Malicious Code Detection and Acquisition Using Active Learning. - Robert Moskovitch; Nir Nissim; Yuval Elovici (ISI, 2007)

Improving the Detection of Unknown Computer Worms Activity Using Active Learning. - Robert Moskovitch; Nir Nissim; Dima Stopel; Clint Feher; Roman Englert; Yuval Elovici (KI, 2007)

Active learning to improve the detection of unknown computer worms activity. - Robert Moskovitch; Nir Nissim; Roman Englert; Yuval Elovici (FUSION, 2008)

Unknown malcode detection via text categorization and the imbalance problem. - Robert Moskovitch; Dima Stopel; Clint Feher; Nir Nissim; Yuval Elovici (ISI, 2008)

Malicious Code Detection Using Active Learning. - Robert Moskovitch; Nir Nissim; Yuval Elovici (PinKDD, 2008)

Unknown malcode detection and the imbalance problem. - Robert Moskovitch; Dima Stopel; Clint Feher; Nir Nissim; Nathalie Japkowicz; Yuval Elovici (J. Comput. Virol., 2009)

Detecting unknown computer worm activity via support vector machines and active learning. - Nir Nissim; Robert Moskovitch; Lior Rokach; Yuval Elovici (Pattern Anal. Appl., 2012)

ALPD: Active Learning Framework for Enhancing the Detection of Malicious PDF Files. - Nir Nissim; Aviad Cohen 002; Robert Moskovitch; Asaf Shabtai; Mattan Edry; Oren Bar-Ad; Yuval Elovici (JISIC, 2014)

Novel active learning methods for enhanced PC malware detection in windows OS. - Nir Nissim; Robert Moskovitch; Lior Rokach; Yuval Elovici (Expert Syst. Appl., 2014)

An Active Learning Framework for Efficient Condition Severity Classification. - Nir Nissim; Mary Regina Boland; Robert Moskovitch; Nicholas P. Tatonetti; Yuval Elovici; Yuval Shahar; George Hripcsak (AIME, 2015)

Boosting the Detection of Malicious Documents Using Designated Active Learning Methods. - Nir Nissim; Aviad Cohen 002; Yuval Elovici (ICMLA, 2015)

Detection of malicious PDF files and directions for enhancements: A state-of-the art survey. - Nir Nissim; Aviad Cohen 002; Chanan Glezer; Yuval Elovici (Comput. Secur., 2015)

SFEM: Structural feature extraction methodology for the detection of malicious office documents using machine learning methods. - Aviad Cohen 002; Nir Nissim; Lior Rokach; Yuval Elovici (Expert Syst. Appl., 2016)

Improving condition severity classification with an efficient active learning based framework. - Nir Nissim; Mary Regina Boland; Nicholas P. Tatonetti; Yuval Elovici; George Hripcsak; Yuval Shahar; Robert Moskovitch (J. Biomed. Informatics, 2016)

ALDROID: efficient update of Android anti-virus software using designated active learning methods. - Nir Nissim; Robert Moskovitch; Oren Bar-Ad; Lior Rokach; Yuval Elovici (Knowl. Inf. Syst., 2016)

Keeping pace with the creation of new malicious PDF files using an active-learning based detection framework. - Nir Nissim; Aviad Cohen 002; Robert Moskovitch; Asaf Shabtai; Matan Edri; Oren Bar-Ad; Yuval Elovici (Secur. Informatics, 2016)

Scholarly Digital Libraries as a Platform for Malware Distribution. - Nir Nissim; Aviad Cohen 002; Jian Wu 006; Andrea Lanzi; Lior Rokach; Yuval Elovici; C. Lee Giles (SG-CRC, 2017)

Inter-labeler and intra-labeler variability of condition severity classification models using active and passive learning methods. - Nir Nissim; Yuval Shahar; Yuval Elovici; George Hripcsak; Robert Moskovitch (Artif. Intell. Medicine, 2017)

USB-based attacks. - Nir Nissim; Ran Yahalom; Yuval Elovici (Comput. Secur., 2017)

Temporal Pattern Discovery for Accurate Sepsis Diagnosis in ICU Patients. - Eitam Sheetrit; Nir Nissim; Denis Klimov; Lior Fuchs; Yuval Elovici; Yuval Shahar (CoRR, 2017)

