On the public citation graph

A Critical Review of Common Log Data Sets Used for Evaluation of Sequence-Based Anomaly Detection Techniques

0 signed · 94 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.

Claim with ORCID

Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.

See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/spe.3164openalex-snapshot

Anomaly detection on OpenStack logs based on an improved robust principal component analysis model and its projection onto column space

inferredcites →https://doi.org/10.1007/3-540-44503-x_27openalex-snapshot

On the Surprising Behavior of Distance Metrics in High Dimensional Space

inferredcites →https://doi.org/10.1007/978-3-031-17143-7_28openalex-snapshot

Can Industrial Intrusion Detection Be SIMPLE?

inferredcites →https://doi.org/10.1007/978-3-319-11698-3_44openalex-snapshot

Evaluating Host-Based Anomaly Detection Systems: Application of the Frequency-Based Algorithms to ADFA-LD

inferredcites →https://doi.org/10.1016/j.cose.2020.101739openalex-snapshot

System log clustering approaches for cyber security applications: A survey

inferredcites →https://doi.org/10.1016/j.cose.2020.102022openalex-snapshot

Are public intrusion datasets fit for purpose characterising the state of the art in intrusion event datasets

inferredcites →https://doi.org/10.1016/j.eswa.2021.116263openalex-snapshot

AutoLog: Anomaly detection by deep autoencoding of system logs

inferredcites →https://doi.org/10.1016/j.mlwa.2023.100470openalex-snapshot

Deep learning for anomaly detection in log data: A survey

inferredcites →https://doi.org/10.1109/ares.2009.105openalex-snapshot

Blue Gene/L Log Analysis and Time to Interrupt Estimation

inferredcites →https://doi.org/10.1109/bigdata55660.2022.10020672openalex-snapshot

A User and Entity Behavior Analytics Log Data Set for Anomaly Detection in Cloud Computing

inferredcites →https://doi.org/10.1109/dsn.2007.103openalex-snapshot

What Supercomputers Say: A Study of Five System Logs

inferredcites →https://doi.org/10.1109/icdm.2009.19openalex-snapshot

Online System Problem Detection by Mining Patterns of Console Logs

inferredcites →https://doi.org/10.1109/icrito48877.2020.9197818openalex-snapshot

A Survey on Log Anomaly Detection using Deep Learning

inferredcites →https://doi.org/10.1109/icse.2013.6606586openalex-snapshot

Assisting developers of Big Data Analytics Applications when deploying on Hadoop clouds

inferredcites →https://doi.org/10.1109/icse43902.2021.00130openalex-snapshot

Semi-Supervised Log-Based Anomaly Detection via Probabilistic Label Estimation

inferredcites →https://doi.org/10.1109/icws.2017.13openalex-snapshot

Drain: An Online Log Parsing Approach with Fixed Depth Tree

inferredcites →https://doi.org/10.1109/ijcnn52387.2021.9534113openalex-snapshot

LogBERT: Log Anomaly Detection via BERT

inferredcites →https://doi.org/10.1109/issre59848.2023.00071openalex-snapshot

Loghub: A Large Collection of System Log Datasets for AI-driven Log Analytics

inferredcites →https://doi.org/10.1109/mc.2018.2888764openalex-snapshot

KDD Cup 99 Data Sets: A Perspective on the Role of Data Sets in Network Intrusion Detection Research

inferredcites →https://doi.org/10.1109/secpri.1996.502675openalex-snapshot

A sense of self for Unix processes

inferredcites →https://doi.org/10.1109/tit.1976.1055501openalex-snapshot

On the Complexity of Finite Sequences

inferredcites →https://doi.org/10.1109/wcnc.2013.6555301openalex-snapshot

Generation of a new IDS test dataset: Time to retire the KDD collection

inferredcites →https://doi.org/10.1145/1541880.1541882openalex-snapshot

Anomaly detection

inferredcites →https://doi.org/10.1145/1629575.1629587openalex-snapshot

Detecting large-scale system problems by mining console logs

inferredcites →https://doi.org/10.1145/2889160.2889232openalex-snapshot

Log clustering based problem identification for online service systems

inferredcites →https://doi.org/10.1145/3133956.3134015openalex-snapshot

DeepLog

inferredcites →https://doi.org/10.1145/3338906.3338931openalex-snapshot

Robust log-based anomaly detection on unstable log data

inferredcites →https://doi.org/10.1145/3510003.3510155openalex-snapshot

Log-based anomaly detection with deep learning

inferredcites →https://doi.org/10.1145/3567675openalex-snapshot

AMiner: A Modular Log Data Analysis Pipeline for Anomaly-based Intrusion Detection

