96 citations · 400 across the 24 of their papers we have counts for
25 papers
SoK: How Frontier AI Reshapes System-Level Security Risk Dynamics in Critical Infrastructure
Chandra Thapa, Mohan Baruwal Chhetri, Marthie Grobler +2
Frontier artificial intelligence (FAI), encompassing large-scale, general-purpose AI systems, including large language models, multimodal foundation models, and agentic systems, is…
From Frontier to Shadow AI: A Simmering Threat to Assurance and Security in Critical Infrastructure
Mohan Baruwal Chhetri, Shahroz Tariq, Tooba Aamir +3
Frontier AI systems, including large language models and emerging agentic AI tools, offer significant operational benefits but present unique challenges to critical infrastructure…
Through the Lens: Benchmarking Deepfake Detectors Against Moiré-Induced Distortions
Razaib Tariq, Minji Heo, Simon S. Woo +1
Deepfake detection remains a pressing challenge, particularly in real-world settings where smartphone-captured media from digital screens often introduces Moiré artifacts that can…
LLMs in the SOC: An Empirical Study of Human-AI Collaboration in Security Operations Centres
Ronal Singh, Shahroz Tariq, Fatemeh Jalalvand +4
The integration of Large Language Models (LLMs) into Security Operations Centres (SOCs) presents a transformative, yet still evolving, opportunity to reduce analyst workload throug…
From Prediction to Explanation: Multimodal, Explainable, and Interactive Deepfake Detection Framework for Non-Expert Users
Shahroz Tariq, Simon S. Woo, Priyanka Singh +3
The proliferation of deepfake technologies poses urgent challenges and serious risks to digital integrity, particularly within critical sectors such as forensics, journalism, and t…
LLMs Are Not Yet Ready for Deepfake Image Detection
Shahroz Tariq, David Nguyen, M. A. P. Chamikara +3
The growing sophistication of deepfakes presents substantial challenges to the integrity of media and the preservation of public trust. Concurrently, vision-language models (VLMs),…
Bridging Expertise Gaps: The Role of LLMs in Human-AI Collaboration for Cybersecurity
Shahroz Tariq, Ronal Singh, Mohan Baruwal Chhetri +2
This study investigates whether large language models (LLMs) can function as intelligent collaborators to bridge expertise gaps in cybersecurity decision-making. We examine two rep…
Towards Effective Identification of Attack Techniques in Cyber Threat Intelligence Reports using Large Language Models
Hoang Cuong Nguyen, Shahroz Tariq, Mohan Baruwal Chhetri +1
This work evaluates the performance of Cyber Threat Intelligence (CTI) extraction methods in identifying attack techniques from threat reports available on the web using the MITRE…
Towards a criteria-based approach to selecting human-AI interaction mode
Jessica Irons, Patrick Cooper, Melanie McGrath +2
Artificial intelligence (AI) tools are now prevalent in many knowledge work industries. As AI becomes more capable and interactive, there is a growing need for guidance on how to e…
Exploring the Impact of Moire Pattern on Deepfake Detectors
Razaib Tariq, Shahroz Tariq, Simon S. Woo
Deepfake detection is critical in mitigating the societal threats posed by manipulated videos. While various algorithms have been developed for this purpose, challenges arise when…
A2C: A Modular Multi-stage Collaborative Decision Framework for Human-AI Teams
Shahroz Tariq, Mohan Baruwal Chhetri, Surya Nepal +1
This paper introduces A2C, a multi-stage collaborative decision framework designed to enable robust decision-making within human-AI teams. Drawing inspiration from concepts such as…
SoK: Systematization and Benchmarking of Deepfake Detectors in a Unified Framework
Binh M. Le, Jiwon Kim, Simon S. Woo +3
Deepfakes have rapidly emerged as a serious threat to society due to their ease of creation and dissemination, triggering the accelerated development of detection technologies. How…
Towards Understanding of Deepfake Videos in the Wild
Beomsang Cho, Binh M. Le, Jiwon Kim +4
Deepfakes have become a growing concern in recent years, prompting researchers to develop benchmark datasets and detection algorithms to tackle the issue. However, existing dataset…
Deepfake in the Metaverse: Security Implications for Virtual Gaming, Meetings, and Offices
Shahroz Tariq, Alsharif Abuadbba, Kristen Moore
The metaverse has gained significant attention from various industries due to its potential to create a fully immersive and interactive virtual world. However, the integration of d…
Bridging Optimal Transport and Jacobian Regularization by Optimal Trajectory for Enhanced Adversarial Defense
Binh M. Le, Shahroz Tariq, Simon S. Woo
Deep neural networks, particularly in vision tasks, are notably susceptible to adversarial perturbations. To overcome this challenge, developing a robust classifier is crucial. In…
Why Do Facial Deepfake Detectors Fail?
Binh Le, Shahroz Tariq, Alsharif Abuadbba +2
Recent rapid advancements in deepfake technology have allowed the creation of highly realistic fake media, such as video, image, and audio. These materials pose significant challen…
Towards an Awareness of Time Series Anomaly Detection Models' Adversarial Vulnerability
Shahroz Tariq, Binh M. Le, Simon S. Woo
Time series anomaly detection is extensively studied in statistics, economics, and computer science. Over the years, numerous methods have been proposed for time series anomaly det…
Evaluation of an Audio-Video Multimodal Deepfake Dataset using Unimodal and Multimodal Detectors
Hasam Khalid, Minha Kim, Shahroz Tariq +1
Significant advancements made in the generation of deepfakes have caused security and privacy issues. Attackers can easily impersonate a person's identity in an image by replacing…
CoReD: Generalizing Fake Media Detection with Continual Representation using Distillation
Minha Kim, Shahroz Tariq, Simon S. Woo
Over the last few decades, artificial intelligence research has made tremendous strides, but it still heavily relies on fixed datasets in stationary environments. Continual learnin…
FakeAVCeleb: A Novel Audio-Video Multimodal Deepfake Dataset
Hasam Khalid, Shahroz Tariq, Minha Kim +1
While the significant advancements have made in the generation of deepfakes using deep learning technologies, its misuse is a well-known issue now. Deepfakes can cause severe secur…
FReTAL: Generalizing Deepfake Detection using Knowledge Distillation and Representation Learning
Minha Kim, Shahroz Tariq, Simon S. Woo
As GAN-based video and image manipulation technologies become more sophisticated and easily accessible, there is an urgent need for effective deepfake detection technologies. Moreo…
TAR: Generalized Forensic Framework to Detect Deepfakes using Weakly Supervised Learning
Sangyup Lee, Shahroz Tariq, Junyaup Kim +1
Deepfakes have become a critical social problem, and detecting them is of utmost importance. Also, deepfake generation methods are advancing, and it is becoming harder to detect. W…
One Detector to Rule Them All: Towards a General Deepfake Attack Detection Framework
Shahroz Tariq, Sangyup Lee, Simon S. Woo
Deep learning-based video manipulation methods have become widely accessible to the masses. With little to no effort, people can quickly learn how to generate deepfake (DF) videos.…
Am I a Real or Fake Celebrity? Measuring Commercial Face Recognition Web APIs under Deepfake Impersonation Attack
Shahroz Tariq, Sowon Jeon, Simon S. Woo
Recently, significant advancements have been made in face recognition technologies using Deep Neural Networks. As a result, companies such as Microsoft, Amazon, and Naver offer hig…