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Showing 1 to 12 of 12 for “"Malware Analysis"”.
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Integrating Multiple Data Views for Improved Malware Analysis
Malicious software (malware) has become a prominent fixture in computing. There have been many methods developed over the years to combat the spread of malware, but these methods have inevitably been met with countermeasures. For instance, signature-based malware detection gave rise to polymorphic …
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Lightweight and purpose built hypervisor for malware analysis
… billions of dollars each year. Safe and thorough analysis of malware is key to protecting vulnerable systems and cleaning those that have already been infected. Most current state-of-the-art analysis platforms run alongside the malware, increasing their detectability. This reduces the value of …
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Transparent and Precise Malware Analysis Using Virtualization: From Theory to Practice
<p>Dynamic analysis is an important technique used in malware analysis and is complementary to static analysis. Thus far, virtualization has been widely adopted for building fine-grained dynamic analysis tools and this trend is expected to continue. Unlike User/Kernel space malware analysis …
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Improving the effectiveness and efficiency of dynamic malware analysis using machine learning
The malware threat landscape is constantly evolving, with upwards of one million new variants being released every day. Traditional approaches for detecting and classifying malware usually contain brittle handcrafted heuristics that quickly become outdated and can be exploited by nefarious actors. …
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An Assessment of Static and Dynamic malware analysis techniques for the android platform
… has fostered an increasing number of mobile malware attacks. The purpose of the research was to answer the following research questions: 1. What are the existing methods for analysing mobile malware? 2. How can methods for analysing mobile malware be evaluated? 3. What would comprise a …
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Optimum parameter machine learning classification and prediction of Internet of Things (IoT) malwares using static malware analysis techniques
Application of machine learning in the field of malware analysis is not a new concept, there have been lots of researches done on the classification of malware in android and windows environments. However, when it comes to malware analysis in the internet of things (IoT), it still requires work to …
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A Framework for the Systematic Evaluation of Malware Forensic Tools
… upon investigations where malicious software (‘malware’) has been identified. A framework, called the ‘Malware Analysis Tool Evaluation Framework’ (MATEF), has been developed to address this lack of methodology to evaluate software tools used during investigations involving malware. A prototype …
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A Feature-Based Call Graph Distance Measure for Program Similarity Analysis
… For example, they can be applied to malware analysis or analysis of university students' programming exercises. However, as programs may be arbitrarily structured, capturing the similarity of two non-trivial programs is a complex task. By extracting call graphs (graphs of …
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NeuroYara: Learning to Rank for Yara Rules Generation through Deep Language Modeling & Discriminative N-gram Encoding
Signature-based malware detection methods are simple, explainable, and efficient. One of the most ubiquitous tools is Yara. It is a widely-used syntax for writing malware signatures. Compared to machine learning models, Yara rules have a lower false-positive rate and better maintainability of the …
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A Static, Dynamic and Memory Analysis Process for Outputting Fileless Malware Prevention Software Requirement
The number of cyber-attacks involving fileless malware has increased in recent years. It can blend in with usual system activity, leave no traces on disk and evade signature-based detection making it difficult to detect with end point detection and response systems and anti-virus software. Many …
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Pattern recognition for computer security
… security problems: email spam campaign and malware detection. Email spam campaigns can easily be generated using popular dissemination tools by specifying simple grammars that serve as message templates. A grammar is disseminated to nodes of a bot net, the nodes create messages by …
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Network-based advanced malware detection using multi-classifier machine learning
… evolved in persistence and sophistication. Malware has been the primary choice of weapon to carry out various cyberattacks. Host-based malware detection, as the primary line of defence, evolved into the \Achilles Heel". In particular, the increase of security-aware targeted attacks, …