A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures | Paper Citation Record

Observation 88026004-46d0-4e53-8885-9d547d1eea44 · outbound

This paper cites https:// www.cisco.com/en/US/technologies/ tk648/tk362/technologies_white_ paper09186a00800a3db9.pdf, Accessed online on 01/10/2024.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures https:// www.cisco.com/en/US/technologies/ tk648/tk362/technologies_white_ paper09186a00800a3db9.pdf, Accessed online on 01/10/2024

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This paper cites https: //research.unsw.edu.au/projects/ unsw-nb15-dataset, Accessed online on 01/09/2024.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures https: //research.unsw.edu.au/projects/ unsw-nb15-dataset, Accessed online on 01/09/2024

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This paper cites https://www.unb.ca/ cic/datasets/ids-2018.html, Accessed online on 12/20/2023.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures https://www.unb.ca/ cic/datasets/ids-2018.html, Accessed online on 12/20/2023

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This paper cites https: //archive.ics.uci.edu/dataset/516/ kitsune+network+attack+dataset, Accessed online on 12/20/2023.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures https: //archive.ics.uci.edu/dataset/516/ kitsune+network+attack+dataset, Accessed online on 12/20/2023

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This paper cites https: //cybersecurityonline.utulsa.edu/ blog/why-is-cybersecurity- important-top-six-reasons/ , Accessed online on 11/29/2023.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures https: //cybersecurityonline.utulsa.edu/ blog/why-is-cybersecurity- important-top-six-reasons/ , Accessed online on 11/29/2023

Reference 5

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A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Unresolved cited work

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A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Unresolved cited work

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This paper cites https: //www.statista.com/statistics/ 325706/global-internet-user- penetration/, Accessed online on 06/04/2024.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures https: //www.statista.com/statistics/ 325706/global-internet-user- penetration/, Accessed online on 06/04/2024

Reference 8

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This paper cites Federated learning for intrusion detection system: Concepts, challenges and future directions.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Federated learning for intrusion detection system: Concepts, challenges and future directions

Reference 9

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This paper cites Inves- tigating adversarial attacks against network intru- sion detection systems in sdns.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Inves- tigating adversarial attacks against network intru- sion detection systems in sdns

Reference 10

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This paper cites Adding robustness to support vec- tor machines against adversarial reverse engineer- ing.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Adding robustness to support vec- tor machines against adversarial reverse engineer- ing

Reference 11

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

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Adversarial Machine Learning In Network Intrusion Detection Domain: A Systematic Review

Reference 12

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This paper cites De- fending deep learning based anomaly detection systems against white-box adversarial examples and backdoor attacks.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures De- fending deep learning based anomaly detection systems against white-box adversarial examples and backdoor attacks

Reference 13

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This paper cites A review of big data in network intrusion detection system: Chal- lenges, approaches, datasets, and tools.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures A review of big data in network intrusion detection system: Chal- lenges, approaches, datasets, and tools

Reference 14

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This paper cites Secure network intrusion detec- tion system using nid-rnn based deep learn- ing.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Secure network intrusion detec- tion system using nid-rnn based deep learn- ing

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This paper cites Reverse engineering of protocols from network traces.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Reverse engineering of protocols from network traces

Reference 16

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This paper cites Modeling realistic adversarial attacks against net- work intrusion detection systems.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Modeling realistic adversarial attacks against net- work intrusion detection systems

Reference 17

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This paper cites Reverse engineering of generative models: In- ferring model hyperparameters from generated im- ages.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Reverse engineering of generative models: In- ferring model hyperparameters from generated im- ages

Reference 18

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This paper cites Synthesizing robust adversarial examples.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Synthesizing robust adversarial examples

Reference 19

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This paper cites Reverse tcp and social engineering attacks in the era of big data.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Reverse tcp and social engineering attacks in the era of big data

Reference 20

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A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Model evasion attack on intrusion detection systems using adversarial machine learning

Reference 21

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This paper cites Recent Advances in Adversarial Training for Adversarial Robustness.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Recent Advances in Adversarial Training for Adversarial Robustness

Reference 22

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This paper cites Malicious packet classification based on neural network using kitsune features.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Malicious packet classification based on neural network using kitsune features

Reference 23

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This paper cites Towards effective feature selection in machine learning- based botnet detection approaches.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Towards effective feature selection in machine learning- based botnet detection approaches

Reference 24

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A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Evasion at- tacks against machine learning at test time

Reference 25

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A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Wild patterns: Ten years after the rise of adversarial machine learning

Reference 26

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A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Evad- edroid: A practical evasion attack on machine learning for black-box android malware detection

Reference 27

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A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Sniff: reverse engi- neering of neural networks with fault attacks

Reference 28

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A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures On Evaluating Adversarial Robustness

Reference 29

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A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures De-pois: An attack-agnostic defense against data poisoning attacks

Reference 30

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A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Stateful detection of black-box adversarial attacks, 2019

Reference 31

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A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Intrusion detection for wireless edge networks based on federated learning

Reference 32

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A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Certified adversarial robustness via randomized smoothing

Reference 33

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A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Adversarial attacks against intrusion detection sys- tems: Taxonomy, solutions and open issues

Reference 34

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A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Tad: Transfer learning-based multi- adversarial detection of evasion attacks against network intrusion detection systems

Reference 35

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A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Adv-bot: Realistic adversarial botnet at- tacks against network intrusion detection systems

Reference 36

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A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures A hybrid adversarial attack for different application scenarios

Reference 37

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A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures The state of ransomware in the us: Report and statistics 2022, 2023

