This book offers in-depth analysis of security vulnerabilities in different mobile operating systems. It provides methodology and solutions for handling Android malware and vulnerabilities and transfers the latest knowledge in machine learning and deep learning models towards this end.
This book offers in-depth analysis of security vulnerabilities in different mobile operating systems. It provides methodology and solutions for handling Android malware and vulnerabilities and transfers the latest knowledge in machine learning and deep learning models towards this end.
Shivi Garg has Doctor of Philosophy in December 2021 from Information Technology Department, Indira Gandhi Delhi Technical University for Women, (IGDTUW), Delhi, India. Thesis title: Design and Analysis of Mobile Application Vulnerabilities. She is also a post graduate in Information security from Delhi Technological University (DTU) Delhi, India. She has teaching and research experience since August 2016. Currently she is an Assistant Professor at J.C. Bose University of Science & Technology, YMCA, Faridabad. Her research interests include- Information Security, mobile security, cyber security, and Machine learning. Her publication and other details can be found at: https://sites.google.com/view/shivigarg/home Niyati Baliyan is an Assistant Professor, Department of Computer Engineering, National Institute of Technology Kurukshetra, Haryana. She has attained Doctor of Philosophy from Computer Science Department, Indian Institute of Technology (IIT) Roorkee, India. Her thesis title was "Quality Assessment of Semantic Web based Applications". She also has a Post Graduate Certificate in Information Technology from Sheffield Hallam University, Sheffield, U.K.Niyati obtained Chancellor's Gold Medal for being University topper during post graduate studies at Gautam Buddha University. She is co-author of "Semantic Web Based Systems: Quality Assessment Models, SpringerBriefs in Computer Science",2018. Her research interests include-Knowledge Engineering, Machine Learning, Healthcare analytics, Recommender systems, Information Security, and Natural Language Processing. Her publication and other details can be found at: https://sites.google.com/site/niyatibaliyan.
Inhaltsangabe
1. Introduction. 2. Background. 3. Relevant Works and Studies Related to Android and iOS. 4. A Parallel Classifier Scheme for Vulnerability Detection in Android. 5. Classification of Android Malware Using Ensemble Classifiers. 6. Text Processing-Based Malware-to-Vulnerability Mapping for Android. 7. Android Vulnerabilities Impact Analysis on Availability, Integrity, and Confidentiality Triad at the Architectural Level. 8. Conclusion and Future Directions.
1. Introduction. 2. Background. 3. Relevant Works and Studies Related to Android and iOS. 4. A Parallel Classifier Scheme for Vulnerability Detection in Android. 5. Classification of Android Malware Using Ensemble Classifiers. 6. Text Processing-Based Malware-to-Vulnerability Mapping for Android. 7. Android Vulnerabilities Impact Analysis on Availability, Integrity, and Confidentiality Triad at the Architectural Level. 8. Conclusion and Future Directions.
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