most citedANUBIS: A Provenance Graph-Based Framework for Advanced Persistent Threat Detection

42 citations · 79 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CR2021★ 42 cited

ANUBIS: A Provenance Graph-Based Framework for Advanced Persistent Threat Detection

Md. Monowar Anjum, Shahrear Iqbal, Benoit Hamelin

We present ANUBIS, a highly effective machine learning-based APT detection system. Our design philosophy for ANUBIS involves two principal components. Firstly, we intend ANUBIS to…

cs.CL2021★ 3 cited

De-identification of Unstructured Clinical Texts from Sequence to Sequence Perspective

Md Monowar Anjum, Noman Mohammed, Xiaoqian Jiang

In this work, we propose a novel problem formulation for de-identification of unstructured clinical text. We formulate the de-identification problem as a sequence to sequence learn…

stat.ML2021

Federated Learning Algorithms for Generalized Mixed-effects Model (GLMM) on Horizontally Partitioned Data from Distributed Sources

Wentao Li, Jiayi Tong, Md. Monowar Anjum +3

Objectives: This paper develops two algorithms to achieve federated generalized linear mixed effect models (GLMM), and compares the developed model's outcomes with each other, as w…

cs.CR2021★ 34 cited

Analyzing the Usefulness of the DARPA OpTC Dataset in Cyber Threat Detection Research

Md. Monowar Anjum, Shahrear Iqbal, Benoit Hamelin

Maintaining security and privacy in real-world enterprise networks is becoming more and more challenging. Cyber actors are increasingly employing previously unreported and state-of…

cs.CR2020

PAARS: Privacy Aware Access Regulation System

Md. Monowar Anjum, Noman Mohammed

During pandemics, health officials usually recommend access monitoring and regulation protocols/systems in places that are major activity centres. As organizations adhere to those…