A Case Study on Android Malware Analysis using Hindroid
Anu Varghese
, Dr.Jagadeesha S N
Background/Purpose: The improvement in technology made the smart phone more familiar to common people and also the current situation demands it. Most of the services are digitalized nowadays. This opened up a wide field for the hackers or intruders and the rate of cyber-attacks and cyber-crimes are high. The malware has turned into a major industry as hackers grow more sophisticated and professional. The defenders and hackers are in a race to defeat each other. Machine learning based techniques has shown a higher rate in successful malware detection. In this paper discusses about Hindroid, an intelligent android malware detection system based on structured heterogeneous information network, which uses a static analysis method to identify malware. It analyses the various relationships in API calls and creates higher level semantics. Design/Methodology/Approach: SWOT framework is being used to analyse and display the information gathered from scholarly articles, web articles, journals and other sources. Findings/Results: Compared with other detection methods, Hindroid claims to outperform with 98.6% accuracy. It claims 99.01% detection rate compared to other security products like clean master, lookout, Norton etc Originality/Value: This study gives an overview of Android Malware Analysis based on the various data collected. Paper Type: Research Analysis based on Case Study
"A Case Study on Android Malware Analysis using Hindroid", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.7, Issue 11, page no.739 - 746, November-2022, Available :https://ijsdr.org/papers/IJSDR2211101.pdf
Volume 7
Issue 11,
November-2022
Pages : 739 - 746
Paper Reg. ID: IJSDR_202605
Published Paper Id: IJSDR2211101
Downloads: 000347215
Research Area: Computer Science & Technology
Country: Ernakulam, Kerala, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
