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389
Dissecting android malware: Characterization and evolution
- In IEEE Symposium on Security and Privacy
, 2012
"... Abstract—The popularity and adoption of smartphones has greatly stimulated the spread of mobile malware, especially on the popular platforms such as Android. In light of their rapid growth, there is a pressing need to develop effective solutions. However, our defense capability is largely constraine ..."
Abstract
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Cited by 212 (8 self)
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security software, our experiments show that the best case detects 79.6 % of them while the worst case detects only 20.2 % in our dataset. These results clearly call for the need to better develop next-generation anti-mobile-malware solutions. Keywords-Android malware; smartphone security I.
Static Analysis of Executables for Collaborative Malware Detection on Android
"... Abstract—Smartphones are getting increasingly popular and several malwares appeared targeting these devices. General countermeasures to smartphone malwares are currently limited to signature-based antivirus scanners which efficiently detect known malwares, but they have serious shortcomings with new ..."
Abstract
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analysis on the executables to extract their function calls in Android environment using the command readelf. Function call lists are compared with malware executables for classifying them with PART, Prism and Nearest Neighbor Algorithms. Second, we present a collaborative malware detection approach
Crowdroid: Behavior-Based Malware Detection System for Android
"... The sharp increase in the number of smartphones on the market, with the Android platform posed to becoming a market leader makes the need for malware analysis on this platform an urgent issue. In this paper we capitalize on earlier approaches for dynamic analysis of application behavior as a means f ..."
Abstract
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Cited by 83 (0 self)
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for detecting malware in the Android platform. The detector is embedded in a overall framework for collection of traces from an unlimited number of real users based on crowdsourcing. Our framework has been demonstrated by analyzing the data collected in the central server using two types of data sets: those
Android Malware Detection Based on System Calls
, 2015
"... With Android being the most widespread mobile platform, protecting it against malicious applications is essential. Android users typically install applications from large remote repositories, which provides ample opportunities for malicious newcomers. In this paper, we propose a simple, and yet high ..."
Abstract
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highly effective technique for detecting malicious Android applications on a repository level. Our technique performs automatic classification based on tracking system calls while applications are executed in a sandbox environment. We implemented the technique in a tool called MALINE, and performed
Malware Detection Techniques in Android
"... Mobile Phones have become an important need of today. The term mobile phone and smart phone are almost identical now-a-days. Smartphone market is booming with very high speed. Smartphones have gained such a huge popularity due to wide range of capabilities they offer. Currently android platform is l ..."
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technique will be introduced to detect malware. This technique detects malware in android applications through machine learning classifier by using both static and dynamic analysis. This technique does not rely on malware signatures for static analysis but instead android permission model is used. Under
BotHunter: Detecting Malware Infection Through IDS-Driven Dialog Correlation
, 2007
"... We present a new kind of network perimeter monitoring strategy, which focuses on recognizing the infection and coordination dialog that occurs during a successful malware infection. BotHunter is an application designed to track the two-way communication flows between internal assets and external ent ..."
Abstract
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Cited by 197 (18 self)
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entities, developing an evidence trail of data exchanges that match a state-based infection sequence model. BotHunter consists of a correlation engine that is driven by three malware-focused network packet sensors, each charged with detecting specific stages of the malware infection process, including
Permission-Based Android Malware Detection
"... Abstract:- Mobile devices have become popular in our lives since they offer almost the same functionality as personal computers. Among them, Android-based mobile devices had appeared lately and, they were now an ideal target for attackers. Android-based smartphone users can get free applications fro ..."
Abstract
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Cited by 5 (0 self)
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Market. The proposed framework intends to develop a machine learning-based malware detection system on Android to detect malware applications and to enhance security and privacy of smartphone users. This system monitors various permissionbased features and events obtained from the android applications
Android Malware Analysis Platform
"... Abstracts—Malware for smartphones is a prominent threat to secu- rity, with Android leading the charge as a primary threat. To combat this, it is vital that the security field devote research into finding better methods of malware analysis and subsequently malware defense. As a result, initiative wa ..."
Abstract
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was taken to perform focused research on this subject in the form of an independent study. The purpose of the study is to develop a lab virtual environment for analyzing Android malware. The solution needs to be intuitive and centrally managed in order to be effective for a professor and their assistants
Detecting Android Malware on Network Level
, 2011
"... As Android OS establishes itself as the primary platform on smartphones, a substantial increase in malware targeted at Android devices is being ob-served in the wild. While anti-virus software is available, and Android limits applications to user approved permissions, many users remain unaware of th ..."
Abstract
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Cited by 1 (0 self)
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of the threat posed by malware and of actual in-fections on their devices. In this paper we explore techniques to enable mobile network operators to detect Android malware and violations of user pri-vacy through network traffic analysis. 1
Monitoring Real Android Malware
"... Abstract. In the most comprehensive study on Android attacks so far (undertaken by the Android Malware Genome Project), the behaviour of more than 1, 200 malwares was analysed and categorised into common, recurring groups of attacks. Based on this work (and the corresponding actual malware files), ..."
Abstract
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Abstract. In the most comprehensive study on Android attacks so far (undertaken by the Android Malware Genome Project), the behaviour of more than 1, 200 malwares was analysed and categorised into common, recurring groups of attacks. Based on this work (and the corresponding actual malware files
Results 1 - 10
of
389
