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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Volume 10 | Issue 12
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 10
Issue Published : 115
Article Submitted : 19459
Article Published : 8041
Total Authors : 21252
Total Reviewer : 769
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| Paper Title: | Cyber Threat Analysis on Android apps using Machine Learning Algorithms |
| Authors Name: | DR. T. Sunil Kumar , Y. Teja Manikanta , P. V. V. Vamsi , L. Sandeep , K. Pavan Kumar |
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IJRTI_202273
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| Published Paper Id: | IJRTI2504099 |
| Published In: | Volume 10 Issue 4, April-2025 |
| DOI: | http://doi.one/10.1729/Journal.44771 |
| Abstract: | Android apps have become a popular target for cyber threats due to their widespread adoption and open nature. The previous studies have used various methods like static, dynamic and hybrid analysis methods. These methods are used for detecting cyber threats that helps users to overcome data breaches. In this project, static analysis is performed on support vector machine algorithm to detect malware using malware detection schema. Genetic algorithm is the process of extracting features (only relevant data) from the data gathered from permissions, API – calls (Application Program Interface). This gathered data is then trained using Support Vector Machine (SVM) and Artificial Neural Network (ANN) algorithms. The result generated after testing is used to identify malware in the app. This result shows the malware detection in app's data. The proposed malware detection schema is able to identify malicious android applications efficiently. |
| Keywords: | Android Malware, SVM, ANN, API calls, Permissions |
| Cite Article: | "Cyber Threat Analysis on Android apps using Machine Learning Algorithms", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 4, page no.a781-a786, April-2025, Available :http://www.ijrti.org/papers/IJRTI2504099.pdf |
| Downloads: | 000325 |
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2504099
Registration ID:202273
Published In: Volume 10 Issue 4, April-2025
DOI (Digital Object Identifier): http://doi.one/10.1729/Journal.44771
Page No: a781-a786 Country: Visakhapatnam, Andhra Pradesh, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2504099 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2504099 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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