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 | 133 | 2018 |
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 | 128 | 2015 |
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 | 110 | 2016 |
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 | 84 | 2016 |
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 | 55 | 2014 |
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 | 54 | 2018 |
MalJPEG: Machine learning based solution for the detection of malicious JPEG images A Cohen, N Nissim, Y Elovici IEEE Access 8, 19997-20011, 2020 | 48 | 2020 |
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 | 47 | 2020 |
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 | 44 | 2018 |
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 | 44 | 2016 |
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 | 37 | 2022 |
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 | 35 | 2019 |
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 | 33 | 2020 |
The infinite race between steganography and steganalysis in images T Muralidharan, A Cohen, A Cohen, N Nissim Signal Processing 201, 108711, 2022 | 31 | 2022 |
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 | 28 | 2019 |
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 | 21 | 2020 |
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 | 21 | 2019 |
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 | 19 | 2020 |
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 | 17 | 2021 |
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 | 12 | 2015 |