Detection of Malware and Rank Fraud Search in Google Play

Authors(2) :-Sravani, K. S. Yuvaraj

The utilization of mobile devices including Tablets, Smart watch, and journals are expanding step by step. Android has the real offer in the versatile application showcase. Android versatile applications turn into a simple focus for the assailants due to its open source condition. Additionally client's numbness the way toward introducing and use of the applications. To distinguish counterfeit and malware applications, all the past techniques concentrated on getting authorization from the client and executing that specific portable application. Malware identification systems that find and break follows left behind by deceitful engineers, to identify seek rank extortion and malware in Google Play. The extortion application is distinguished by conglomerating the three bits of confirmation, for example, positioning b3ased, co-audit based and rating based proof. At long last amassing every one of the exercises of front running applications, it can be accomplish sure precision in arranging considerate standard datasets of malware, false and honest to goodness applications. Also, I apply incremental learning way to deal with describe a substantial number of informational collections. It consolidated viably for every one of the confirmations for misrepresentation recognition. To precisely find the positioning extortion, there is a need to mining the dynamic time frame's to be specific driving sessions, of versatile Apps

Authors and Affiliations

Sravani
PG Scholar,Dept of MCA,St.Annís College of Engineering & Technology, Chirala, Andhra Pradesh, India
K. S. Yuvaraj
Ass.Professor,Dept of MCA, St.Annís College of Engineering & Technology, Chirala, Andhra Pradesh, India

Mobile applications, Malware, Ranking, Rating, Google Play.

  1. Alaa Salman Imad H. Elhajj Ali Chehab Ayman Kayss, IEEE Mobile Malware Exposed. International Conference on Knowledge discovery and data mining, KDD’14 pages 978- 983.
  2. Alfonso Munoz, Ignacio Mart '?n, Antonio Guzman, Jos ' e Alberto Hern ' andez, IEEE Android malware detection from Google Play meta-data: Selection of important features.2015, pages,245-251.
  3. Chia-Mei Chen, Je-Ming Lin, Gu-Hsin Lai,IEEE Detecting Mobile Application Malicious Behaviors Based on Data Flow of Source Code.2014 International Conference on Trustworthy Systems and their Applications pp 95-109.
  4. D. F. Gleich and L.-h. Lim. Rank aggregation via nuclear norm minimization. In Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining, KDD ’11, pages 60-68, 2011.Y.T. Yu, M.F. Lau, "A comparison of MC/DC, MUMCUT and several other coverage criteria for logical decisions", Journal of Systems and Software, 2005, in press.
  5. E.-P. Lim, V.-A. Nguyen, N. Jindal, B. Liu, and H. W. Lauw. Detecting product review spammers using rating behaviors. In Proceedings of the 19th ACM international conference on Information and knowledge management, CIKM ’10, pages 939-948, 2010.
  6. N. Jindal and B. Liu, “Opinion spam and analysis,” in Proc. Int. Conf. Web Search Data Mining, 2008, pp. 219- 230.
  7. J. Oberheide and C. Miller, “Dissecting the Android Bouncer,” presented at the SummerCon2012, New York, NY, USA, 2012.
  8. K.Shi and K.Ali. Getjar mobile application recommendations with very sparse datasets. In Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining, KDD ’12, pages 204-212, 2012.
  9. J.Kivinen and M. K. Warmuth, “Additive versus exponentiated gradient updates for linear prediction,” in Proc. 27th Annu. ACM Symp. Theory Comput., 1995, pp. 2014.
  10. N. Spirin and J. Han. Survey on web spam detection: principles and algorithms. SIGKDD Explor. Newsl.,13 (2):50-64,May2012.

Publication Details

Published in : Volume 4 | Issue 7 | March-April 2018
Date of Publication : 2018-04-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 70-75
Manuscript Number : IJSRSET184498
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

Sravani, K. S. Yuvaraj, " Detection of Malware and Rank Fraud Search in Google Play, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 7, pp.70-75, March-April.2018
URL : http://ijsrset.com/IJSRSET184498

Follow Us

Contact Us