A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic | Paper Citation Record

Observation 78facc1e-69a8-4d13-9eef-7ddb04042cfa · outbound

This paper cites A holistic review of Network Anomaly Detection Systems: A comprehensive survey,.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic A holistic review of Network Anomaly Detection Systems: A comprehensive survey,

Reference 1

Resolution: verified exact; doi, observed 2026-08-01T19:08:20.944332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation ffbd9c55-c1ec-4579-bbd8-fbdcb10142df · outbound

This paper cites DI-NIDS: Domain invariant network intrusion detection system,.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic DI-NIDS: Domain invariant network intrusion detection system,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:05.616672Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ed828137-4dac-472f-bd52-021fb41d4885 · outbound

This paper cites It, serves as a standard benchmark for evaluating network intrusion detection systems.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic It, serves as a standard benchmark for evaluating network intrusion detection systems

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:04.898756Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 632fb01a-17f0-4ba2-b5a8-848d1ef45030 · outbound

This paper cites We start by constructing the NIDS model.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic We start by constructing the NIDS model

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:05.017809Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd34819a-0221-4dc0-a567-2cc597be7c9d · outbound

This paper cites It is well -suited for deep learning tasks.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic It is well -suited for deep learning tasks

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:05.123794Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a66bea18-0623-467d-b305-088d0aa302b1 · outbound

This paper cites Each scenario highlights the model’s performance, adaptability, and robustness when subjected to adversarial attacks, specifically FGSM and C&W methods.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic Each scenario highlights the model’s performance, adaptability, and robustness when subjected to adversarial attacks, specifically FGSM and C&W methods

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:05.275751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 39e00706-e203-4bfe-a67a-3c572d49ac8e · outbound

This paper cites • Adversarial Attacks: The research investigated two widely known adversarial attack methods, FGSM and C&W.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic • Adversarial Attacks: The research investigated two widely known adversarial attack methods, FGSM and C&W

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:05.373713Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 62b5b2c5-a7be-4d0e-bf4b-6da3b1af9811 · outbound

This paper cites The critical vulnerability is exposed when evaluating NIDS to adversarial attacks, specifically FGSM and C&W.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic The critical vulnerability is exposed when evaluating NIDS to adversarial attacks, specifically FGSM and C&W

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:05.426570Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e8e1f1ca-c857-4558-885d-ef7b04fffdbe · outbound

This paper cites A Stacking Ensemble for Network Intrusion Detection Using Heterogeneous Datasets,.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic A Stacking Ensemble for Network Intrusion Detection Using Heterogeneous Datasets,

Reference 9

Resolution: verified exact; doi, observed 2026-08-01T19:08:20.331592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 7379c90f-8f10-4c67-a14c-bdaf7e51aa9b · outbound

This paper cites Ensemble deep learning: A review,.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic Ensemble deep learning: A review,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:06.879709Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fe5a47c6-385e-474b-b3af-18da70b2da91 · outbound

This paper cites Ensemble based collaborative and distributed intrusion detection systems: A survey,.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic Ensemble based collaborative and distributed intrusion detection systems: A survey,

Reference 11

Resolution: verified exact; doi, observed 2026-08-01T19:08:20.198792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 5480ab7c-0c92-4ba0-b0e3-c2a31f3b9385 · outbound

This paper cites Towards a machine learning-based framework for DDOS attack detection in software-defined IoT (SD-IoT) networks,.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic Towards a machine learning-based framework for DDOS attack detection in software-defined IoT (SD-IoT) networks,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:05.776195Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d7cfbed2-5429-496f-bc23-8da9fb0397c3 · outbound

This paper cites A Systematic Review of Deep Learning Approaches for Computer Network and Information Security,.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic A Systematic Review of Deep Learning Approaches for Computer Network and Information Security,

Reference 13

Resolution: verified exact; doi, observed 2026-08-01T19:08:20.795723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 5da2bbee-9d23-4533-8b0f-424a949bf919 · outbound

This paper cites Deep Learning Approaches for Anomaly and Intrusion Detection in Computer Network: A Review,.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic Deep Learning Approaches for Anomaly and Intrusion Detection in Computer Network: A Review,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:06.110293Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 08d7f1ab-5056-4e3c-8c43-3978f79e8ef0 · outbound