ALDOCX: Detection of Unknown Malicious Microsoft Office Documents Using Designated Active Learning Methods Based on New Structural Feature Extraction Methodology. - Nir Nissim; Aviad Cohen 002; Yuval Elovici (IEEE Trans. Inf. Forensics Secur., 2017)

Know Your Enemy: Characteristics of Cyber-Attacks on Medical Imaging Devices. - Tom Mahler; Nir Nissim; Erez Shalom; Israel Goldenberg; Guy Hasman; Arnon Makori; Itzik Kochav; Yuval Elovici; Yuval Shahar (CoRR, 2018)

Trusted detection of ransomware in a private cloud using machine learning methods leveraging meta-features from volatile memory. - Aviad Cohen 002; Nir Nissim (Expert Syst. Appl., 2018)

Novel set of general descriptive features for enhanced detection of malicious emails using machine learning methods. - Aviad Cohen 002; Nir Nissim; Yuval Elovici (Expert Syst. Appl., 2018)

Trusted system-calls analysis methodology aimed at detection of compromised virtual machines using sequential mining. - Nir Nissim; Yuval Lapidot; Aviad Cohen 002; Yuval Elovici (Knowl. Based Syst., 2018)

TrustSign: Trusted Malware Signature Generation in Private Clouds Using Deep Feature Transfer Learning. - Daniel Nahmias; Aviad Cohen 002; Nir Nissim; Yuval Elovici (IJCNN, 2019)

Temporal Probabilistic Profiles for Sepsis Prediction in the ICU. - Eitam Sheetrit; Nir Nissim; Denis Klimov; Yuval Shahar (KDD, 2019)

Sec-Lib: Protecting Scholarly Digital Libraries From Infected Papers Using Active Machine Learning Framework. - Nir Nissim; Aviad Cohen 002; Jian Wu 006; Andrea Lanzi; Lior Rokach; Yuval Elovici; C. Lee Giles (IEEE Access, 2019)

Malboard: A novel user keystroke impersonation attack and trusted detection framework based on side-channel analysis. - Nitzan Farhi; Nir Nissim; Yuval Elovici (Comput. Secur., 2019)

Volatile memory analysis using the MinHash method for efficient and secured detection of malware in private cloud. - Nir Nissim; Omri Lahav; Aviad Cohen 002; Yuval Elovici; Lior Rokach (Comput. Secur., 2019)

Dynamic Malware Analysis in the Modern Era - A State of the Art Survey. - Ori Or-Meir; Nir Nissim; Yuval Elovici; Lior Rokach (ACM Comput. Surv., 2019)

Keep an eye on your personal belongings! The security of personal medical devices and their ecosystems. - Matan Kintzlinger; Nir Nissim (J. Biomed. Informatics, 2019)

MalJPEG: Machine Learning Based Solution for the Detection of Malicious JPEG Images. - Aviad Cohen 002; Nir Nissim; Yuval Elovici (IEEE Access, 2020)

SEC-C-U: The Security of Intensive Care Unit Medical Devices and Their Ecosystems. - Carmel Eliash; Isaac Lazar; Nir Nissim (IEEE Access, 2020)

CardiWall: A Trusted Firewall for the Detection of Malicious Clinical Programming of Cardiac Implantable Electronic Devices. - Matan Kintzlinger; Aviad Cohen 002; Nir Nissim; Moshe Rav-Acha; Vladimir Khalameizer; Yuval Elovici; Yuval Shahar; Amos Katz (IEEE Access, 2020)

Mind your privacy: Privacy leakage through BCI applications using machine learning methods. - Ofir Landau; Aviad Cohen 002; Shirley Gordon; Nir Nissim (Knowl. Based Syst., 2020)

ASSAF: Advanced and Slim StegAnalysis Detection Framework for JPEG images based on deep convolutional denoising autoencoder and Siamese networks. - Assaf Cohen; Aviad Cohen 002; Nir Nissim (Neural Networks, 2020)

Deep feature transfer learning for trusted and automated malware signature generation in private cloud environments. - Daniel Nahmias; Aviad Cohen 002; Nir Nissim; Yuval Elovici (Neural Networks, 2020)

