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Monet: A User-oriented Behavior-based Malware Variants Detection System for Android
[article]
2016
arXiv
pre-print
Preserved Fulltext
Hence, we propose a framework to combine "runtime behavior" with "static structures" to detect malware variants. ...
Our experiments show that MONET can achieve around 99% accuracy in detecting malware variants. ...
Our aim is to design a new and novel user-oriented approach for malware detection to achieve the following goals: (1) resistant to malware variants and transformation attacks, (2) user-oriented and easy ...
arXiv:1612.03312v1
fatcat:jrd4eke62zelzpakbzwhmeeba4
Android Malware Detection using Markov Chain Model of Application Behaviors in Requesting System Services
[article]
2017
arXiv
pre-print
Preserved Fulltext
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Widespread growth in Android malwares stimulates security researchers to propose different methods for analyzing and detecting malicious behaviors in applications. ...
In this paper, we propose ServiceMonitor, a lightweight host-based detection system that dynamically detects malicious applications directly on mobile devices. ...
[12] proposed Monet, an Android malware detection system, that is based on constructing dependency graphs to model the dependencies between application components and system services. ...
arXiv:1711.05731v1
fatcat:7ar5foxp5vcu3g3svih7uygrdi
Toward Engineering a Secure Android Ecosystem
2016
ACM Computing Surveys
Preserved Fulltext
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Based on our collection of knowledge, we envision a blueprint for engineering a secure, next-generation Android ecosystem. ...
The openness and extensibility of Android have made it a popular platform for mobile devices and a strong candidate to drive the Internet-of-Things. ...
IX Summary of Popular Monetization Schemes by Malware 10.3.3. Cloud-Based Malware Scanning. ...
doi:10.1145/2963145
fatcat:d5vhxpdywrevvbh4as6vvt576q
Self-hiding behavior in Android apps
2018
Proceedings of the 40th International Conference on Software Engineering - ICSE '18
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Specifically, we present (1) a detailed characterization of SHB, (2) a suite of static analyses to detect such behavior, and (3) a set of detectors that employ SHB to distinguish between benign and malicious ...
Using our static analysis tools on a large dataset of 9,452 Android apps (benign as well as malicious) we expose the frequency of 12 such SH behaviors. ...
This material is based upon work supported by the National Science Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation here on. ...
doi:10.1145/3180155.3180214
dblp:conf/icse/ShanNS18
fatcat:uicdmkwg65dzpg45pxiyk7k6du
Reducing Security Risks of Suspicious Data and Codes through a Novel Dynamic Defense Model
2019
IEEE Transactions on Information Forensics and Security
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Index Terms-Dynamic defense model, dynamic taint tracking, information flow control, behavior-based malware analysis, android. ...
We also practically implemented a prototype system named DDDroid on Android. ...
Lorenzo Cavallaro and reviewers for their valuable comments and suggestions. ...
doi:10.1109/tifs.2019.2901798
fatcat:vrsm6s7mxbh4zh5y3ovj3xeyiq
Beyond Google Play: A Large-Scale Comparative Study of Chinese Android App Markets
2018
Zenodo
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As Chinese users cannot access Google Play to buy and install Android apps, a number of independent app stores have emerged and compete in the Chinese app market. ...
of malware, fake, and cloned apps than Google Play. ...
Zhenhua Li (Tsinghua University), and all the anonymous reviewers for their valuable suggestions and comments to improve this paper. ...
doi:10.5281/zenodo.3461587
fatcat:znp2uldzhnd4jacsjxqgiy6xau
Beyond Google Play: A Large-Scale Comparative Study of Chinese Android App Markets
[article]
2018
arXiv
pre-print
Preserved Fulltext
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As Chinese users cannot access Google Play to buy and install Android apps, a number of independent app stores have emerged and compete in the Chinese app market. ...
of malware, fake, and cloned apps than Google Play. ...
Zhenhua Li (Tsinghua University), and all the anonymous reviewers for their valuable suggestions and comments to improve this paper. ...
arXiv:1810.07780v1
fatcat:jb2dg5nhz5djhpk3ushgz4aneq
Machine Learning-Based Routing and Wavelength Assignment in Software-Defined Optical Networks
2019
IEEE Transactions on Network and Service Management
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Permission-based Detection of Android Malware In general, permissions have been extensively studied for malware detection within the Android Ecosystem. ...
