Follow
Aviad Cohen
Aviad Cohen
Ph.D., Software and Information Systems Engineering in Ben-Gurion
Verified email at post.bgu.ac.il - Homepage
Title
Cited by
Cited by
Year
Trusted detection of ransomware in a private cloud using machine learning methods leveraging meta-features from volatile memory
A Cohen, N Nissim
Expert Systems with Applications 102, 158-178, 2018
1392018
Detection of malicious PDF files and directions for enhancements: A state-of-the art survey
N Nissim, A Cohen, C Glezer, Y Elovici
Computers & Security 48, 246-266, 2015
1362015
ALDOCX: detection of unknown malicious microsoft office documents using designated active learning methods based on new structural feature extraction methodology
N Nissim, A Cohen, Y Elovici
IEEE Transactions on Information Forensics and Security 12 (3), 631-646, 2016
1152016
SFEM: Structural feature extraction methodology for the detection of malicious office documents using machine learning methods
A Cohen, N Nissim, L Rokach, Y Elovici
Expert Systems With Applications 63, 324-343, 2016
872016
Alpd: Active learning framework for enhancing the detection of malicious pdf files
N Nissim, A Cohen, R Moskovitch, A Shabtai, M Edry, O Bar-Ad, Y Elovici
2014 IEEE Joint Intelligence and Security Informatics Conference, 91-98, 2014
602014
Trusted system-calls analysis methodology aimed at detection of compromised virtual machines using sequential mining
N Nissim, Y Lapidot, A Cohen, Y Elovici
Knowledge-Based Systems 153, 147-175, 2018
592018
MalJPEG: Machine learning based solution for the detection of malicious JPEG images
A Cohen, N Nissim, Y Elovici
IEEE Access 8, 19997-20011, 2020
552020
Deep feature transfer learning for trusted and automated malware signature generation in private cloud environments
D Nahmias, A Cohen, N Nissim, Y Elovici
Neural Networks 124, 243-257, 2020
512020
File packing from the malware perspective: Techniques, analysis approaches, and directions for enhancements
T Muralidharan, A Cohen, N Gerson, N Nissim
ACM Computing Surveys 55 (5), 1-45, 2022
492022
Novel Set of General Descriptive Features For Enhanced Detection of Malicious Emails Using Machine Learning Methods
A Cohen, N Nissim, Y Elovici
Expert Systems with Applications, 2018
462018
Keeping pace with the creation of new malicious PDF files using an active-learning based detection framework
N Nissim, A Cohen, R Moskovitch, A Shabtai, M Edri, O BarAd, Y Elovici
Security Informatics 5, 1-20, 2016
442016
Volatile memory analysis using the MinHash method for efficient and secured detection of malware in private cloud
N Nissim, O Lahav, A Cohen, Y Elovici, L Rokach
Computers & Security 87, 101590, 2019
382019
The infinite race between steganography and steganalysis in images
T Muralidharan, A Cohen, A Cohen, N Nissim
Signal Processing 201, 108711, 2022
362022
Mind your privacy: Privacy leakage through BCI applications using machine learning methods
O Landau, A Cohen, S Gordon, N Nissim
Knowledge-Based Systems 198, 105932, 2020
342020
Trustsign: trusted malware signature generation in private clouds using deep feature transfer learning
D Nahmias, A Cohen, N Nissim, Y Elovici
2019 International Joint Conference on Neural Networks (IJCNN), 1-8, 2019
292019
CardiWall: a trusted firewall for the detection of malicious clinical programming of cardiac implantable electronic devices
M Kintzlinger, A Cohen, N Nissim, M Rav-Acha, V Khalameizer, Y Elovici, ...
IEEE Access 8, 48123-48140, 2020
242020
Sec-lib: Protecting scholarly digital libraries from infected papers using active machine learning framework
N Nissim, A Cohen, J Wu, A Lanzi, L Rokach, Y Elovici, L Giles
IEEE Access 7, 110050-110073, 2019
242019
ASSAF: Advanced and Slim StegAnalysis Detection Framework for JPEG images based on deep convolutional denoising autoencoder and Siamese networks
A Cohen, A Cohen, N Nissim
Neural Networks 131, 64-77, 2020
202020
Pay attention: Improving classification of PE malware using attention mechanisms based on system call analysis
O Or-Meir, A Cohen, Y Elovici, L Rokach, N Nissim
2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021
192021
Boosting the detection of malicious documents using designated active learning methods
N Nissim, A Cohen, Y Elovici
2015 IEEE 14th International Conference on Machine Learning and Applications …, 2015
122015
The system can't perform the operation now. Try again later.
Articles 1–20