activity
20212026
most citedFlowTransformer: A Transformer Framework for Flow-based Network Intrusion Detection Systems

206 citations · 239 across the 14 of their papers we have counts for

collaborators

14 papers

cs.CL2026

T5-CSBoost: Adversarial Perturbation Resistant LLM Fingerprinting

Gayan K. Kulatilleke, Mahsa Baktashmotlagh, Siamak Layeghy +1

While many AI-generated text (AIGT) detectors achieve strong performance on clean inputs, their accuracy degrades significantly under light paraphrasing, word substitutions, charac…

cs.CR2026

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…

cs.LG2025★ 8 cited

Temporal Analysis of NetFlow Datasets for Network Intrusion Detection Systems

Majed Luay, Siamak Layeghy, Seyedehfaezeh Hosseininoorbin +3

This paper investigates the temporal analysis of NetFlow datasets for machine learning (ML)-based network intrusion detection systems (NIDS). Although many previous studies have hi…

cs.CV2023

Ugly Ducklings or Swans: A Tiered Quadruplet Network with Patient-Specific Mining for Improved Skin Lesion Classification

Nathasha Naranpanawa, H. Peter Soyer, Adam Mothershaw +4

An ugly duckling is an obviously different skin lesion from surrounding lesions of an individual, and the ugly duckling sign is a criterion used to aid in the diagnosis of cutaneou…

cs.CR2023★ 206 cited

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…

cs.LG2022

NBC-Softmax : Darkweb Author fingerprinting and migration tracking

Gayan K. Kulatilleke, Shekhar S. Chandra, Marius Portmann

Metric learning aims to learn distances from the data, which enhances the performance of similarity-based algorithms. An author style detection task is a metric learning problem, w…