This paper cites An Optimized Auto-Encoder based Approach for Detecting Zero-Day Cyber-Attacks in Computer Network,.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic An Optimized Auto-Encoder based Approach for Detecting Zero-Day Cyber-Attacks in Computer Network,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:06.271783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d713e8f-a5e9-4762-9e06-c0d16ba6e38d · outbound

This paper cites Adversarial Attacks and Defenses in Deep Learning,.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic Adversarial Attacks and Defenses in Deep Learning,

Reference 16

Resolution: verified exact; doi, observed 2026-08-01T19:08:20.600750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d47a0929-2f60-4e61-ba0d-c796bf442abf · outbound

This paper cites Deep stacking network for intrusion detection,.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic Deep stacking network for intrusion detection,

Reference 17

Resolution: verified exact; doi, observed 2026-08-01T19:08:20.478992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation f2fbc69e-a8d7-4e83-b2c0-d73d2fdef61a · outbound

This paper cites Adversarial Machine Learning In Network Intrusion Detection Domain: A Systematic Review.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic Adversarial Machine Learning In Network Intrusion Detection Domain: A Systematic Review

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:07.754225Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d1fa725d-02c4-43ab-b869-fa87518f0ae8 · outbound

This paper cites Adversarial Machine Learning: a taxonomy and terminology of attacks and mitigations,.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic Adversarial Machine Learning: a taxonomy and terminology of attacks and mitigations,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:07.826327Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a6adaa51-bd34-43b5-8936-95190d65d583 · outbound

This paper cites Efficient defenses against adversarial atacks,.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic Efficient defenses against adversarial atacks,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:07.936439Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ab298d95-8c25-4e32-a199-f9c919ccaa04 · outbound

This paper cites Ensemble adaptive online machine learning in data stream: a case study in cyber intrusion detection system,.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic Ensemble adaptive online machine learning in data stream: a case study in cyber intrusion detection system,

Reference 21

Resolution: verified exact; doi, observed 2026-08-01T19:08:20.049504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 5116a73a-1629-4692-b20d-179acc605b8e · outbound

This paper cites AE-Integrated: Real-time network intrusion detection with Apache Kafka and autoencoder,.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic AE-Integrated: Real-time network intrusion detection with Apache Kafka and autoencoder,

Reference 22

Resolution: verified exact; doi, observed 2026-08-01T19:08:19.895974Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 9f2d82c7-0d55-4c58-ada6-3a4cdfd0ebc4 · outbound

This paper cites Explaining and Harnessing Adversarial Examples.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic Explaining and Harnessing Adversarial Examples

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:07.471040Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 717bb9c6-8fbb-4d67-91b6-6b1e7f5acef6 · outbound

This paper cites Towards Evaluating the Robustness of Neural Networks,.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic Towards Evaluating the Robustness of Neural Networks,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:07.474507Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2846a27b-92ab-4971-bd2e-ddac549516b0 · outbound

This paper cites Network Anomaly Detection: Methods, Systems and Tools,.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic Network Anomaly Detection: Methods, Systems and Tools,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:07.554342Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eed3b0b3-be9b-41e6-937a-4836b96c5765 · outbound

This paper cites A detailed investigation and analysis of using machine learning techniques for intrusion detection,.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic A detailed investigation and analysis of using machine learning techniques for intrusion detection,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:07.652312Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 64790a6f-8502-46d0-a89f-549cd64c999e · outbound

This paper cites A complete list of all (arxiv) adversarial example papers.,.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic A complete list of all (arxiv) adversarial example papers.,

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:08.978183Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e89160f-e6aa-453a-885f-7423f90129fe · outbound

This paper cites Black-box adversarial transferability: An empirical study in cybersecurity perspective,.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic Black-box adversarial transferability: An empirical study in cybersecurity perspective,

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:09.084080Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 81e68f41-df28-4fdc-9292-afd1f5845bf6 · outbound

This paper cites Boosting robustness of network intrusion detection systems: A novel two phase defense strategy against untargeted white-box optimization adversarial attack,.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic Boosting robustness of network intrusion detection systems: A novel two phase defense strategy against untargeted white-box optimization adversarial attack,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:09.231059Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2be76472-ba72-442f-8a42-4762698a368f · outbound

