Alternatives and similar repositories for Contextual-Outlier-Interpreter:

Users that are interested in Contextual-Outlier-Interpreter are comparing it to the libraries listed below

• Anjin-Liu / TCYB2019-EIkMeansDriftDetection
  ☆13Updated 4 years ago
• whyisyoung / CADE
  Code for our USENIX Security 2021 paper -- CADE: Detecting and Explaining Concept Drift Samples for Security Applications
  ☆138Updated 2 years ago
• dongtsi / OWAD
  Anomaly Detection in the Open World: Normality Shift Detection, Explanation, and Adaptation (NDSS'23).
  ☆67Updated last month
• nitishabharathi / LEMNA
  Source code for 'Lemna: Explaining deep learning based security applications'.
  ☆22Updated 4 years ago
• dongtsi / DeepAID
  Interpreting and Improving Deep Learning-based Anomaly Detection in Security Applications (CCS'21)
  ☆71Updated 3 years ago
• pfmarteau / DiFF-RF
  Forest of random partitioning trees for point-wise and collective anomaly detection
  ☆11Updated 6 months ago
• ninghaohello / Interpretation2Adversary
  Adversarial learning by utilizing model interpretation
  ☆10Updated 6 years ago
• junjieliang672 / FARE
  FARE: Enabling Fine-grained Attack Categorization under Low-quality Labeled Data
  ☆25Updated 3 years ago
• Western-OC2-Lab / OASW-Concept-Drift-Detection-and-Adaptation
  An online learning method used to address concept drift and model drift. Code for the paper entitled "A Lightweight Concept Drift Detecti…
  ☆51Updated last year
• cx0113 / fine-grained-unknown-attack-detection
  ☆17Updated 4 years ago
• Ruoyu-Li / UAD-Rule-Extraction
  Rule Extraction from Unsupervised Anomaly Detection in Security
  ☆19Updated last week
• pnnl / safekit
  ☆143Updated 4 years ago
• mlopezm / Supervised-contrastive-learning-over-prototype-label-embeddings
  Code for the paper: "Supervised contrastive learning over prototype-label embeddings for network intrusion detection"
  ☆14Updated 3 years ago
• cdogemaru / CPIP
  ☆16Updated 2 years ago
• GuansongPang / deep-outlier-detection
  Deep distance-based outlier detection published in KDD18: Learning representations specifically for distance-based outlier detection. Few…
  ☆48Updated 4 years ago
• ronniemi / explainAnomaliesUsingSHAP
  Explaining Anomalies Detected by Autoencoders Using SHAP
  ☆41Updated 3 years ago
• Henrygwb / Explaining-DL
  ☆55Updated 5 years ago
• Mobile-Intelligence-Lab / ACID
  Source code for the paper: Adaptive Clustering-based Malicious Traffic Classification at the Network Edge (https://homepages.inf.ed.ac.uk…
  ☆33Updated 4 years ago
• Forcrush / Efficient-GAN-based-method-for-cyber-intrusion
  A GAN-based model focused on anomaly detection in discrete dataset
  ☆26Updated 5 years ago
• jasonyanglu / ACDWM
  ACDWM (Adaptive Chunk-based Dynamic Weighted Majority)
  ☆10Updated 5 years ago
• ACANETS / NetML-Competition2020
  ☆27Updated last year
• jukworks / swat-seq2seq
  Anomaly Detection for SWaT Dataset using Sequence-to-Sequence Neural Networks
  ☆47Updated 5 years ago
• dongtsi / TrafficManipulator
  An automatic packet crafting tool for evading learning-based NIDS
  ☆79Updated 3 years ago
• amsadeghzadeh / AdversarialNetworkTraffic
  ☆19Updated 4 years ago
• ogarreche / XAI_NIDS
  Towards an Explainable Artificial Intelligence Framework for Enhancing Explainability in Network Intrusion Detection Systems
  ☆13Updated 5 months ago
• Chaomeng-Lu / MAML-CNN-FSIDS-IoT
  A Few-shot Based Model-Agnostic Meta-Learning for Intrusion Detection in Security of Internet of Things
  ☆12Updated 2 months ago
• PanpanZheng / OCAN
  ☆52Updated 4 years ago
• lixiangwang / DAGMM-pytorch
  ☆73Updated 4 years ago
• bazz-066 / aeids-py
  AEIDS is a prototype of anomaly-based intrusion detection system which works by remembering the pattern of legitimate network traffic usi…
  ☆14Updated 5 years ago
• Battlingboy / AE-IDS
  Network Intrusion Detection System(Abnormal Detection)
  ☆11Updated 4 years ago