ISSN 2394-5125
 

Research Article 


HYBRID NAIVE BAYES-ADASVM BASED MALWARE PREDICTION IN MOBILE APPLICATIONS

Dr.S.Selvi, Mr.M.Sivakumar, Dr.M.Vimaladevi, Mr.U.Gowrisankar.

Abstract
Employing Mobile applications for secured and sensitive real time applications like banking, e-commerce, etc. is increasing day by day and it has created as an unbreakable bondage in our life survival. Simultaneously, there is a rise in danger and fraudulency targeting us primarily by invoking malware mobile apps. The identification and elimination of such malwares turned out into a serious challenge, since there is only inadequate availability of resources and restricted number of privileges granted to the users. Traditional methods based on structured features such as permissions and sensitive Application Programming Interface (API) lacks high-level behavioral semantics to detect evolving malware As a remedy for this issue, a Machine Learning approach collided with Support Vector Machine (SVM) is being proposed in this paper for leveraging higher computing power of a server or cluster of servers. In this paper, we proposed a novel Android malware detection method based on method-level correlation relationship of application’s abstracted API calls named Hybrid Naive Bayes-Adasvm Based Malware Prediction algorithm. We combine machine learning to identify the different behavioral patterns of malicious and benign apps to build the detection system. The results of our empirical evaluation would prove our system is competitive in terms of classification accuracy and detection efficiency. Experimentation has been carried out on Drebin(benign 5.9K and malware 5.6K) and AMD(benign 20.5K and malware 20.8K) datasets. It has been proved that proposed algorithm would achieve 96% and 98% detection results both in Accuracy and F-measure.

Key words: Malware Detection, SVM, Naïve-Bayes


 
ARTICLE TOOLS
Abstract
PDF Fulltext
How to cite this articleHow to cite this article
Citation Tools
Related Records
 Articles by Dr.S.Selvi
Articles by Mr.M.Sivakumar
Articles by Dr.M.Vimaladevi
Articles by Mr.U.Gowrisankar
on Google
on Google Scholar


How to Cite this Article
Pubmed Style

Dr.S.Selvi, Mr.M.Sivakumar, Dr.M.Vimaladevi, Mr.U.Gowrisankar. HYBRID NAIVE BAYES-ADASVM BASED MALWARE PREDICTION IN MOBILE APPLICATIONS. JCR. 2020; 7(9): 3186-3193. doi: 10.31838/jcr.07.09.485


Web Style

Dr.S.Selvi, Mr.M.Sivakumar, Dr.M.Vimaladevi, Mr.U.Gowrisankar. HYBRID NAIVE BAYES-ADASVM BASED MALWARE PREDICTION IN MOBILE APPLICATIONS. http://www.jcreview.com/?mno=24827 [Access: May 30, 2021]. doi: 10.31838/jcr.07.09.485


AMA (American Medical Association) Style

Dr.S.Selvi, Mr.M.Sivakumar, Dr.M.Vimaladevi, Mr.U.Gowrisankar. HYBRID NAIVE BAYES-ADASVM BASED MALWARE PREDICTION IN MOBILE APPLICATIONS. JCR. 2020; 7(9): 3186-3193. doi: 10.31838/jcr.07.09.485



Vancouver/ICMJE Style

Dr.S.Selvi, Mr.M.Sivakumar, Dr.M.Vimaladevi, Mr.U.Gowrisankar. HYBRID NAIVE BAYES-ADASVM BASED MALWARE PREDICTION IN MOBILE APPLICATIONS. JCR. (2020), [cited May 30, 2021]; 7(9): 3186-3193. doi: 10.31838/jcr.07.09.485



Harvard Style

Dr.S.Selvi, Mr.M.Sivakumar, Dr.M.Vimaladevi, Mr.U.Gowrisankar (2020) HYBRID NAIVE BAYES-ADASVM BASED MALWARE PREDICTION IN MOBILE APPLICATIONS. JCR, 7 (9), 3186-3193. doi: 10.31838/jcr.07.09.485



Turabian Style

Dr.S.Selvi, Mr.M.Sivakumar, Dr.M.Vimaladevi, Mr.U.Gowrisankar. 2020. HYBRID NAIVE BAYES-ADASVM BASED MALWARE PREDICTION IN MOBILE APPLICATIONS. Journal of Critical Reviews, 7 (9), 3186-3193. doi: 10.31838/jcr.07.09.485



Chicago Style

Dr.S.Selvi, Mr.M.Sivakumar, Dr.M.Vimaladevi, Mr.U.Gowrisankar. "HYBRID NAIVE BAYES-ADASVM BASED MALWARE PREDICTION IN MOBILE APPLICATIONS." Journal of Critical Reviews 7 (2020), 3186-3193. doi: 10.31838/jcr.07.09.485



MLA (The Modern Language Association) Style

Dr.S.Selvi, Mr.M.Sivakumar, Dr.M.Vimaladevi, Mr.U.Gowrisankar. "HYBRID NAIVE BAYES-ADASVM BASED MALWARE PREDICTION IN MOBILE APPLICATIONS." Journal of Critical Reviews 7.9 (2020), 3186-3193. Print. doi: 10.31838/jcr.07.09.485



APA (American Psychological Association) Style

Dr.S.Selvi, Mr.M.Sivakumar, Dr.M.Vimaladevi, Mr.U.Gowrisankar (2020) HYBRID NAIVE BAYES-ADASVM BASED MALWARE PREDICTION IN MOBILE APPLICATIONS. Journal of Critical Reviews, 7 (9), 3186-3193. doi: 10.31838/jcr.07.09.485