Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/588908
Title: An Efficient Deep Learning Framework for Android Malware Detection
Researcher: Lakshman Rao A
Guide(s): Shashi M
Keywords: Computer Science
Computer Science Software Engineering
Engineering and Technology
University: Andhra University
Completed Date: 2023
Abstract: Cybersecurity affects every aspect of our lives, whether or not we are conscious newlineof it. The term quotcyber securityquot encompasses any measures used to prevent harm to or newlineunauthorized access to digital resources such as computers, mobile devices, and newlinesoftware. Some of the major issues in cyber security are spam detection, intrusion newlinedetection, malware detection, etc. Among several cyber security issues, malware newlinedetection is one of the most important research areas in cyber security. Any software newlinedesigned to cause damage to a computer, mobile device, network, or server is called newlinemalware. Malware is a short term for quotmalicious softwarequot. Malicious software comes newlinein many forms, including viruses, spyware, worms, Trojan horses, rootkits, adware, newlinebotnets, and many more. Malware can be influenced by both PCs and mobile devices. newlineBut, there is a difference between PC malware and mobile malware. PC malware also newlinehas differences based on the operating system used. For example, the malware on a newlineWindows PC is different from the malware on a Linux PC. newlineWith the introduction of smartphones, mobile phone usage has increased newlinedramatically. The advent of smartphones has altered many aspects of our culture, newlineincluding media consumption, commerce, and day-to-day life. While security newlinesoftware is routinely used on laptops and desktops, the vast majority of mobile newlinedevices lack security protection and are thus susceptible to a new and rising kind of newlinemobile malware. The detection mechanisms used for mobile malware detection are newlinedifferent from those used for PC malware. The two most widely used mobile newlineoperating systems are Android and iOS. The market shares of the Android and iOS newlineoperating systems are 71% and 27%, respectively. So, there is a need to focus more newlineon Android malware detection. The Android operating system is a mobile operating newlinesystem developed by Google. It is based on the Linux environment. newlineThe most commonly used programming language for creating Android newlineapplications is Java. An Android application is an archived file
Pagination: 168 Pg
URI: http://hdl.handle.net/10603/588908
Appears in Departments:Department of Computer Science & Systems Engineering

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01_title.pdfAttached File176.99 kBAdobe PDFView/Open
02_prelim pages.pdf126.76 kBAdobe PDFView/Open
03_abstract.pdf100.65 kBAdobe PDFView/Open
04_content.pdf79.8 kBAdobe PDFView/Open
05_chapter 1.pdf693.02 kBAdobe PDFView/Open
06_chapter 2.pdf469.09 kBAdobe PDFView/Open
07_chapter 3.pdf1.6 MBAdobe PDFView/Open
08_chapter 4.pdf2.46 MBAdobe PDFView/Open
09_chapter 5.pdf1.13 MBAdobe PDFView/Open
10_chapter 6.pdf1.8 MBAdobe PDFView/Open
11_chapter 7.pdf391.95 kBAdobe PDFView/Open
12_annexure.pdf3.31 MBAdobe PDFView/Open
80_recommendation.pdf2.03 MBAdobe PDFView/Open
9743 - annemneedi lakshmanarao @ award.pdf2.35 MBAdobe PDFView/Open
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