Pay Attention: Improving Classification of PE Malware Using Attention Mechanisms Based on System Call Analysis. - Ori Or-Meir; Aviad Cohen 002; Yuval Elovici; Lior Rokach; Nir Nissim (IJCNN, 2021)

Cardio-ML: Detection of malicious clinical programmings aimed at cardiac implantable electronic devices based on machine learning and a missing values resemblance framework. - Tamar Levy-Loboda; Moshe Rav-Acha; Amos Katz; Nir Nissim (Artif. Intell. Medicine, 2021)

Mind Your Mind: EEG-Based Brain-Computer Interfaces and Their Security in Cyber Space. - Ofir Landau; Rami Puzis; Nir Nissim (ACM Comput. Surv., 2021)

Leveraging malicious behavior traces from volatile memory using machine learning methods for trusted unknown malware detection in Linux cloud environments. - Tomer Panker; Nir Nissim (Knowl. Based Syst., 2021)

Deep-Hook: A trusted deep learning-based framework for unknown malware detection and classification in Linux cloud environments. - Tom Landman; Nir Nissim (Neural Networks, 2021)

A time-interval-based active learning framework for enhanced PE malware acquisition and detection. - Ido Finder; Eitam Sheetrit; Nir Nissim (Comput. Secur., 2022)

Personalized insulin dose manipulation attack and its detection using interval-based temporal patterns and machine learning algorithms. - Tamar Levy-Loboda; Eitam Sheetrit; Idit F. Liberty; Alon Haim; Nir Nissim (J. Biomed. Informatics, 2022)

Time-interval temporal patterns can beat and explain the malware. - Ido Finder; Eitam Sheetrit; Nir Nissim (Knowl. Based Syst., 2022)

The infinite race between steganography and steganalysis in images. - Trivikram Muralidharan; Aviad Cohen 002; Assaf Cohen; Nir Nissim (Signal Process., 2022)

File Packing from the Malware Perspective: Techniques, Analysis Approaches, and Directions for Enhancements. - Trivikram Muralidharan; Aviad Cohen 002; Noa Gerson; Nir Nissim (ACM Comput. Surv., 2023)

Improving malicious email detection through novel designated deep-learning architectures utilizing entire email. - Trivikram Muralidharan; Nir Nissim (Neural Networks, 2023)

Can NeuroIS improve executive employee recruitment? Classifying levels of executive functions using resting state EEG and data science methods. - Dor Zazon; Lior Fink; Shirley Gordon; Nir Nissim (Decis. Support Syst., 2023)

Efficient feature extraction methodologies for unknown MP4-Malware detection using Machine learning algorithms. - Tal Tsafrir; Aviad Cohen 002; Etay Nir; Nir Nissim (Expert Syst. Appl., 2023)

Bon-APT: Detection, attribution, and explainability of APT malware using temporal segmentation of API calls. - Gil Shenderovitz; Nir Nissim (Comput. Secur., 2024)

Patterns of time-interval based patterns for improved multivariate time series data classification. - Gil Shenderovitz; Eitam Sheetrit; Nir Nissim (Eng. Appl. Artif. Intell., 2024)

CADefender: Detection of unknown malicious AutoLISP computer-aided design files using designated feature extraction and machine learning methods. - Alexander Yevsikov; Trivikram Muralidharan; Tomer Panker; Nir Nissim (Eng. Appl. Artif. Intell., 2024)

MinCloud: Trusted and transferable MinHash-based framework for unknown malware detection for Linux cloud environments. - Tomer Panker; Aviad Cohen 002; Tom Landman; Chen Bery; Nir Nissim (J. Inf. Secur. Appl., 2024)

Speech emotion recognition systems and their security aspects. - Itzik Gurowiec; Nir Nissim (Artif. Intell. Rev., 2024)

Securing Linux Cloud Environments: Privacy-Aware Federated Learning Framework for Advanced Malware Detection in Linux Clouds. - Tom Landman; Nir Nissim (IEEE Access, 2025)

Can your brain signals reveal your romantic emotions? - Dor Zazon; Nir Nissim (Comput. Biol. Medicine, 2025)