CERTAIN INVESTIGATIONS ON VARIOUS ALGORITHMS THAT IS USED TO CLASSIFY MALWARE AND GOODWARE IN ANDROID APPLICATIONS
In recent trends, the mobile devices play a very vital role in day to day activities of human beings. Google Android OS appeared lately i.e., in September 2008 in mobile market and gains more popularity. Google Android OS offers more flexibility for the users by offering N number of free downloadabl...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
ICT Academy of Tamil Nadu
2016-10-01
|
| Series: | ICTACT Journal on Soft Computing |
| Subjects: | |
| Online Access: | http://ictactjournals.in/ArticleDetails.aspx?id=2700 |
| _version_ | 1818142543054897152 |
|---|---|
| author | B.P. Sreejith Vignesh M. Rajesh Babu |
| author_facet | B.P. Sreejith Vignesh M. Rajesh Babu |
| author_sort | B.P. Sreejith Vignesh |
| collection | DOAJ |
| description | In recent trends, the mobile devices play a very vital role in day to day activities of human beings. Google Android OS appeared lately i.e., in September 2008 in mobile market and gains more popularity. Google Android OS offers more flexibility for the users by offering N number of free downloadable applications to the users, which in turn gets changed as the superlative target for the attackers . As a result, many android applications that may contain the malware applications which are capable of stealing privacy information of users are available in market as a (.apk) file. The attackers started to target uneducated people and started stealing the information using applications. These applications request user to allow set of permissions during installation. For a new user it is difficult to identify the set of permissions that are harmful. This could be an advantage for malware intruders to access the data or infect the mobile device by introducing malware applications. Therefore, android malware detection various algorithms algorithm and Machine learning approaches is proposed to classify malware and goodware applications by analyzing the permission features. |
| first_indexed | 2024-12-11T11:17:26Z |
| format | Article |
| id | doaj.art-c526edd3ff384afb827dfbd5764fe7b4 |
| institution | Directory Open Access Journal |
| issn | 0976-6561 2229-6956 |
| language | English |
| last_indexed | 2024-12-11T11:17:26Z |
| publishDate | 2016-10-01 |
| publisher | ICT Academy of Tamil Nadu |
| record_format | Article |
| series | ICTACT Journal on Soft Computing |
| spelling | doaj.art-c526edd3ff384afb827dfbd5764fe7b42022-12-22T01:09:17ZengICT Academy of Tamil NaduICTACT Journal on Soft Computing0976-65612229-69562016-10-017113441349CERTAIN INVESTIGATIONS ON VARIOUS ALGORITHMS THAT IS USED TO CLASSIFY MALWARE AND GOODWARE IN ANDROID APPLICATIONSB.P. Sreejith Vignesh0M. Rajesh Babu1Bharathiar University, IndiaKarpagam College of Engineering, IndiaIn recent trends, the mobile devices play a very vital role in day to day activities of human beings. Google Android OS appeared lately i.e., in September 2008 in mobile market and gains more popularity. Google Android OS offers more flexibility for the users by offering N number of free downloadable applications to the users, which in turn gets changed as the superlative target for the attackers . As a result, many android applications that may contain the malware applications which are capable of stealing privacy information of users are available in market as a (.apk) file. The attackers started to target uneducated people and started stealing the information using applications. These applications request user to allow set of permissions during installation. For a new user it is difficult to identify the set of permissions that are harmful. This could be an advantage for malware intruders to access the data or infect the mobile device by introducing malware applications. Therefore, android malware detection various algorithms algorithm and Machine learning approaches is proposed to classify malware and goodware applications by analyzing the permission features.http://ictactjournals.in/ArticleDetails.aspx?id=2700AndroidMalware ApplicationPrincipal Component AnalysisCuckoo SearchPearson Correlation Coefficient |
| spellingShingle | B.P. Sreejith Vignesh M. Rajesh Babu CERTAIN INVESTIGATIONS ON VARIOUS ALGORITHMS THAT IS USED TO CLASSIFY MALWARE AND GOODWARE IN ANDROID APPLICATIONS ICTACT Journal on Soft Computing Android Malware Application Principal Component Analysis Cuckoo Search Pearson Correlation Coefficient |
| title | CERTAIN INVESTIGATIONS ON VARIOUS ALGORITHMS THAT IS USED TO CLASSIFY MALWARE AND GOODWARE IN ANDROID APPLICATIONS |
| title_full | CERTAIN INVESTIGATIONS ON VARIOUS ALGORITHMS THAT IS USED TO CLASSIFY MALWARE AND GOODWARE IN ANDROID APPLICATIONS |
| title_fullStr | CERTAIN INVESTIGATIONS ON VARIOUS ALGORITHMS THAT IS USED TO CLASSIFY MALWARE AND GOODWARE IN ANDROID APPLICATIONS |
| title_full_unstemmed | CERTAIN INVESTIGATIONS ON VARIOUS ALGORITHMS THAT IS USED TO CLASSIFY MALWARE AND GOODWARE IN ANDROID APPLICATIONS |
| title_short | CERTAIN INVESTIGATIONS ON VARIOUS ALGORITHMS THAT IS USED TO CLASSIFY MALWARE AND GOODWARE IN ANDROID APPLICATIONS |
| title_sort | certain investigations on various algorithms that is used to classify malware and goodware in android applications |
| topic | Android Malware Application Principal Component Analysis Cuckoo Search Pearson Correlation Coefficient |
| url | http://ictactjournals.in/ArticleDetails.aspx?id=2700 |
| work_keys_str_mv | AT bpsreejithvignesh certaininvestigationsonvariousalgorithmsthatisusedtoclassifymalwareandgoodwareinandroidapplications AT mrajeshbabu certaininvestigationsonvariousalgorithmsthatisusedtoclassifymalwareandgoodwareinandroidapplications |