Sökning: "Static Malware Analysis"

Visar resultat 1 - 5 av 8 uppsatser innehållade orden Static Malware Analysis.

1. 1. Android Malware Detection Using Machine Learning

   Kandidat-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskap

   Författare :Rahul Sai Kesani; [2024]
   Nyckelord :Malware; Machine Learning; Random Forest; Sequential Neural Network.;

   Sammanfattning : Background. The Android smartphone, with its wide range of uses and excellent performance, has attracted numerous users. Still, this domination of the Android platform also has motivated the attackers to develop malware. The traditional methodology which detects the malware based on the signature is unfit to discover unknown applications. LÄS MER

3. 2. Static Detection of Malware in Portable Executables

   Kandidat-uppsats, Högskolan Dalarna/Institutionen för information och teknik

   Författare :Josefin Paananen; [2021]
   Nyckelord :malware detection; machine learning; portable executables; static malware analysis;

   Sammanfattning : The first detected computer virus commenced in the 1970s. Since then, malware infections have grown exponentially along with rapid increases within the digital environment. Malware detection is a challenging task due to the relentless growth in complexity and volume. That is why the need for automated detection arises. LÄS MER

4. 3. Comparing state-of-the-art machine learning malware detection methods on Windows

   Master-uppsats,

   Författare :Filip Ahlgren; [2021]
   Nyckelord :Malware; Machine Learning; Static Analysis;

   Sammanfattning : Background. Malware has been a major issue for years and old signature scanning methods for detecting malware are outdated and can be bypassed by most advanced malware. With the help of machine learning, patterns of malware behavior and structure can be learned to detect the more advanced threats that are active today. Objectives. LÄS MER

5. 4. An Evaluation of Machine Learning Approaches for Hierarchical Malware Classification

   Uppsats för yrkesexamina på avancerad nivå, Blekinge Tekniska Högskola/Institutionen för datavetenskap

   Författare :Robin Roth; Martin Lundblad; [2019]
   Nyckelord :Machine Learning; Hierarchical Malware Classification; Static Malware Analysis; Mnemonic N-grams;

   Sammanfattning : With an evermore growing threat of new malware that keeps growing in both number and complexity, the necessity for improvement in automatic detection and classification of malware is increasing. The signature-based approaches used by several Anti-Virus companies struggle with the increasing amount of polymorphic malware. LÄS MER

7. 5. Studying the effectiveness of dynamic analysis for fingerprinting Android malware behavior

   Master-uppsats, Linköpings universitet/Databas och informationsteknik

   Författare :Viktor Regard; [2019]
   Nyckelord :Android malware; dynamic analysis; droidbox; cuckoodroid; droidscope; mobsf; malware behavior; correlation; pearson correlation; cosine similarity; euclidean distance; chebyshev distance; mahalanobis distance; similarity analysis; static features; dynamic features; tf-idf; term frequency inverse document frequency; AMD; Android malware dataset; malware dataset; UpDroid; EC2;

   Sammanfattning : Android is the second most targeted operating system for malware authors and to counter the development of Android malware, more knowledge about their behavior is needed. There are mainly two approaches to analyze Android malware, namely static and dynamic analysis. LÄS MER