Recent advancements in Generative Artificial Intelligence have revolutionized the landscape of content creation and have significantly changed how content is conceptualized, developed, and delivered across various industries. Large Language Models (LLMs), such as BERT, T5, ChatGPT, GPT-4, Falcon 180B, and Codex, have influenced most disciplines of science and technology that support content generation in diverse applications, including cybersecurity. In cybersecurity, LLMs represent a dual-purpose tool. On the one hand, they empower malicious actors to identify vulnerabilities and enhance attack strategies. Conversely, they empower security teams to fortify defenses, identify threats, and effectively streamline risk management and operational processes. Despite the anticipated widespread adoption of these LLMs, our understanding of their full impact on cybersecurity still needs to be completed. There is a critical need to assess how they contribute to the discovery of vulnerabilities comprehensively, the development of new attack tactics and techniques, the creation of complex malware patterns, the identification of potential threats, and the mitigation of risks through automated vulnerability remediation

We invite the submission of original papers on all topics related to LLMs and cybersecurity, with special interest in but not limited to:

LLMs-empowered defensive strategies
Offensive approaches using LLMs
LLMs and cybercrime laws
Chatbot software/Apps (BERT, T5, ChatGPT, GPT-4, Falcon 180B , ...) impact on cybersecurity education
LLM for creating cybersecurity policies
Security of LLM-generated code
LLMs-driven threat modeling
LLMs for Solving Offensive Security Challenges such as Capture the Flag
Reliability Issues of using LLMs in the cybersecurity contex
LLMs for generation and analysis of Cyber Threat Intelligence (CTI)
Privacy issues of LLMs and privacy-preserving LLMs
Generating Adversarial machine learning examples using LLMs
LLMs driven threat prevention
LLMs based cybersecurity awareness framework

Organization Committee

Muna Al-Hawawreh, Deakin University, Australia (Muna.alhawawreh@deakin.edu.au)
Mohammad Saidur Rahman, RMIT University, Australia (mohammadsaidur.rahman@rmit.edu.au)
Aws Naser, KTH University, Sweeden (awsj@kth.se)
Giordano Colò, CY4GATE, Italy (giordano.colo@cy4gate.com)

KEYNOTE SPEAKERS

FLLM2024 Keynote at https://fllm2024.fllm-conference.org/index.php

Authors Submission Guidelines:

Submission Site:

https://easychair.org/conferences/?conf=fllm2024

Paper format

Submitted papers (.pdf format) must use the A4 IEEE Manuscript Templates for Conference Proceedings. Please remember to add Keywords to your submission.

Length

Submitted papers may be 6 to 8 pages. Up to two additional pages may be added for references. The reference pages must only contain references. Overlength papers will be rejected without review.

Originality

Papers submitted to GenAISE must be the original work of the authors. The may not be simultaneously under review elsewhere. Publications that have been peer-reviewed and have appeared at other conferences or workshops may not be submitted to GenAISE. Authors should be aware that IEEE has a strict policy with regard to plagiarism https://www.ieee.org/publications/rights/plagiarism/plagiarism-faq.html The authors' prior work must be cited appropriately.

Author list

Please ensure that you submit your papers with the full and final list of authors in the correct order. The author list registered for each submission is not allowed to be changed in any way after the paper submission deadline.

Proofreading:

Please proofread your submission carefully. It is essential that the language use in the paper is clear and correct so that it is easily understandable. (Either US English or UK English spelling conventions are acceptable.)

Publication:

All accepted papers in GenAISE 2024 and FLLM 2024 will be submitted to IEEEXplore for possible publication.

Program

The program will be announced with the FLLM 2024 program at https://fllm2024.fllm-conference.org/index.php

Venue

For venue and acomodoation information, please visit https://fllm2024.fllm-conference.org/venue.php

Registration

For registration information, please visit https://fllm2024.fllm-conference.org/index.php

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