This paper cites Adversarial classification,.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic Adversarial classification,

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:08.096176Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 412e813c-2fc1-45cc-9cce-b112c9b2a693 · outbound

This paper cites Adversarial learning,.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic Adversarial learning,

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:08.230993Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5da2ae90-113c-468c-9118-512d95331f68 · outbound

This paper cites Can machine learning be secure?,.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic Can machine learning be secure?,

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:08.443703Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9faa744d-666b-4cf6-840b-d302675c8343 · outbound

This paper cites an unresolved cited work.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic Unresolved cited work

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:04.206128Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 97a1f622-103b-495c-a7c0-5bdf64443cac · outbound

This paper cites Intriguing properties of neural networks.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic Intriguing properties of neural networks

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:08.555404Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c7216be1-e5ed-497b-8c56-ee4568b441a9 · outbound

This paper cites Deep learning,.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic Deep learning,

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:08.717435Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 03160103-ce5b-4f5f-8d12-1c66be0251c8 · outbound

This paper cites [37] (2021) CNN, DNN, KNN, RNN, C4.5 SCX- VPN- NON- VPN, NIMS DeepFool, PGD, Zoo (WB, BB ) NA Pre Attack F1: 97%, Post Attack F1 (Min):8% - Compared ML vs.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic [37] (2021) CNN, DNN, KNN, RNN, C4.5 SCX- VPN- NON- VPN, NIMS DeepFool, PGD, Zoo (WB, BB ) NA Pre Attack F1: 97%, Post Attack F1 (Min):8% - Compared ML vs

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:04.439704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2bddc8e8-f7c2-491c-be99-b537fdf0502f · outbound

This paper cites Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversarial Samples.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversarial Samples

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:08.871825Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 749cd242-edba-4afe-88ba-05e22d2f5ccc · outbound

This paper cites Adversarial machine learning in Network Intrusion Detection Systems,.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic Adversarial machine learning in Network Intrusion Detection Systems,

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:10.056143Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3a638586-690b-4247-9ba1-79cb5479c01a · outbound

This paper cites an unresolved cited work.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic Unresolved cited work

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:04.694036Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eae92fb3-3cd9-4357-aa3f-41ad20804641 · outbound

This paper cites RAIDS: Robust autoencoder -based intrusion detection system model against adversarial attacks,.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic RAIDS: Robust autoencoder -based intrusion detection system model against adversarial attacks,

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:09.311571Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ecc4efa3-93e7-4f4b-81e1-e7a9f49cbdd5 · outbound

This paper cites Adv -Bot: Realistic adversarial botnet attacks against network intrusion detection systems,.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic Adv -Bot: Realistic adversarial botnet attacks against network intrusion detection systems,

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:09.429729Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d346522-acbc-4181-b2cf-63980bdd7843 · outbound

This paper cites Defending against adversarial machine learning attacks using hierarchical learning: A case study on network traffic attack classification,.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic Defending against adversarial machine learning attacks using hierarchical learning: A case study on network traffic attack classification,

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:09.514517Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 162ae9e0-23ee-4c12-aec7-8e819c979c67 · outbound

This paper cites TAD: Transfer Learning-based Multi-Adversarial Detection of Evasion Attacks against Network Intrusion Detection Systems,.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic TAD: Transfer Learning-based Multi-Adversarial Detection of Evasion Attacks against Network Intrusion Detection Systems,

Reference 43

Resolution: verified exact; doi, observed 2026-08-01T19:08:19.772774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation aaed4320-e4aa-4ec3-a343-ab614f3f5bbe · outbound

This paper cites Investigating the practicality of adversarial evasion attacks on network intrusion detection,.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic Investigating the practicality of adversarial evasion attacks on network intrusion detection,

Reference 44

Resolution: malformed identifier; no resolver link, observed 2026-08-01T19:07:09.658105Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d3eca021-5834-4843-b16d-78da6a0229f8 · outbound

This paper cites Adversarial Attacks Against Deep Learning- Based Network Intrusion Detection Systems and Defense Mechanisms,.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic Adversarial Attacks Against Deep Learning- Based Network Intrusion Detection Systems and Defense Mechanisms,

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:09.735164Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3b30662d-fc51-4d79-a5a7-733f6241a4a3 · outbound

