Search Results - (( problem based malware algorithm ) OR ( java implication based algorithm ))
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Maldroid- attribute selection analysis for malware classification
Published 2019“…A major problem with malware detection is the existence of numerous features in malware code and the need to look at the relevant features in malware analysis. …”
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Ensemble based categorization and adaptive model for malware detection
Published 2011“…Previously was a primitive and easy to detect, it evolves to a sophisticated and professionally written piece of software. Current malware detection method involved string search algorithm which based on the pattern detection. …”
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Android malware detection using permission based static analysis
Published 2023“…There have been many studies on permission-based Android malware detection. In this study, a permission-based Android malware system is analyzed. …”
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A malware analysis and detection system for mobile devices / Ali Feizollah
Published 2017“…We then used feature selection algorithms and deep learning algorithms to build a detection model. …”
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A novel framework for identifying twitter spam data using machine learning algorithms
Published 2020“…Previous studies have approached spam detection as a classification problem, high dimension, time-consuming problem, which requires new methods to address the problems. …”
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Classification of polymorphic virus based on integrated features
Published 2018“…Standard virus classification relies on the use of virus function, which is a small number of bytes written in assembly language. The addressable problem with current malware intrusion detection and prevention system is having difficulties in detecting unknown and multipath polymorphic computer virus solely based on either static or dynamic features. …”
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Towards cross-site scripting vulnerability detection in mobile web applications
Published 2018“…It proposes an enhanced genetic algorithm-based approach that detects cross-site scripting vulnerabilities in mobile versions of web applications. …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method
Published 2024thesis::doctoral thesis -
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An enhanced android botnet detection approach using feature refinement
Published 2019“…The experimental and statistical tests show that 97.28% accuracy achieved by Random Forest machine classifier, it performs well as compared to other classification algorithms. Based on the test results, various open research issues which need to be addressed in future studies are highlighted.…”
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