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
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
772015
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
522016
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
422018
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
382016
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
372014
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), 1, 2016
242016
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
212018
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
182018
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
72015
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
62019
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
52019
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
32020
MalJPEG: Machine Learning Based Solution for the Detection of Malicious JPEG Images
A Cohen, N Nissim, Y Elovici
IEEE Access 8, 19997-20011, 2020
32020
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
32019
Search problems in the domain of multiplication: Case study on anomaly detection using markov chains
Y Mirsky, A Cohen, R Stern, A Felner, L Rokack, Y Elovici, B Shapira
Eighth Annual Symposium on Combinatorial Search, 2015
32015
Mind your privacy: Privacy leakage through BCI applications using machine learning methods
O Landau, A Cohen, S Gordon, N Nissim
Knowledge-Based Systems, 105932, 2020
22020
Scholarly Digital Libraries as a Platform for Malware Distribution.
N Nissim, A Cohen, J Wu, A Lanzi, L Rokach, Y Elovici, CL Giles
SG-CRC, 107-128, 2017
22017
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
12020
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
2020
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Articles 1–19