Results 171 to 180 of about 1,811,594 (209)

Clustering for malware classification

Journal of Computer Virology and Hacking Techniques, 2016
In this research, we apply clustering techniques to the malware classification problem. We compute clusters using the well-known K-means and Expectation Maximization algorithms, with the underlying scores based on Hidden Markov Models. We compare the results obtained from these two clustering approaches and we carefully consider the interplay between ...
Swathi Pai, Fabio Di Troia, Corrado Aaron Visaggio, Thomas H. Austin, Mark Stamp 0001   +4 more
openaire   +2 more sources

Integrated Framework for Classification of Malwares

Proceedings of the 7th International Conference on Security of Information and Networks, 2014
Malware is one of the most terrible and major security threats facing the Internet today. It is evolving, becoming more sophisticated and using new ways to target computers and mobile devices. The traditional defences like antivirus softwares typically rely on signature based methods and are unable to detect previously unseen malwares. Machine learning
Ekta Gandotra, Divya Bansal, Sanjeev Sofat   +2 more
openaire   +2 more sources

Malware classification with recurrent networks

2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2015
Attackers often create systems that automatically rewrite and reorder their malware to avoid detection. Typical machine learning approaches, which learn a classifier based on a handcrafted feature vector, are not sufficiently robust to such reorderings. We propose a different approach, which, similar to natural language modeling, learns the language of
Razvan Pascanu, Jack W. Stokes, Hermineh Sanossian, Mady Marinescu, Anil Thomas   +4 more
openaire   +2 more sources

Malware Analysis and Classification

2023
Malicious applications can be a security threat to Cyber-physical systems as these systems are composed of heterogeneous distributed systems and mostly depends on the internet, ICT services and products. The usage of ICT products and services gives the opportunity of less expensive data collection, intelligent control and decision systems using ...
Jairaj Singh, Kishore Kumar Kumar Senapati   +1 more
openaire   +1 more source

Transfer learning for malware multi-classification

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   +1 more source

A Malware Classification Method Based on Generic Malware Information

2015
Since attackers easily have been making malware using dedicated malware generation tools, the number of malware is increasing rapidly. However, it is hard to analyze all malwares because of rise in high-volume of malwares. For this reason, many researchers have proposed the malware classification methods for classifying new and well-known types of ...
Jiyeon Choi, HeeSeok Kim, Jangwon Choi 0001, Jungsuk Song 0001   +3 more
openaire   +1 more source

Classification of malware for self-driving systems

Neurocomputing, 2021
Abstract Classification and distinguishing of malware is key to predict the malicious attack, which is essential in self-driving systems. In order to handle large number of malware variants, many machine learning methods have been proposed. However, the accuracy and efficiency of multiple class classification of malware still remained inadequate to ...
Xiangyu Han, Fusheng Jin, Runan Wang, Shuliang Wang 0001, Ye Yuan 0001   +4 more
openaire   +1 more source

Clustering and Malware Classification

2019
In the present time, where people maintain a close relationship with smartphones, it is easier for cybercriminals to gain user’s personal data by installing malware without the user’s knowledge or authorization. In such a situation where the user’s data and privacy are always at threat, it is necessary to build a resilient system so as to curb such ...
Tony Thomas, Athira P. Vijayaraghavan, Sabu Emmanuel   +2 more
openaire   +1 more source

Texture-Based Malware Family Classification

2019 10th International Conference on Computing, Communication and Networking Technologies (ICCCNT), 2019
Malware is one of the major threats on internet whose count is increasing rapidly every year in millions. Most of the time similar malware files are modified for creation of new variants and most of the existing technique are obfuscated. So, malware visualization using image helps to overcome this problem.
Nitish Kumar, Toshanlal Meenpal
openaire   +1 more source

A New Malware Classification Approach Based on Malware Dynamic Analysis

2017
Dynamic analysis plays an important role in analyzing malware variants which have used obfuscation, polymorphism and metamorphism techniques. Malware classification is an emerging approach for discriminating different malware families. However, existing malware classification methods have mediocre performance in small scale datasets and some machine ...
Ying Fang, Bo Yu 0008, Yong Tang 0005, Liu Liu 0004, Zexin Lu, Yi Wang 0036, Qiang Yang   +6 more
openaire   +2 more sources