Android Malware Detection At present, malware detection is a very complex process that investigates applications to discover undesired behaviors and take the required actions for their removal. ...
doi:10.1109/tnsm.2019.2927867
fatcat:or3lhqdqbnas3cztwkqr5ykhhq
A Lustrum of Malware Network Communication: Evolution and Insights
2017
2017 IEEE Symposium on Security and Privacy (SP)
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Both the operational and academic security communities have used dynamic analysis sandboxes to execute malware samples for roughly a decade. ...
Network information derived from dynamic analysis is frequently used for threat detection, network policy, and incident response. ...
ACKNOWLEDGEMENTS We are grateful to Daniel Plohmann for his help with the DGArchive and to VirusTotal for their support. ...
doi:10.1109/sp.2017.59
dblp:conf/sp/LeverKBCA17
fatcat:utk43nkwtjdf7k7xzvrwsunk3y
Software engineering issues for mobile application development
2010
Proceedings of the FSE/SDP workshop on Future of software engineering research - FoSER '10
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Again, these questions are just a small subset of a broad range of research questions that need further study. ...
Among the topics are development processes, tools, user interface design, application portability, quality, and security. ...
Whittle et al. proposed the requirements specification language RELAX as a medium of explicitly expressing environmental and behavioral uncertainty for the behavior of dynamically adaptive systems [18 ...
doi:10.1145/1882362.1882443
dblp:conf/sigsoft/Wasserman10
fatcat:zqzn646yfzfl3oxktd2r24xzwi
Wild patterns: Ten years after the rise of adversarial machine learning
2018
Pattern Recognition
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2017 pre-print arXiv:1712.03141v1 fatcat:k5zcrg73xzhp5bfopktde25ifyOther Versions
Learning-based pattern classifiers, including deep networks, have shown impressive performance in several application domains, ranging from computer vision to cybersecurity. ...
In this work, we provide a thorough overview of the evolution of this research area over the last ten years and beyond, starting from pioneering, earlier work on the security of non-deep learning algorithms ...
Acknowledgments We are grateful to Ambra Demontis and Marco Melis for providing the experimental results on evasion and poisoning attacks. ...
doi:10.1016/j.patcog.2018.07.023
fatcat:adgnesv7rrarjptsxxqa7t6cr4
Deep Learning in Mobile and Wireless Networking: A Survey
2019
IEEE Communications Surveys and Tutorials
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Upcoming 5G systems are evolving to support exploding mobile traffic volumes, real-time extraction of fine-grained analytics, and agile management of network resources, so as to maximize user experience ...
We complete this survey by pinpointing current challenges and open future directions for research. ...
AE
Martinelli [421]
Android malware detection
Apps in Drebin, Android Malware Genome Project
and Google Play Store
Supersived
CNN
McLaughlin et al ...
doi:10.1109/comst.2019.2904897
fatcat:xmmrndjbsfdetpa5ef5e3v4xda
Deep Learning in Mobile and Wireless Networking: A Survey
[article]
2019
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Other Versions
Upcoming 5G systems are evolving to support exploding mobile traffic volumes, agile management of network resource to maximize user experience, and extraction of fine-grained real-time analytics. ...
We complete this survey by pinpointing current challenges and open future directions for research. ...
AE
Martinelli [418]
Android malware detection
Apps in Drebin, Android Malware Genome Project
and Google Play Store
Supersived
CNN
McLaughlin et al ...
arXiv:1803.04311v3
fatcat:awuvyviarvbr5kd5ilqndpfsde
IoT Vulnerability Assessment for Sustainable Computing: Threats, Current Solutions, and Open Challenges
2020
IEEE Access
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Over the last few decades, sustainable computing has been widely used in areas like social computing, artificial intelligence-based agent systems, mobile computing, and Internet of Things (IoT). ...
In this context, several efforts are initiated to deal with the evolving security issues in IoT systems and make them self-sufficient to harvest energy for smooth functioning. ...
Y.Meidan et al. [160] proposed a novel approach N-BaIoT, a network-based anomaly detection strategy for IoT devices. ...
doi:10.1109/access.2020.3022842
fatcat:ifkplk2lsjhupkt4c42fovqpta
Deep Learning in Diverse Intelligent Sensor Based Systems
2022
Sensors
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Deep learning has become a predominant method for solving data analysis problems in virtually all fields of science and engineering. ...
This survey serves as a catalyst to accelerate the application and transformation of deep learning in diverse sensor systems. ...
from a Gaussian distribution. (2) Android-based malware detection. ...
doi:10.3390/s23010062
pmid:36616657
pmcid:PMC9823653
fatcat:riifuhqtnrbrrkat26mxummwd4
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