Guilt-by-Association: Detecting Malicious Entities via Graph Mining. - Pejman Najafi; Andrey Sapegin; Feng Cheng 002; Christoph Meinel (SecureComm, 2017)

MalRank: a measure of maliciousness in SIEM-based knowledge graphs. - Pejman Najafi; Alexander Mühle; Wenzel Pünter; Feng Cheng 002; Christoph Meinel (ACSAC, 2019)

Detect Me If You Can: Spam Bot Detection Using Inductive Representation Learning. - Seyed Ali Alhosseini; Raad Bin Tareaf; Pejman Najafi; Christoph Meinel (WWW (Companion Volume), 2019)

NLP-based Entity Behavior Analytics for Malware Detection. - Pejman Najafi; Daniel Köhler; Feng Cheng 002; Christoph Meinel (IPCCC, 2021)

SIEMA: Bringing Advanced Analytics to Legacy Security Information and Event Management. - Pejman Najafi; Feng Cheng 002; Christoph Meinel (SecureComm (1), 2021)

A Comprehensive Review of Anomaly Detection in Web Logs. - Mehryar Majd; Pejman Najafi; Seyed Ali Alhosseini; Feng Cheng 002; Christoph Meinel (BDCAT, 2022)

Leveraging data science & engineering for advanced security operations. - Pejman Najafi (2023)

HEOD: Human-assisted Ensemble Outlier Detection for cybersecurity. - Pejman Najafi; Feng Cheng 002; Christoph Meinel (Comput. Secur., 2024)

You are your friends: Detecting malware via guilt-by-association and exempt-by-reputation. - Pejman Najafi; Wenzel Pünter; Feng Cheng 002; Christoph Meinel (Comput. Secur., 2024)

Large Language Models in Cybersecurity: State-of-the-Art. - Farzad Nourmohammadzadeh Motlagh; Mehrdad Hajizadeh; Mehryar Majd; Pejman Najafi; Feng Cheng 002; Christoph Meinel (ICISSP (2), 2025)