inferredcites →https://doi.org/10.1145/3590777.3590789openalex-snapshot

Towards Detecting Anomalies in Log-Event Sequences with Deep Learning: Open Research Challenges

inferredcites →https://doi.org/10.1186/s42400-019-0038-7openalex-snapshot

Survey of intrusion detection systems: techniques, datasets and challenges

inferredcites →https://doi.org/10.3390/app9010178openalex-snapshot

A Lightweight Perceptron-Based Intrusion Detection System for Fog Computing

inferredcites →https://doi.org/10.48550/arxiv.2107.05908openalex-snapshot

Experience Report: Deep Learning-based System Log Analysis for Anomaly Detection

inferredcites →https://doi.org/10.48550/arxiv.2401.03151openalex-snapshot

Semi-supervised learning via DQN for log anomaly detection

inferredcites →https://doi.org/10.5281/zenodo.11528722openalex-snapshot

ait-aecid/anomaly-detection-log-datasets: Zenodo DOI

inferredcites →https://doi.org/10.5860/choice.46-2715openalex-snapshot

Introduction to information retrieval

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/978-3-032-05176-9_25openalex-snapshot

Large Language Model Framework for Log Sequence Anomaly Detection

inferred← citeshttps://doi.org/10.1007/978-3-032-22542-9_1openalex-snapshot

Fine-Tuning Large Language Models for Anomaly Detection in Distributed System Logs

inferred← citeshttps://doi.org/10.1007/978-3-032-35586-7_33openalex-snapshot

Learning to Leak: Data Exfiltration from LSTM-Based Next-Token Prediction Models

inferred← citeshttps://doi.org/10.1007/978-3-032-36587-3_20openalex-snapshot

Towards LLM Accelerated Rapid Reviews for Software Tool Discovery - Case for Log Anomaly Detection

inferred← citeshttps://doi.org/10.1007/978-981-92-3391-5_27openalex-snapshot

LogAMF: Adaptive Multi-Feature Fusion for Log Anomaly Detection

inferred← citeshttps://doi.org/10.1007/978-981-95-6786-7_35openalex-snapshot

From Burst to Routine: Mining Time-Aware Patterns from Sequential Dataset

inferred← citeshttps://doi.org/10.1007/s10515-025-00527-3openalex-snapshot

What information contributes to log-based anomaly detection? Insights from a configurable transformer-based approach

inferred← citeshttps://doi.org/10.1007/s10664-025-10669-3openalex-snapshot

A comprehensive study of machine learning techniques for log-based anomaly detection

inferred← citeshttps://doi.org/10.1007/s41060-024-00659-xopenalex-snapshot

Sequential pattern mining algorithms and their applications: a technical review

inferred← citeshttps://doi.org/10.1007/s44354-026-00033-2openalex-snapshot

A security control recommender approach with human in the loop for cybersecurity compliance auditing

inferred← citeshttps://doi.org/10.1016/j.cose.2025.104312openalex-snapshot

Using approximate matching and machine learning to uncover malicious activity in logs

inferred← citeshttps://doi.org/10.1016/j.cose.2025.104503openalex-snapshot

A uniform assessment of host-based intrusion detection data sets

inferred← citeshttps://doi.org/10.1016/j.eswa.2025.130438openalex-snapshot

Reinforced temporal graph neural networks for class-imbalanced log anomaly detection

inferred← citeshttps://doi.org/10.1016/j.eswa.2025.130553openalex-snapshot

LogCALM: a log-based causal discovery and semantic modeling approach for network fault diagnosis

