Big-IDS: a decentralized multi agent reinforcement learning approach for distributed intrusion detection in big data networks
The growing complexity of security threats and the pervasive prevalence of cyberattacks
have become more apparent in the present era, and the advent of big data, characterized by …
have become more apparent in the present era, and the advent of big data, characterized by …
A Comprehensive Review of Behind-the-Meter Distributed Energy Resources Load Forecasting: Models, Challenges, and Emerging Technologies
Behind the meter (BTM) distributed energy resources (DERs), such as photovoltaic (PV)
systems, battery energy storage systems (BESSs), and electric vehicle (EV) charging …
systems, battery energy storage systems (BESSs), and electric vehicle (EV) charging …
A Comprehensive Overview of Large Language Models (LLMs) for Cyber Defences: Opportunities and Directions
M Hassanin, N Moustafa - arXiv preprint arXiv:2405.14487, 2024 - arxiv.org
The recent progression of Large Language Models (LLMs) has witnessed great success in
the fields of data-centric applications. LLMs trained on massive textual datasets showed …
the fields of data-centric applications. LLMs trained on massive textual datasets showed …
Harnessing the advanced capabilities of llm for adaptive intrusion detection systems
O G. Lira, A Marroquin, MA To - International Conference on Advanced …, 2024 - Springer
Abstract The integration of Machine Learning (ML) and Deep Learning (DL) techniques has
significantly advanced Intrusion Detection Systems (IDSs) across diverse domains such as …
significantly advanced Intrusion Detection Systems (IDSs) across diverse domains such as …
Enhancing Intrusion Detection Systems with Reinforcement Learning: A Comprehensive Survey of RL-based Approaches and Techniques
Intrusion detection systems (IDSs) play a crucial role in network security, as the need for
secure networks continues to grow. However, traditional IDSs are not able to accurately and …
secure networks continues to grow. However, traditional IDSs are not able to accurately and …
SECURE: Benchmarking Generative Large Language Models for Cybersecurity Advisory
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 …
but have also caused lower confidence due to problems like hallucinations and a lack of …
A Comprehensive Survey on the Security of Smart Grid: Challenges, Mitigations, and Future Research Opportunities
In this study, we conduct a comprehensive review of smart grid security, exploring system
architectures, attack methodologies, defense strategies, and future research opportunities …
architectures, attack methodologies, defense strategies, and future research opportunities …
Applying Fine-Tuned LLMs for Reducing Data Needs in Load Profile Analysis
This paper presents a novel method for utilizing fine-tuned Large Language Models (LLMs)
to minimize data requirements in load profile analysis, demonstrated through the restoration …
to minimize data requirements in load profile analysis, demonstrated through the restoration …
[PDF][PDF] CAUSALPROMPT: ENHANCING LLMS WITH WEAKLY SUPERVISED CAUSAL REASONING FOR ROBUST PER-FORMANCE IN NON-LANGUAGE TASKS
In confronting the pressing issue of climate change, we introduce” Causal-Prompt”, an
innovative prompting strategy that adapts large language models (LLMs) for classification …
innovative prompting strategy that adapts large language models (LLMs) for classification …