Results 11 to 20 of about 5,558 (210)

On Deceiving Malware Classification with Section Injection [PDF]

Machine Learning and Knowledge Extraction, 2023
We investigate how to modify executable files to deceive malware classification systems. This work’s main contribution is a methodology to inject bytes across a malware file randomly and use it both as an attack to decrease classification accuracy but ...
Adeilson Antonio da Silva, Mauricio Pamplona Segundo   +1 more
doaj   +4 more sources

MalwareDNA: Simultaneous Classification of Malware, Malware Families, and Novel Malware [PDF]

2023 IEEE International Conference on Intelligence and Security Informatics (ISI), 2023
Malware is one of the most dangerous and costly cyber threats to national security and a crucial factor in modern cyber-space. However, the adoption of machine learning (ML) based solutions against malware threats has been relatively slow. Shortcomings in the existing ML approaches are likely contributing to this problem.
Maksim Ekin Eren, Manish Bhattarai, Kim Ø. Rasmussen, Boian S. Alexandrov, Charles Nicholas   +4 more
core   +5 more sources

Learning and Classification of Malware Behavior [PDF]

, 2008
Malicious software in form of Internet worms, computer viruses, and Trojan horses poses a major threat to the security of networked systems. The diversity and amount of its variants severely undermine the effectiveness of classical signature-based detection.
Konrad Rieck, Thorsten Holz, Carsten Willems, Patrick Düssel, Pavel Laskov   +4 more
openaire   +4 more sources

Malware Classification with BERT [PDF]

, 2022
Malware Classification is used to distinguish unique types of malware from each other. This project aims to carry out malware classification using word embeddings which are used in Natural Language Processing (NLP) to identify and evaluate the ...
Alvares, Joel Lawrence
openaire   +3 more sources

Classification of Malware Network Activity [PDF]

, 2012
In the previous work, we have designed and implemented a platform with tools for capturing malware, running botnets in a controlled environment, analyzing their interactions with a botmaster, testing methods and techniques for mitigating botnet nuisance, and eventually disrupting them.
Gilles Berger-Sabbatel, Andrzej Duda
openaire   +2 more sources

Multimodal Techniques for Malware Classification [PDF]

CoRR
The threat of malware is a serious concern for computer networks and systems, highlighting the need for accurate classification techniques. In this research, we experiment with multimodal machine learning approaches for malware classification, based on the structured nature of the Windows Portable Executable (PE) file format.
Jonathan Jiang, Mark Stamp 0001
openaire   +3 more sources

Metamorphic Malware Classification [PDF]

, 2014
Metamorphic malware tend to change its code structure, every time it infects a new host machine. This makes classification and subsequent detection of the malware very difficult. Unlike other viruses, metamorphic malware uses code obfuscation techniques on the body of the malware and that way the malware structure does not exhibit a common signature ...
Ramakrishnan, Rukmini
openaire   +2 more sources

Transfer learning for malware multi-classification [PDF]

Proceedings of the 23rd International Database Applications & Engineering Symposium on - IDEAS '19, 2019
In this paper, we build on top of the MalConv neural networks learning architecture which was initially designed for malware/benign classification. We evaluate the transfer learning of MalConv for malware multi-class classification by extending its contribution in several directions: (1) We assess MalConv performance on a multi-classification problem ...
Mohamad Al Kadri, Mohamed Nassar 0001, Haïdar Safa   +2 more
openaire   +2 more sources

A Data Mining Classification Approach for Behavioral Malware Detection [PDF]

Journal of Computer Networks and Communications, 2016
Data mining techniques have numerous applications in malware detection. Classification method is one of the most popular data mining techniques. In this paper we present a data mining classification approach to detect malware behavior.
Monire Norouzi, Alireza Souri, Majid Samad Zamini   +2 more
doaj   +2 more sources

Classification of Malware Models [PDF]

, 2019
Automatically classifying similar malware families is a challenging problem. In this research, we attempt to classify malware families by applying machine learning to machine learning models.
Sethi, Akriti
openaire   +4 more sources