In this work, we perform a comparitive study on the behavior of malware and benign applications using its static and dynamic features. In static analysis, the permissions required for an application...doi:10.1007/978-981-10-7200-0_13Krishna Sugunan...
The signature is a unique identification for a binary file, which is created by analyzing the binary file using static analysis methods. Dynamic analysis uses the behavior and actions while in execution to identify whether the executable is a malware or not. Both methods have its own advantages ...
Specifically, we train Hidden Markov Models (HMMs) on both static and dynamic feature sets and compare the resulting detection rates over a substantial number of malware families. We also consider hybrid cases, where dynamic analysis is used in the training phase, with static techniques used in ...
Static and dynamic analysis of Android malware Ankita KapratwarFabio Di TroiaMark Stamp Jan 2017 28 被引用·0 笔记 Identification of Android Malware Families with Model Checking Pasquale BattistaFrancesco MercaldoVittoria Nardone...Corrado Aaron Visaggio ...
We used both static and dynamic analysis of android applications to extract six different features: intent, opcode, permission from static analysis, and unigram, bigram, trigram from system call log using dynamic analysis. Then, we proposed a custom malware detection model ( MalCNN ) that uses ...
Combining Dynamic and Static Analysis for Malware Detection by Anusha Damodaran Well-designed malware can evade static detection techniques, such as signature scanning. Dynamic analysis strips away one layer of obfuscation and hence such... A Damodaran 被引量: 6发表: 2015年 Effectiveness of Synthesis...
IoT malware detection approaches could be classified into two main domains based on the type of strategy: dynamic and static analysis. Dynamic approach [7] consists of monitoring executables during run-time period and detecting abnormal behaviors. However, monitoring executing processes is resource-inten...
Mobile Security Framework (MobSF) is an automated, all-in-one mobile application (Android/iOS/Windows) pen-testing framework capable of performing static, dynamic and malware analysis. It can be used for effective and fast security analysis of Android, iOS and Windows mobile applications and ...
Toward extracting malware features for classification using static and dynamic analysis GATTACA consists of three components: (1) START(STatic Analyzer using vaRious Techniques) extracts static Mal-DNA of malware. (2) DeBON(Debugging-based ... YH Choi,BJ Han,BC Bae,... - International Conference...
Few-Shot malware classification using fused features of static analysis and dynamic analysis (基于静态+动态分析的混合特征的小样本恶意代码分类框架) - Asichurter/MalFusionFSL