Results 1 to 10 of about 5,547 (215)

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   +4 more sources

FedHGCDroid: An Adaptive Multi-Dimensional Federated Learning for Privacy-Preserving Android Malware Classification [PDF]

Entropy, 2022
With the popularity of Android and its open source, the Android platform has become an attractive target for hackers, and the detection and classification of malware has become a research hotspot.
Changnan Jiang, Kanglong Yin, Chunhe Xia, Weidong Huang   +3 more
doaj   +4 more sources

Binary and Multi-Class Malware Threads Classification

Applied Sciences, 2022
The security of a computer system can be harmed by specific applications, such as malware. Malware comprises unwanted, dangerous enemies that aim to compromise the security and generate significant loss.
Ismail Taha Ahmed, Norziana Jamil, Marina Md. Din, Baraa Tareq Hammad   +3 more
doaj   +4 more sources

Robust Malware Family Classification Using Effective Features and Classifiers

Applied Sciences, 2022
Malware development has significantly increased recently, posing a serious security risk to both consumers and businesses. Malware developers continually find new ways to circumvent security research’s ongoing efforts to guard against malware attacks ...
Baraa Tareq Hammad, Norziana Jamil, Ismail Taha Ahmed, Zuhaira Muhammad Zain, Shakila Basheer   +4 more
doaj   +4 more sources

MalwareDNA: Simultaneous Classification of Malware, Malware Families, and Novel Malware

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   +4 more sources

An Analysis of Android Malware Classification Services. [PDF]

Sensors (Basel), 2021
The increasing number of Android malware forced antivirus (AV) companies to rely on automated classification techniques to determine the family and class of suspicious samples. The research community relies heavily on such labels to carry out prevalence studies of the threat ecosystem and to build datasets that are used to validate and benchmark novel ...
Rashed M, Suarez-Tangil G.
europepmc   +6 more sources

CSMC: A Secure and Efficient Visualized Malware Classification Method Inspired by Compressed Sensing [PDF]

Sensors
With the rapid development of the Internet of Things (IoT), the sophistication and intelligence of sensors are continually evolving, playing increasingly important roles in smart homes, industrial automation, and remote healthcare.
Wei Wu, Haipeng Peng, Haotian Zhu, Derun Zhang   +3 more
doaj   +2 more sources

Attention-Based Cross-Modal CNN Using Non-Disassembled Files for Malware Classification

IEEE Access, 2023
The role of malware classification is crucial in addressing the explosive increase in malware variants. By classifying malware instances into malware families, malware analysts can apply appropriate techniques and tools to handle malware variants in each
Jeongwoo Kim, Joon-Young Paik, Eun-Sun Cho   +2 more
doaj   +3 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   +3 more sources

Study on Malware Classification Based on N-Gram Static Analysis Technology [PDF]

Jisuanji kexue, 2022
In order to solve the problem of low accuracy of malware classification,this paper proposes a research on malware classification based on N-Gram static analysis technology.Firstly,the N-Gram method is used to extract the byte sequence of length 2 from ...
ZHANG Guang-hua, GAO Tian-jiao, CHEN Zhen-guo, YU Nai-wen
doaj   +1 more source