Bayes Classifier for Android
| Content Provider | Semantic Scholar |
|---|---|
| Author | Koundel, Deepak Ithape, Suraj Khobaragade, Vishakha Jain, Rajat |
| Copyright Year | 2014 |
| Abstract | -ABSTRACT-In the global world of mobile technology millions of users connect and share on unknown networks without being aware of vulnerability of their confidentiality. Android platform is most popular OS among the smart phones users as well as developers, its open and flexible nature allows a large community to upload and download applications. Such extensive usage makes it an easy target for attack and misuse. A malicious application may steal the confidential data of user and upload it on its server, which is a threat to user's security. In this paper, we propose an approach to classify an application as malware or benign app by using data mining. To categorize an application we use various attributes of an app:(i) the permissions used by an application, (ii) battery usage rating based on permissions and (iii)rating acquired by the application on Android market. We apply Naive Bayes classifier to deduce the results based on the probability of an application being malware or not. These results are uploaded on the cloud where a user can view the results and query an application as being malicious or not to our server. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://theijes.com/papers/v3-i4/Version-2/I03402059063.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
