Frank Breitinger

Associate Professor of Digital Forensic Science and Investigation

University of Lausanne

Switzerland

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Frank Breitinger is an Associate Professor of Digital Forensic Science and Investigation at the University of Lausanne, Switzerland. His research focuses on digital forensics, including the evaluation of tamper resistance of digital artifacts, the optimization of dataset creation for cybersecurity, and the application of large language models in digital forensic investigations. He has published various articles exploring the efficiency of digital forensic methodologies and metadata fairness in forensic datasets.

Frank Breitinger

Research Interests

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Articles (20)

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

Evaluating tamper resistance of digital forensic artifacts during event reconstruction

Optimising data set creation in the cybersecurity landscape with a special focus on digital forensics: Principles, characteristics, and use cases

DFRWS EU 10-year review and future directions in Digital Forensic Research

Beyond timestamps: Integrating implicit timing information into digital forensic timelines

DFPulse: The 2024 digital forensic practitioner survey

Was the clock correct? Exploring timestamp interpretation through time anchors for digital forensic event reconstruction

ChatGPT, Llama, can you write my report? An experiment on assisted digital forensics reports written using (local) large language models

FAIRness in digital forensics datasets’ metadata – and how to improve it

Towards AI forensics: Did the artificial intelligence system do it?

Sharing datasets for digital forensic: A novel taxonomy and legal concerns

The role of national cybersecurity strategies on the improvement of cybersecurity education

FRASHER – A framework for automated evaluation of similarity hashing

Wake Up Digital Forensics' Community and Help Combating Ransomware

Android application forensics: A survey of obfuscation, obfuscation detection and deobfuscation techniques and their impact on investigations

Malware family classification via efficient Huffman features

Bringing order to approximate matching: Classification and attacks on similarity digest algorithms

What do incident response practitioners need to know? A skillmap for the years ahead

A survey on smartphone user's security choices, awareness and education

Collaborators (7)

John Sheppard

Chris Hargreaves

Radek Hranický

Felix Freiling

Mark Scanlon

Stephen OShaughnessy

Saed Alrabaee

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