Results 181 to 190 of about 5,547 (215)

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   +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

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

Hierarchical Classification of Android Malware Traffic

2022 IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), 2022
In the last few years, Android mobile devices have encountered a large spread and nowadays a huge part of the traffic traversing the Internet is related to them. In parallel, the number of possible threats and attacks has also increased, thus emphasizing the need for accurate automatic malware detection systems.
Bovenzi G., Persico V., Pescape' A., Piscitelli A., Spadari V.   +4 more
openaire   +2 more sources

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

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

Improving malware classification

Proceedings of the 5th ACM workshop on Security and artificial intelligence, 2012
Malware classification systems have typically used some machine learning algorithm in conjunction with either static or dynamic features collected from the binary. Recently, more advanced malware has introduced mechanisms to avoid detection in these views by using obfuscation techniques to avoid static detection and execution-stalling techniques to ...
Blake Anderson, Curtis B. Storlie, Terran Lane   +2 more
openaire   +1 more source

Malware Classification Based on System Call

2021
It has always been a never-ending battle between security analysts and malware developers due to the complexity of malware changing as quickly as innovation grows. Current research focuses on the application of machine learning techniques for malware detection due to its ability to combat the malware evolution.
Mohamad Redza Izudin Abu Zaharin, Shafiza Mohd Shariff   +1 more
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   +1 more source