38 citations · 63 across the 11 of their papers we have counts for
7 papers · 1 filter
LLMs for Zero-Shot Threat Detection via Structured Risk Indicators
Abdullah Alghamdi, Siamak Layeghy, Marius Portmann
We propose a two-stage large language model (LLM) framework for zero-shot detection of insider threats and advanced persistent threats (APTs) from heterogeneous security logs. The…
MambaNetBurst: Direct Byte-level Network Traffic Classification without Tokenization or Pretraining
Gayan K. Kulatilleke, Siamak Layeghy, Mahsa Baktashmotlagh +1
We present MambaNetBurst, a compact tokenizer-free byte-level sequence classifier for network burst classification based on a Mamba-2 backbone. In contrast to most recent strong tr…
eX-NIDS: A Framework for Explainable Network Intrusion Detection Leveraging Large Language Models
Paul R. B. Houssel, Siamak Layeghy, Priyanka Singh +1
This paper introduces eX-NIDS, a framework designed to enhance interpretability in flow-based Network Intrusion Detection Systems (NIDS) by leveraging Large Language Models (LLMs).…
Towards Explainable Network Intrusion Detection using Large Language Models
Paul R. B. Houssel, Priyanka Singh, Siamak Layeghy +1
Large Language Models (LLMs) have revolutionised natural language processing tasks, particularly as chat agents. However, their applicability to threat detection problems remains u…
FlowTransformer: A Transformer Framework for Flow-based Network Intrusion Detection Systems
Liam Daly Manocchio, Siamak Layeghy, Wai Weng Lo +3
This paper presents the FlowTransformer framework, a novel approach for implementing transformer-based Network Intrusion Detection Systems (NIDSs). FlowTransformer leverages the st…
Network Intrusion Detection System in a Light Bulb
Liam Daly Manocchio, Siamak Layeghy, Marius Portmann
Internet of Things (IoT) devices are progressively being utilised in a variety of edge applications to monitor and control home and industry infrastructure. Due to the limited comp…