Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 189 for “"Malware"”.
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Dynamic analyses of malware
… machine learning techniques for detecting malware using dynamic runtime opcodes. Previous work in the field has faltered on inadequately sized and poorly sampled datasets. A novel run-trace dataset is presented, the largest in the literature to date. Using this dataset, malware detection …
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Towards robust malware detection
A central challenge of malware detection using machine learning methods is the presence of adversarial variants, small changes to detectable malware that allow it to evade a model (i.e. be classified as benign). We take inspiration from adversarial variant generation methods in the …
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DEALING WITH NEXT-GENERATION MALWARE
… security of billions of Internet users. Today's malware authors are motivated by the easy financial gain they can obtain by selling on the underground market the information stolen from the infected hosts. To maximize their profit, miscreants continuously improve their creations to make them more …
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Estudio sobre el malware Ransomware
… con este trabajo es realizar un estudio sobre el malware Ransomware para cubrir la necesidad que poseen las organizaciones de proteger su información. Para ello se estudia las características de este programa malicioso, los tipos de ransomwares que existen, qué vectores de infección utiliza, sus …
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Machine Learning Interpretability in Malware Detection
… with increasingly complex applications, such as malware detection. Recently, malware authors have become increasingly successful in bypassing traditional malware detection methods, partly due to advanced evasion techniques such as obfuscation and server-side polymorphism. Further, new programming …
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Malware Recognition by Properties of Executables
… patterns, if any, exist to differentiate non-malware from malware, given only a sequence of raw bytes composing either a received file or a fixed-length initial segment of a received file. If any such patterns are found, their effectiveness as filtering criteria is investigated.
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MDEA : malware detection with evolutionary adversarial learning
… have used machine learning as a tool to detect malware. These applications take in raw or processed binary data to feed neural network models to classify benign or malicious files. Even though this approach has proved effective against dynamic changes, such as encrypting, obfuscating and packing …
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Foresight: Countering Malware through Cooperative Forensics Sharing
… monitoring alone can be an effective tool for malware detection. Cooperation amongst domains greatly increases the effectiveness of our approach. Domains are able to pre-empt attacks and respond to malware behavior that they have not seen before. We also analyze various immunization/prevention …
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Similarity hashing of malware on IoT devices
A security threat to enterprise networks is the malware that exists on IoT devices which is rarely controlled at the same level that are observed for conventional computing devices. More specifically, IoT devices are poorly monitored for malware. Through self-modification, this malware attempts to …
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Detection of HTTPS malware traffic without decryption
… activities such as Command and Control, loading malware into a network, and exfiltration of sensitive data. The use of TLS by threat actors poses a challenge to security professionals as traditional techniques used in the detection of HTTP malware cannot be applied in detecting Hypertext Transfer …
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Enabling malware remediation in expanding home networks
As the Internet of Things (IoT) grows, malware will increasingly threaten Internet security and stability. Many actors, from individuals installing antivirus on their personal computers to law enforcement conducting botnet takedowns, have some capability to prevent or remediate malware, but these …
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A Malware Classification Method Based on the Multi-Layer Feature Fusion of Malware Image Representations and Opcode Markov Images
As the threat of malware to information security becomes increasingly severe, the study of efficient malware classification methods has become more urgent. This paper proposes a multilayer malware classification method based on the fusion of image representation and opcode features. By integrating …
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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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Machine Learning Methods for Hardware-Based Malware Detection
L'abstract è presente nell'allegato / the abstract is in the attachment
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Analysis of Evasion Techniques in Web-based Malware
… JavaScript code, play an important role in malware delivery today, making defenses against web-based malware crucial for system security. To make it even more challenging, malware authors often take advantage of various evasion techniques to evade detection. As a result, a constant arms race …
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Lightweight and purpose built hypervisor for malware analysis
… 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 analysis …
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Feature Selection and Improving Classification Performance for Malware Detection
… on machine learning algorithms for detecting malware. However, these methods require significant amount of extracted features for correct malware classification, making that feature extraction, training, and testing take significant time; even more, it has been unexplored which are the most …
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Effective Knowledge Graph Aggregation for Malware-Related Cybersecurity Text
<p>With the rate at which malware spreads in the modern age, it is extremely important that cyber security analysts are able to extract relevant information pertaining to new and active threats in a timely and effective manner. Having to manually read through articles and blog posts on the internet …
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Android behind the scenes: revealing hidden malware with AndroMEDA
… including malicious applications such as malware and trojans. To better understand mobile malware, we introduce the concept of the User-App Agreement (UAA) — a concep- tual framework for a user consenting to and trusting specific actions an app may perform. Using UAA we examine the Android …
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