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InstDroid: A Light Weight Instant Malware Detector for Android Operating Systems

Saba Arshad, Rabia Chaudhary, Munam Ali, Neshmia Hafeez, Muhammad Kamran
2017 International Journal of Advanced Computer Science and Applications  
This research proposes a light weight instant malware detector, named as InstDroid, for Android devices that can identify the malicious applications immediately.  ...  are still resource inefficient and takes longer time to detect the malicious behavior of applications.  ...  As mobile devices are resource constrained due to which malware detection systems cannot perform detailed and effective analysis on mobile devices.  ... 
doi:10.14569/ijacsa.2017.080822 fatcat:tlshfm27urd2ba25c5o2nxqjx4

Survey on Mobile Malware Analysis and Detection

K Swetha, K V.D.Kiran
2018 International Journal of Engineering & Technology  
This paper provides overview on malware classification, methodologies of assessment, analysis and on and off device detection methods on android.  ...  On account of particular qualities of mobiles such as constrained assets, user action and neighborhood correspondence ability, consistent system network, versatile malware detection faces new difficulties  ...  Because of the particular qualities of mobiles, for example, constrained assets and steady network, malware detection presents new difficulties, particularly on unique dynamic malware detection.  ... 
doi:10.14419/ijet.v7i2.32.15584 fatcat:sehu4yjgl5ddtcs3o7z6s4kuha

SAMADroid: A Novel 3-Level Hybrid Malware Detection Model for Android Operating System

Saba Arshad, Munam A. Shah, Abdul Wahid, Amjad Mehmood, Houbing Song, Hongnian Yu
2018 IEEE Access  
For accurate malware detection, multilayer analysis is required which consumes large amount of hardware resources of resource constrained mobile devices.  ...  A large number of malware analysis and detection systems have been developed which uses static analysis, dynamic analysis, or hybrid analysis to keep Android devices secure from malware.  ...  On-device hybrid analysis helps to generate the quick analysis results but mobile devices are usually resource constrained and requires more hardware resources to perform the hybrid analysis on the device  ... 
doi:10.1109/access.2018.2792941 fatcat:vvrkm6rqx5agfelqxtg2s44vqm

A Friend or a Foe? Detecting Malware using Memory and CPU Features

Jelena Milosevic, Miroslaw Malek, Alberto Ferrante
2016 Proceedings of the 13th International Joint Conference on e-Business and Telecommunications  
For this purpose, we identify an optimized set of features to be monitored at runtime on mobile devices as well as detection algorithms that are suitable for battery-operated environments.  ...  However, due to the fact that IoT devices are resource-constrained, it is difficult to provide effective solutions.  ...  It is usually lightweight and suitable for the limited resources of mobile devices.  ... 
doi:10.5220/0005964200730084 dblp:conf/secrypt/MilosevicMF16 fatcat:44guaswpgnbftpmdsninjjxjoq

Host-Based Detection and Analysis of Android Malware

Moses Ashawa, Sarah Morris
2019 International Journal for Information Security Research  
Though there are a lot of anti-virus programs for malware detection designed with varying degrees of signatures for this purpose, many don't give analysis of what the malware does.  ...  A general detection and classification of the Android malware corpus was performed using K-means clustering algorithm.  ...  This approach provides analytical information about the activities of the malware on the android device, it can also be applied for other types of mobile operating system.  ... 
doi:10.20533/ijisr.2042.4639.2019.0100 fatcat:7zqrmcrm3fd5bk5zaiser7jgjq

Android Code Protection via Obfuscation Techniques: Past, Present and Future Directions [article]

Parvez Faruki (Malaviya National Institute of Technology Jaipur, India) and Hossein Fereidooni and Vijay Laxmi and Mauro Conti, Manoj Gaur (Malaviya National Institute of Technology Jaipur, India)
2016 arXiv   pre-print
Mobile devices have become ubiquitous due to centralization of private user information, contacts, messages and multiple sensors.  ...  We believe that, there is a need to investigate efficiency of the defense techniques used for code protection.  ...  The Android platform customized "vanilla" kernel for resource constrained mobile devices.  ... 
arXiv:1611.10231v1 fatcat:qvx7bm553vcutfhclemlpwaozi

Malware Detection & Prevention in Android Mobile by using Significant Permission Identification & Machine Learning

Ms. Kirti Reddy
2020 International Journal for Research in Applied Science and Engineering Technology  
Malware is today one of the biggest security threat to internet.  ...  People today use terms such as malware, spyware, or ransomware much more than the term "virus" where Malware can steal your information, make your device send SMS messages to premium rate text services  ...  Android is the most popular mobile operating system market share of 80 per cent, but as a result it is often the most malware-targeted device.  ... 
doi:10.22214/ijraset.2020.6046 fatcat:atbikmtpjbhdxnlkowshtbjq6a

A Comprehensive Review of Android Security: Threats, Vulnerabilities, Malware Detection, and Analysis

