Mahinthan Chandramohan
Principal Researcher
Mahinthan Chandramohan
Mahin Chandramohan is leading the machine learning efforts in Intelligent Application Security group at Oracle Labs, Australia.
His research areas of interest include:
• Open Source Intelligence (OSINT)
• Threat intelligence
• Malware analysis and binary reverse engineering
• Machine learning for program analysis and bug detection (MLonCode).
Education:
* PhD in Computer Science, Nanyang Technological University, Singapore
* B.Eng. in Computer Engineering, Nanyang Technological University, Singapore
Publications
Conference Publication
Exploring topic models to discern zero-day vulnerabilities on Twitter through a case study on log4shell
Joy Wang, Bashar Md Abul, Mahinthan Chandramohan, Richi Nayak
Article
ColdPress: An Extensible Malware Analysis Platform for Threat Intelligence
Haoxi Tan, Chandramohan, Mahin, Cifuentes, Cristina, Guangdong Bai, Ryan K. L. Ko
In Proceedings
ColdPress - An Extensible Malware Analysis Platform for Threat Intelligence.
Haoxi Tan, Mahin Chandramohan, Cristina Cifuentes, Guangdong Bai, Ryan K. L. Ko
In Proceedings
Accurate and Scalable Cross-Architecture Cross-OS Binary Code Search with Emulation.
Yinxing Xue, Zhengzi Xu, Mahinthan Chandramohan, Yang Liu 0003
In Proceedings
ROPSentry - Runtime defense against ROP attacks using hardware performance counters.
Sanjeev Das, Bihuan Chen 0001, Mahinthan Chandramohan, Yang Liu 0003, Wei Zhang 0012
In Proceedings
A multi-view context-aware approach to Android malware detection and malicious code localization.
Annamalai Narayanan, Mahinthan Chandramohan, Lihui Chen, Yang Liu 0003
In Proceedings
Steelix - program-state based binary fuzzing.
Yuekang Li, Bihuan Chen 0001, Mahinthan Chandramohan, Shang-Wei Lin, Yang Liu 0003, Alwen Tiu
In Proceedings
A Multi-view Context-aware Approach to Android Malware Detection and Malicious Code Localization.
Annamalai Narayanan, Mahinthan Chandramohan, Lihui Chen, Yang Liu 0003
In Proceedings
graph2vec - Learning Distributed Representations of Graphs.
Annamalai Narayanan, Mahinthan Chandramohan, Rajasekar Venkatesan, Lihui Chen, Yang Liu 0003, Shantanu Jaiswal
In Proceedings
Context-aware, Adaptive and Scalable Android Malware Detection through Online Learning (extended version).
Annamalai Narayanan, Mahinthan Chandramohan, Lihui Chen, Yang Liu 0003
In Proceedings
SPAIN - security patch analysis for binaries towards understanding the pain and pills.
Zhengzi Xu, Bihuan Chen 0001, Mahinthan Chandramohan, Yang Liu 0003, Fu Song
In Proceedings
Context-Aware, Adaptive, and Scalable Android Malware Detection Through Online Learning.
Annamalai Narayanan, Mahinthan Chandramohan, Lihui Chen, Yang Liu 0003
In Proceedings
Mystique - Evolving Android Malware for Auditing Anti-Malware Tools.
Guozhu Meng, Yinxing Xue, Mahinthan Chandramohan, Annamalai Narayanan, Yang Liu 0003, Jie Zhang 0002, Tieming Chen
In Proceedings
subgraph2vec - Learning Distributed Representations of Rooted Sub-graphs from Large Graphs.
Annamalai Narayanan, Mahinthan Chandramohan, Lihui Chen, Yang Liu 0003, Santhoshkumar Saminathan
In Proceedings
BinGo - cross-architecture cross-OS binary search.
Mahinthan Chandramohan, Yinxing Xue, Zhengzi Xu, Yang Liu 0003, Chia Yuan Cho, Hee Beng Kuan Tan
In Proceedings
Semantics-Based Online Malware Detection - Towards Efficient Real-Time Protection Against Malware.
Sanjeev Das, Yang Liu 0003, Wei Zhang 0012, Mahinthan Chandramohan
In Proceedings
An Adaptive Markov Strategy for Effective Network Intrusion Detection.
Jianye Hao, Yinxing Xue, Mahinthan Chandramohan, Yang Liu 0003, Jun Sun 0001
In Proceedings
Detection and classification of malicious JavaScript via attack behavior modelling.
Yinxing Xue, Junjie Wang 0007, Yang Liu 0003, Hao Xiao, Jun Sun 0001, Mahinthan Chandramohan
In Proceedings
A scalable approach for malware detection through bounded feature space behavior modeling.
Mahinthan Chandramohan, Hee Beng Kuan Tan, Lionel C. Briand, Lwin Khin Shar, Bindu Madhavi Padmanabhuni
In Proceedings
Detection of Buffer Overflow Vulnerabilities in C/C++ with Pattern Based Limited Symbolic Evaluation.
Sun Ding, Hee Beng Kuan Tan, Kaiping Liu, Mahinthan Chandramohan, Hongyu Zhang 0002
In Proceedings
Scalable malware clustering through coarse-grained behavior modeling.
Mahinthan Chandramohan, Hee Beng Kuan Tan, Lwin Khin Shar
In Proceedings
Evolutionary design of agent-based simulation experiments.
James Decraene, Yew Ti Lee, Fanchao Zeng, Mahinthan Chandramohan, Yong Yong Cheng, Malcolm Yoke-Hean Low
In Proceedings
Autonomous Bee Colony Optimization for multi-objective function.
Fanchao Zeng, James Decraene, Malcolm Yoke-Hean Low, Philip Hingston, Wentong Cai, Suiping Zhou, Mahinthan Chandramohan
In Proceedings
Evolvable simulations applied to Automated Red Teaming - A preliminary study.
James Decraene, Mahinthan Chandramohan, Malcolm Yoke-Hean Low, Chwee Seng Choo
In Proceedings
Application of Multi-objective Bee Colony Optimization Algorithm to Automated Red Teaming.
Malcolm Yoke-Hean Low, Mahinthan Chandramohan, Chwee Seng Choo