This paper cites Evaluating and Improving Adversarial Robustness of Machine Learning - Based Network Intrusion Detectors,.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic Evaluating and Improving Adversarial Robustness of Machine Learning - Based Network Intrusion Detectors,

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:09.848657Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e72f1fc0-4239-4dec-955b-8e1e3884c0d3 · outbound

This paper cites Evaluating Resilience of Encrypted Traffic Classification against Adversarial Evasion Attacks,.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic Evaluating Resilience of Encrypted Traffic Classification against Adversarial Evasion Attacks,

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:09.927756Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 81005003-c4f9-4745-84df-1b4cded04d2e · outbound

This paper cites A context -aware robust intrusion detection system: a reinforcement learning-based approach,.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic A context -aware robust intrusion detection system: a reinforcement learning-based approach,

Reference 48

Resolution: verified exact; doi, observed 2026-08-01T19:08:19.614417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 433822b4-3ab2-4d9a-a86a-7eb4dd641456 · outbound

This paper cites Defending network intrusion detection systems against adversarial evasion attacks,.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic Defending network intrusion detection systems against adversarial evasion attacks,

Reference 49

Resolution: verified exact; doi, observed 2026-08-01T19:08:19.435068Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 4b1d7e6b-943d-4bc1-8750-72869157b534 · outbound

This paper cites Generative Adversarial Networks For Launching and Thwarting Adversarial Attacks on Network Intrusion Detection Systems,.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic Generative Adversarial Networks For Launching and Thwarting Adversarial Attacks on Network Intrusion Detection Systems,

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:10.280286Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b0bbed9-34d2-4927-87a7-bdce65f35a13 · outbound

This paper cites Toward generating a new intrusion detection dataset and intrusion traffic characterization,.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic Toward generating a new intrusion detection dataset and intrusion traffic characterization,

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:10.356682Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 275e9195-6179-4651-a364-2e2b343abbb4 · outbound

This paper cites A detailed analysis of CICIDS2017 dataset for designing Intrusion Detection Systems,.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic A detailed analysis of CICIDS2017 dataset for designing Intrusion Detection Systems,

Reference 52

Resolution: verified exact; doi, observed 2026-08-01T19:08:19.271496Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation ff63639a-1c2b-4809-a9bd-34a663f362f8 · outbound

This paper cites Using Kernel SHAP XAI Method to Optimize the Network Anomaly Detection Model,.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic Using Kernel SHAP XAI Method to Optimize the Network Anomaly Detection Model,

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:10.594857Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 78580f79-0f9b-47d4-a8e0-96cdc2d01069 · outbound

This paper cites Utilizing Xai Technique to Improve Autoencoder Based Model for Computer Network Anomaly Detection with Shapley Additive Explanation(SHAP),.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic Utilizing Xai Technique to Improve Autoencoder Based Model for Computer Network Anomaly Detection with Shapley Additive Explanation(SHAP),

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:10.674193Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 28b89eaf-8a56-4896-859e-40bcf61ed25f · outbound

This paper cites Explainable Artificial Intelligence for Tabular Data: A Survey,.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic Explainable Artificial Intelligence for Tabular Data: A Survey,

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:10.747916Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ecdfa4a8-aa3b-45e0-bd26-af7a9c9782f9 · outbound

This paper cites Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI),.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI),

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:10.826260Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 41eb1c50-25aa-4747-95a9-e93b23a7b999 · outbound

This paper cites Enhancing Robustness Against Adversarial Examples in Network Intrusion Detection Systems,.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic Enhancing Robustness Against Adversarial Examples in Network Intrusion Detection Systems,

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:10.900542Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3ddf18c7-d423-40f8-b789-f77039000ee7 · outbound

This paper cites Untargeted white-box adversarial attack with heuristic defence methods in real-time deep learning based network intrusion detection system,.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic Untargeted white-box adversarial attack with heuristic defence methods in real-time deep learning based network intrusion detection system,

Reference 58

Resolution: verified exact; doi, observed 2026-08-01T19:08:19.118396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 7776ffc7-831f-47ee-851a-0e50cca7a2a7 · outbound

This paper cites Security Vulnerability in Face Mask Monitoring System,.

A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic Security Vulnerability in Face Mask Monitoring System,

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:11.036422Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers