Results 11 to 20 of about 1,811,594 (209)

On Deceiving Malware Classification with Section Injection

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   +5 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   +6 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

A Deep Learning Framework for Malware Classification [PDF]

International Journal of Digital Crime and Forensics, 2020
In this article, the authors propose a deep learning framework for malware classification. There has been a huge increase in the volume of malware in recent years which poses serious security threats to financial institutions, businesses, and individuals.
Mahmoud Kalash, Mrigank Rochan, Noman Mohammed, Neil D. B. Bruce, Yang Wang 0003, Farkhund Iqbal   +5 more
openaire   +3 more sources

Classification of Malware Network Activity

, 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   +3 more sources

Classification of packet contents for malware detection

Journal in Computer Virology, 2011
Many existing schemes for malware detection are signature-based. Although they can effectively detect known malwares, they cannot detect variants of known malwares or new ones. Most network servers do not expect executable code in their in-bound network traffic, such as on-line shopping malls, Picasa, Youtube, Blogger, etc.
Irfan Ahmed 0001, Kyung-suk Lhee
openaire   +3 more sources

Metamorphic Malware Classification

, 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
core   +3 more sources

Multimodal Techniques for Malware Classification

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   +4 more sources

Effective and Reliable Malware Group Classification for a Massive Malware Environment [PDF]

International Journal of Distributed Sensor Networks, 2016
Most of the cyber-attacks are caused by malware, and damage from them has escalated from cyber space to home appliances and infrastructure, thus affecting the daily living of the people. As such, anticipative analysis and countermeasures for malware have
Taejin Lee, Jin Kwak
doaj   +4 more sources