inferred← citeshttps://doi.org/10.1016/j.future.2025.108090openalex-snapshot

Collaborative anomaly detection in log data: Comparative analysis and evaluation framework

inferred← citeshttps://doi.org/10.1016/j.infsof.2026.108199openalex-snapshot

Log-based anomaly detection for evolving software: An incremental deep-learning approach

inferred← citeshttps://doi.org/10.1016/j.jss.2026.112916openalex-snapshot

InterpLog: Interpretable log-based anomaly detection assisting troubleshooting for system reliability

inferred← citeshttps://doi.org/10.1016/j.mlwa.2024.100554openalex-snapshot

Anomaly detection in log-event sequences: A federated deep learning approach and open challenges

inferred← citeshttps://doi.org/10.1016/j.scico.2025.103433openalex-snapshot

MulAD: A log-based anomaly detection approach for distributed systems using multi-pattern and multi-model fusion

inferred← citeshttps://doi.org/10.1109/access.2025.3592192openalex-snapshot

DeSFAM: An Adaptive eBPF and AI-Driven Framework for Securing Cloud Containers in Real Time

inferred← citeshttps://doi.org/10.1109/ase63991.2025.00035openalex-snapshot

LogMoE: Lightweight Expert Mixture for Cross-System Log Anomaly Detection

inferred← citeshttps://doi.org/10.1109/bigdata66926.2025.11401507openalex-snapshot

AI-Driven Log Analysis: Advances and Challenges

inferred← citeshttps://doi.org/10.1109/cbd69312.2025.00037openalex-snapshot

LogSwift: An Efficient Log Anomaly Detection Method with Lightweight Semantic Modeling and Hierarchical Attention

inferred← citeshttps://doi.org/10.1109/csecs64665.2025.11009471openalex-snapshot

Design and Implementation of Online Log Parsing Method Based on ALBERT and K-Means ++ Clustering

inferred← citeshttps://doi.org/10.1109/educon62633.2025.11016426openalex-snapshot

Integrating Generative AI in Cybersecurity Curricula

inferred← citeshttps://doi.org/10.1109/eiecc64539.2024.10929241openalex-snapshot

Log Anomaly Detection Method Based On Multi-Feature Graph Embedding

inferred← citeshttps://doi.org/10.1109/etncc66224.2025.11299798openalex-snapshot

Prediction of Operational Risk in Rural Credit Banks Based on CNN and LSTM Methods

inferred← citeshttps://doi.org/10.1109/icbctis66509.2025.11387440openalex-snapshot

LogFree: A Low-Resource-Oriented Model for Log Anomaly Detection

inferred← citeshttps://doi.org/10.1109/icde65706.2026.00056openalex-snapshot

Efficient Zero-Shot and Label-free Log Anomaly Detection for Resource-Constrained Systems

inferred← citeshttps://doi.org/10.1109/icdir66749.2025.11281022openalex-snapshot

KDPBert: Efficient Log Classification via Keyword-Guided Dynamic Pooling and LLM-Driven Open-Set Adaptation

inferred← citeshttps://doi.org/10.1109/icic68054.2025.11309610openalex-snapshot

Attention-Enhanced LSTM Autoencoder for Login Anomaly Detection

inferred← citeshttps://doi.org/10.1109/icoin68469.2026.11480531openalex-snapshot

Detecting Behavioural Anomalies in System Logs Using Log Sequence Analysis

inferred← citeshttps://doi.org/10.1109/icpads67057.2025.11322907openalex-snapshot

LINEADAPTER: Parameter-Efficient Fine-Tuning for Log Anomaly Detection and Root Cause Analysis

inferred← citeshttps://doi.org/10.1109/icse-companion66252.2025.00036openalex-snapshot

Practical Preprocessing of Logs at Scale

inferred← citeshttps://doi.org/10.1109/icse55347.2025.00189openalex-snapshot

Weakly-Supervised Log-Based Anomaly Detection with Inexact Labels via Multi-Instance Learning

inferred← citeshttps://doi.org/10.1109/jiot.2026.3685253openalex-snapshot

LogRMC: Robust Log Anomaly Detection in IoT Systems via Multifield Fusion, Contrastive Learning, and Pseudo-Label Refinement

inferred← citeshttps://doi.org/10.1109/mercon71835.2026.11691438openalex-snapshot

