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Mark Scanlon

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Associate Professor

Dublin City University

Ireland

Research Interests

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Professors in Ireland Professors in Cybersecurity Cybersecurity professors in Ireland

About

Mark Scanlon is an Assistant Professor in Forensic Computing and Cybercrime Investigation at University College Dublin. His research focuses on the application of artificial intelligence in digital forensics, including areas such as large language models for enhancing investigation efficiency and contextual-based password cracking. His recent publications also explore advanced techniques in electromagnetic side-channel analysis and age estimation to support cybercrime investigations.

Recent Grants

Grant: Close

MIND: Machine learning for INtrusion Detection

Open Date: 2018-03-01

Close Date: 2021-02-01

Grant: Close

Prediction Model for Accurately Determining Customer Life Time Value

Open Date: 2017-01-01

Close Date: 2019-01-01

Grant: Close

Tackling the Digital Evidence Backlog: Enabling Faster Digital Evidence Processing through a Cloud-Based Deduplicated Data Store

Open Date: 2016-09-01

Close Date: 2020-09-01

Grant: Close

An Automated Digital Evidence Injection Methodology for Education and Training in Cybercrime Investigation and Cybersecurity

Open Date: 2016-07-01

Close Date: 2016-10-01

Grant: Close

Forensic Disk Image Reconstruction from a Deduplicated Data Store

Open Date: 2016-05-01

Close Date: 2016-08-01

Articles (15)

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2020

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2020

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2020

Collaborators (5)

John Sheppard

Lecturer

Waterford Institute of Technology

IRELAND

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Nhien-An Le-Khac

Dublin City University

IRELAND

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Harm van Beek

Endowed full professor (chair) of Digital Forensics

Open Universiteit

NETHERLANDS

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Jimmy McGibney

Lecturer

South East Technological University

IRELAND

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Frank Breitinger

Endowed Full Professor (Chair) for Cyber Security

University of Augsburg

GERMANY

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Mark Scanlon

Research Interests

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About

Recent Grants

Articles (15)

Fine-Tuning Large Language Models for Digital Forensics: Case Study and General Recommendations

Exploring the potential of large language models for improving digital forensic investigation efficiency

Improving Image Embeddings With Colour Features in Indoor Scene Geolocation

AutoDFBench: A Framework for AI Generated Digital Forensic Code and Tool Testing and Evaluation

An AI-Based Network Forensic Readiness Framework for Resource-Constrained Environments

Low-overhead and Non-invasive Electromagnetic Side-Channel Monitoring for Forensic-ready Industrial Control Systems

Towards a standardized methodology and dataset for evaluating LLM-based digital forensic timeline analysis

A comprehensive evaluation on the benefits of context based password cracking for digital forensics

Revealing IoT Cryptographic Settings through Electromagnetic Side-Channel Analysis

Data Exfiltration through Electromagnetic Covert Channel of Wired Industrial Control Systems

A Novel Dictionary Generation Methodology for Contextual-Based Password Cracking

Application of Artificial Intelligence to Network Forensics: Survey, Challenges and Future Directions

Cutting through the Emissions: Feature Selection from Electromagnetic Side-Channel Data for Activity Detection

DeepUAge: Improving Underage Age Estimation Accuracy to Aid CSEM Investigation

EMvidence: A Framework for Digital Evidence Acquisition from IoT Devices through Electromagnetic Side-Channel Analysis

Collaborators (5)

John Sheppard

Nhien-An Le-Khac

Harm van Beek

Jimmy McGibney

Frank Breitinger

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