IDENTIFICATION SYSTEM FOR PERNICIOUS CODE ON ANDROID USING STATIC TECHNIQUES
Abstract & Details
Research Area
computer science
Keywords
Android application
Malware detection
static techniques
Abstract
Android Operating System is widely used mobile OS in the world. There is a high increment in pernicious apps in android phones. This paper is gear towards detecting malware application and proposes a technique that can detect any malware application in android phone using static techniques. It analyzes system calls’ logs and also the conduct of an app and afterward produces signatures for malware conduct. This research work provides an effective and efficient technique to detect malicious code in Android Application. The system was developed using Android Studio, Android SDK written with Java and XML. The Object Oriented Analysis and Design Methodology (OOADM) were used for the analysis, design and development of the system using Unified Modelling Language (UML) to model the system.
License
This work is licensed under a Creative
Commons
Attribution-ShareAlike 4.0 International License.
Author Information
| # | Name | Institute / Affiliation |
|---|---|---|
| 1 | OBAYI ADAORA ANGELA. | University of Nigeria, Nsukka (UNN), |
| 2 | AGBOKE ADEOLA J. | Cabel University, imota, lagos state |
| 3 | AJAYI, TAIWO DAVID | Cabel University, imota, lagos state |
| 4 | UZO BLESSING CHIMEZIE | University of Nigeria, Nsukka (UNN) |
| 5 | IKEDILO, OBIORA EMEKA | Akanu Ibaim Federal Polytechnic, Uwana |
| 6 | UGWU, MAUREEN. K | Enugu State polytechnic, Iwollo |
| 7 | NLEBEDIM, EMMANUEL ARINZE. | Real brain point schools |
How to Cite
Use the following formats to cite this article in your research.
APA Style
ANGELA., OBAYI ADAORA, J., AGBOKE ADEOLA, DAVID, AJAYI, TAIWO, CHIMEZIE, UZO BLESSING, EMEKA, IKEDILO, OBIORA, K, UGWU, MAUREEN., & ARINZE., NLEBEDIM, EMMANUEL (2021). IDENTIFICATION SYSTEM FOR PERNICIOUS CODE ON ANDROID USING STATIC TECHNIQUES. International Journal of Advance Research and Innovative Ideas In Education, 7(5), 789-796.
MLA Style
ANGELA., OBAYI ADAORA, et al. "IDENTIFICATION SYSTEM FOR PERNICIOUS CODE ON ANDROID USING STATIC TECHNIQUES." International Journal of Advance Research and Innovative Ideas In Education, vol. 7, no. 5, 2021, pp. 789-796.
IEEE Style
OBAYI ADAORA ANGELA., AGBOKE ADEOLA J., AJAYI, TAIWO DAVID, UZO BLESSING CHIMEZIE, IKEDILO, OBIORA EMEKA, UGWU, MAUREEN. K, and NLEBEDIM, EMMANUEL ARINZE., "IDENTIFICATION SYSTEM FOR PERNICIOUS CODE ON ANDROID USING STATIC TECHNIQUES," International Journal of Advance Research and Innovative Ideas In Education, vol. 7, no. 5, pp. 789-796, 2021.
Vancouver Style
ANGELA. OBAYI ADAORA, J. AGBOKE ADEOLA, DAVID AJAYI, TAIWO, CHIMEZIE UZO BLESSING, EMEKA IKEDILO, OBIORA, K UGWU, MAUREEN., et al. IDENTIFICATION SYSTEM FOR PERNICIOUS CODE ON ANDROID USING STATIC TECHNIQUES. International Journal of Advance Research and Innovative Ideas In Education. 2021;7(5):789-796.
Harvard Style
ANGELA., OBAYI ADAORA, J., AGBOKE ADEOLA, DAVID, AJAYI, TAIWO, CHIMEZIE, UZO BLESSING, EMEKA, IKEDILO, OBIORA, K, UGWU, MAUREEN., & ARINZE., NLEBEDIM, EMMANUEL (2021) 'IDENTIFICATION SYSTEM FOR PERNICIOUS CODE ON ANDROID USING STATIC TECHNIQUES', International Journal of Advance Research and Innovative Ideas In Education, 7(5), pp. 789-796.
Chicago Style
ANGELA., OBAYI ADAORA, et al. "IDENTIFICATION SYSTEM FOR PERNICIOUS CODE ON ANDROID USING STATIC TECHNIQUES." International Journal of Advance Research and Innovative Ideas In Education 7, no. 5 (2021): 789-796.
Turabian Style
ANGELA., OBAYI ADAORA, et al. "IDENTIFICATION SYSTEM FOR PERNICIOUS CODE ON ANDROID USING STATIC TECHNIQUES." International Journal of Advance Research and Innovative Ideas In Education 7, no. 5 (2021): 789-796.
Related Research
Comprehensive Review of Existing Chatbot Systems for Career Assistance, Resume Support, and ATS-Aware Guidance
PDF Unavailable
Development of an AI-Powered Multimodal Web Assistant with Intelligent Resume Building and ATS Enhancement
PDF Unavailable
A Deep Learning-Based Framework for Mood-Oriented Music Recommendation Using Facial Expression Analysis
PDF Unavailable
Survey On : Intelligent Payroll and Human Resource Management Systems: A Systematic Review of Automation, Security, and Analytics
PDF Unavailable
Civic Engagement & Empowerment Platform
PDF Unavailable
Recent Developments in Microneedle Technology and Its Diverse Biomedical Applications
PDF Unavailable
RAG System Development with Pydantic AI ChromaDB & Groq
PDF Unavailable
Machine Learning Based Early Stage Diabetes Detection System
PDF Unavailable
A Survey on Skillsense:AI Career Analyzer App
PDF Unavailable
Employee Performance Portal
PDF Unavailable