A Dataset-Aware Drift-Robust Log Anomaly Detection Pipeline for Cloud Service Reliability

inferred← citeshttps://doi.org/10.1109/saner64311.2025.00049openalex-snapshot

Cross-System Software Log-based Anomaly Detection Using Meta-Learning

inferred← citeshttps://doi.org/10.1109/tnse.2026.3654089openalex-snapshot

Log Anomaly Detection via Transformers Pre-Trained on Massive Unlabeled Data

inferred← citeshttps://doi.org/10.1109/tr.2026.3677674openalex-snapshot

Lightweight Techniques for Federated Anomaly Detection in Log Data

inferred← citeshttps://doi.org/10.1109/tsc.2024.3521675openalex-snapshot

Towards Close-to-Zero Runtime Collection Overhead: Raft-Based Anomaly Diagnosis on System Faults for Distributed Storage System

inferred← citeshttps://doi.org/10.1109/tsc.2025.3594870openalex-snapshot

E-Log: Fine-Grained Elastic Log-Based Anomaly Detection and Diagnosis for Databases

inferred← citeshttps://doi.org/10.1109/tse.2025.3586700openalex-snapshot

Practitioners’ Expectations on Log Anomaly Detection

inferred← citeshttps://doi.org/10.1142/s0129156425407314openalex-snapshot

Design of an Automatic Network Anomaly Detection Algorithm Based on Improved Machine Learning

inferred← citeshttps://doi.org/10.1145/3680256.3721259openalex-snapshot

Kernel-Level Event-Based Performance Anomaly Detection in Software Systems under Varying Load Conditions

inferred← citeshttps://doi.org/10.1145/3718350.3718354openalex-snapshot

Anomaly Detection in Large-Scale Monitoring Systems using a Language Model

inferred← citeshttps://doi.org/10.1145/3727582.3728682openalex-snapshot

LO2: Microservice API Anomaly Dataset of Logs and Metrics

inferred← citeshttps://doi.org/10.1145/3744916.3773248openalex-snapshot

Knowledge-Augmented Log Anomaly Detection with Large Language Models

inferred← citeshttps://doi.org/10.1145/3746635openalex-snapshot

A Survey of AIOps in the Era of Large Language Models

inferred← citeshttps://doi.org/10.1145/3774904.3792263openalex-snapshot

DyLogNet: A Dynamic Multi-Relational Graph Framework for Log Anomaly Detection

inferred← citeshttps://doi.org/10.1145/3774904.3792804openalex-snapshot

Smart Eye: LLM-Guided Proposer-Verifier Framework for Industrial-Scale Log Anomaly Detection

inferred← citeshttps://doi.org/10.1145/3793302.3793319openalex-snapshot

World of Logs: A Dataset of Logs from Online Documents

inferred← citeshttps://doi.org/10.14778/3749646.3749668openalex-snapshot

CoLA: Model Collaboration for Log-Based Anomaly Detection

inferred← citeshttps://doi.org/10.2139/ssrn.7051341openalex-snapshot

Detecting, Explaining, and Auditing Account Hijacking in Cloud Audit Logs with a Fine-Tuned Small Language Model

inferred← citeshttps://doi.org/10.23919/cnsm67658.2025.11297503openalex-snapshot

Anomaly Detection in Log Data: A Comparative Study

inferred← citeshttps://doi.org/10.3390/en19163716openalex-snapshot

Time-Interval-Driven Sequence Construction with a Transformer-Based Autoencoder for Anomaly Detection in NPP DCS Controller Logs

inferred← citeshttps://doi.org/10.3390/s25092649openalex-snapshot

Temporal Decay Loss for Adaptive Log Anomaly Detection in Cloud Environments

inferred← citeshttps://doi.org/10.5937/jcfs4-59602openalex-snapshot

Application of time series algorithms in cybersecurity

Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.