Saket Acharya, Umashankar Rawat, Roheet Bhatnagar, Bharat Bhushan
2022 Security and Communication Networks  
The popularity and open-source nature of Android devices have resulted in a dramatic growth of Android malware.  ...  The proposed model can efficiently detect, characterize, and provide a familial classification of Android malware with a good accuracy rate.  ...  Resource management: this layer is responsible for allocating and managing resources. Mobile data used by Android applications can be checked using device settings option.  ... 
doi:10.1155/2022/7775917 fatcat:ux2eun5y4bbfxlqkc36glj2fxq

Characterizing Evaluation Practicesof Intrusion Detection Methodsfor Smartphones

J. Alzahran Abdullah, Nataliav Stakhanoa, Hugo Gonzalezand Ali, A. Ghorbani
2014 Journal of Cyber Security and Mobility  
Mobile malware, a dominant threat for modern mobile devices, was almost non-existent before the official release of the Android platform in 2008.  ...  The rapid development of mobile platform apps and app markets coupled with the open nature of the Android platform triggered an explosive growth of specialized malware and subsequent search for effective  ...  At the same time, there are several specificities that make traditional IDSs not suitable for mobile devices: • Constrained resources: the resource-constrained environment of smartphones puts strict limitations  ... 
doi:10.13052/jcsm2245-1439.321 fatcat:3eltcf7r6fcdrp6os4vyleyjpq

A Note on Latency Variability of Deep Neural Networks for Mobile Inference [article]

Luting Yang, Bingqian Lu, Shaolei Ren
2020 arXiv   pre-print
not limited to different devices and different levels of CPU resource contention considered in this note.  ...  In this note, we conduct a preliminary measurement study on the latency variability of DNNs for mobile inference.  ...  latency of DNN-based image classification on mobile devices.  ... 
arXiv:2003.00138v1 fatcat:va2e5zlubvf57favc2h4u7g77q

Analysis of Android Malware Detection Techniques in Deep Learning

Neetu Agarwal, Vipin Jain, Raju K Ranjan
2020 SKIT research journal  
Android users have been strained most because of Android's open nature. Throughout this time, efforts have been made to devise software and methods to detect android malwares.  ...  This has captivated malware authors' attention. Malware attacks in various forms has troubled users by stealing their personal information, banking information and much more.  ...  Types of mobile malwares that can harm the mobile devices are spyware, ransomware, virus, trojans, worms, bot processes and crypto mining.  ... 
doi:10.47904/ijskit.10.2.2020.21-26 fatcat:sbjbjpx4n5hjdk3lvou7gqw5ui

User Privacy and Data Flow Control for Android Apps: Systematic Literature Review

Zainab Rashid Alkindi, Mohamed Sarrab, Nasser Alzeidi
2021 Journal of Cyber Security and Mobility  
Our thorough examination of the relevant literature has led to a critical analysis of the proposed solutions with a focus on user privacy extensions and mechanism for the Android mobile platform.  ...  Android mobile apps gain access to numerous users' private data. Users of different Android mobile apps have less control over their sensitive data during their installation and run-time.  ...  In 2006, [109] provided an information tracking mechanism based on resource classification.  ... 
doi:10.13052/jcsm2245-1439.1019 fatcat:ztxz4fikrnax3lxiuvir22dvdm

Behavioral detection of malware on mobile handsets

Abhijit Bose, Xin Hu, Kang G. Shin, Taejoon Park
2008 Proceeding of the 6th international conference on Mobile systems, applications, and services - MobiSys '08  
We also find that the time and resource overheads of constructing the behavior signatures from lowlevel API calls are acceptably low for their deployment in mobile devices.  ...  A novel behavioral detection framework is proposed to detect mobile worms, viruses and Trojans, instead of the signature-based solutions currently available for use in mobile devices.  ...  Joseph and the anonymous reviewers for their constructive comments and helpful advice.  ... 
doi:10.1145/1378600.1378626 dblp:conf/mobisys/BoseHSP08 fatcat:n6b5xgygqval5claabarxyfnca

Comparing the Efficiency of Malware Detection in Android System

Badal Sharma
2022 International Journal for Research in Applied Science and Engineering Technology  
As a result of its open-source design, the Android OS is endless in the versatile business today. It is a wide assortment of uses and essential highlights.  ...  Application clients will generally trust the Android Operating System to get information; however, it is being demonstrated that Android is more defenseless and eccentric. of concern.  ...  Dynamic analysis is more accurate and time-consuming than static analysis, but it has a high computing overhead that prevents it from being used on mobile devices with limited resources.  ... 
doi:10.22214/ijraset.2022.45373 fatcat:tccaf2muenflzcatfjb6x4i3ym

Andro-profiler: Detecting and Classifying Android Malware based on Behavioral Profiles [article]

Jae-wook Jang and Jaesung Yun and Aziz Mohaisen and Jiyoung Woo and Huy Kang Kim
2016 arXiv   pre-print
In this paper, we contribute to the mobile security defense posture by introducing Andro-profiler, a hybrid behavior based analysis and classification system for mobile malware.  ...  Mass-market mobile security threats have increased recently due to the growth of mobile technologies and the popularity of mobile devices.  ...  The availability of this information in many mass-market mobile devices makes them a desirable target for hackers, who excelled at developing a large number of mobile malicious software (malware), making  ... 
arXiv:1606.01403v1 fatcat:3riflksanrc4hkojaz7pdn6mfm
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