24 citations · 65 across the 18 of their papers we have counts for
9 papers · 1 filter
AthenaBench: A Dynamic Benchmark for Evaluating LLMs in Cyber Threat Intelligence
Md Tanvirul Alam, Dipkamal Bhusal, Salman Ahmad +2
Large Language Models (LLMs) have demonstrated strong capabilities in natural language reasoning, yet their application to Cyber Threat Intelligence (CTI) remains limited. CTI anal…
R+R: Revisiting Static Feature-Based Android Malware Detection using Machine Learning
Md Tanvirul Alam, Dipkamal Bhusal, Nidhi Rastogi
Static feature-based Android malware detection using machine learning (ML) remains critical due to its scalability and efficiency. However, existing approaches often overlook secur…
CTIBench: A Benchmark for Evaluating LLMs in Cyber Threat Intelligence
Md Tanvirul Alam, Dipkamal Bhusal, Le Nguyen +1
Cyber threat intelligence (CTI) is crucial in today's cybersecurity landscape, providing essential insights to understand and mitigate the ever-evolving cyber threats. The recent r…
SECURE: Benchmarking Large Language Models for Cybersecurity
Dipkamal Bhusal, Md Tanvirul Alam, Le Nguyen +7
Large Language Models (LLMs) have demonstrated potential in cybersecurity applications but have also caused lower confidence due to problems like hallucinations and a lack of truth…
PASA: Attack Agnostic Unsupervised Adversarial Detection using Prediction & Attribution Sensitivity Analysis
Dipkamal Bhusal, Md Tanvirul Alam, Monish K. Veerabhadran +3
Deep neural networks for classification are vulnerable to adversarial attacks, where small perturbations to input samples lead to incorrect predictions. This susceptibility, combin…
Looking Beyond IoCs: Automatically Extracting Attack Patterns from External CTI
Md Tanvirul Alam, Dipkamal Bhusal, Youngja Park +1
Public and commercial organizations extensively share cyberthreat intelligence (CTI) to prepare systems to defend against existing and emerging cyberattacks. However, traditional C…
SoK: Modeling Explainability in Security Analytics for Interpretability, Trustworthiness, and Usability
Dipkamal Bhusal, Rosalyn Shin, Ajay Ashok Shewale +4
Interpretability, trustworthiness, and usability are key considerations in high-stake security applications, especially when utilizing deep learning models. While these models are…
CyNER: A Python Library for Cybersecurity Named Entity Recognition
Md Tanvirul Alam, Dipkamal Bhusal, Youngja Park +1
Open Cyber threat intelligence (OpenCTI) information is available in an unstructured format from heterogeneous sources on the Internet. We present CyNER, an open-source python libr…
Adversarial Patterns: Building Robust Android Malware Classifiers
Dipkamal Bhusal, Nidhi Rastogi
Machine learning models are increasingly being adopted across various fields, such as medicine, business, autonomous vehicles, and cybersecurity, to analyze vast amounts of data, d…