Reference 38

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A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Backdoor Attacks and Countermeasures on Deep Learning: A Comprehensive Review

Reference 39

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A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures A detailed anal- ysis of benchmark datasets for network intrusion detection system

Reference 40

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A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Explaining and Harnessing Adversarial Examples

Reference 41

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A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Evaluating and improving adversarial ro- bustness of machine learning-based network intru- sion detectors

Reference 42

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This paper cites Adversarial machine learning for network intrusion detection systems: a compre- hensive survey.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Adversarial machine learning for network intrusion detection systems: a compre- hensive survey

Reference 43

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A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Liuer Mihou: A Practical Framework for Generating and Evaluating Grey-box Adversarial Attacks against NIDS

Reference 44

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A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Fooling neural network interpretations via adver- sarial model manipulation

Reference 45

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A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Deep PackGen: A Deep Reinforcement Learning Framework for Adversarial Network Packet Generation

Reference 46

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This paper cites The Threat of Adversarial Attacks on Machine Learning in Network Security -- A Survey.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures The Threat of Adversarial Attacks on Machine Learning in Network Security -- A Survey

Reference 47

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A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Inves- tigation malware analysis depend on reverse en- gineering

Reference 48

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A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures A deep learning approach for net- work intrusion detection system

Reference 49

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This paper cites Adver- sarial machine learning for network intrusion de- tection: A comparative study.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Adver- sarial machine learning for network intrusion de- tection: A comparative study

Reference 50

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This paper cites Deep learning for intrusion detection and security of internet of things (iot): current analysis, challenges, and possible solu- tions.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Deep learning for intrusion detection and security of internet of things (iot): current analysis, challenges, and possible solu- tions

Reference 51

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This paper cites Channel-aware adversarial attacks against deep learning-based wireless signal classifiers.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Channel-aware adversarial attacks against deep learning-based wireless signal classifiers

Reference 52

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This paper cites Deep learning- based network intrusion detection using multiple image transformers.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Deep learning- based network intrusion detection using multiple image transformers

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:44:31.065694Z

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Observation f4cb5ebc-56c6-47a5-8364-b28ce1f6852f · outbound

This paper cites Reverse engineering of net- work signatures.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Reverse engineering of net- work signatures

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:44:31.041292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation da79bfdf-dee4-4d03-b9d8-aeed81de340f · outbound

This paper cites Black box attacks on deep anomaly detectors.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Black box attacks on deep anomaly detectors

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:44:31.020589Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation fbcb6b85-c2d9-4970-9fbf-afb201b7eec9 · outbound

This paper cites Two-phase defense against poisoning attacks on federated learning- based intrusion detection.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Two-phase defense against poisoning attacks on federated learning- based intrusion detection

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:44:30.997405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c17cb537-0b22-418c-83b4-bba41cc6e556 · outbound

This paper cites Survey on intrusion detec- tion systems based on deep learning.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Survey on intrusion detec- tion systems based on deep learning

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:44:30.977450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation da06965a-f99e-480d-865d-9a2d9c2819fb · outbound

This paper cites A review of adversarial at- tack and defense for classification methods.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures A review of adversarial at- tack and defense for classification methods

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:44:30.956755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2a2843a3-68d4-433c-9aec-55a45c8330e0 · outbound

This paper cites Deeppayload: Black-box backdoor attack on deep learning models through neural payload injection.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Deeppayload: Black-box backdoor attack on deep learning models through neural payload injection

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:44:30.936457Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation be826092-cffa-416a-bc99-bc2930c641af · outbound

This paper cites Machine learning and deep learning methods for intrusion detection sys- tems: A survey.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Machine learning and deep learning methods for intrusion detection sys- tems: A survey

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:44:30.911390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ee912a62-28c8-4df6-ac09-81ac4648a4cd · outbound

This paper cites Mitigating reverse engineering attacks on deep neural networks.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Mitigating reverse engineering attacks on deep neural networks

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:44:30.886625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5bbefe08-82d4-433a-9504-40f2137f2958 · outbound

This paper cites Functionality-preserving ad- versarial machine learning for robust classification in cybersecurity and intrusion detection domains: A survey.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Functionality-preserving ad- versarial machine learning for robust classification in cybersecurity and intrusion detection domains: A survey

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:44:30.864703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation babd9b79-b8b6-4d88-a4cd-9376e6033dff · outbound

This paper cites Black-box Model Inversion Attribute Inference Attacks on Classification Models.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Black-box Model Inversion Attribute Inference Attacks on Classification Models

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-11T12:44:28.776799Z

Source-reported events for the cited work

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Observation 274212cf-89ab-421e-8e6a-f596de769483 · outbound

This paper cites Is Deep Learning Safe for Robot Vision? Adversarial Examples against the iCub Humanoid.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Is Deep Learning Safe for Robot Vision? Adversarial Examples against the iCub Humanoid

Reference 64

Resolution: verified exact; local_arxiv, observed 2026-08-11T12:44:29.341785Z

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Observation d6c9a4f6-873d-4ad0-973b-210365e64f32 · outbound

This paper cites Inves- tigating the practicality of adversarial evasion at- tacks on network intrusion detection.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Inves- tigating the practicality of adversarial evasion at- tacks on network intrusion detection

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:44:30.844223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c15c0fcb-7e3d-4b98-b6f2-3cbf012bb02e · outbound

This paper cites Gradient-based adversarial attack detection via deep feature extrac- tion.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Gradient-based adversarial attack detection via deep feature extrac- tion

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:44:30.824122Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8a3dbe03-d3d9-4b3d-bcdb-b12d7edb7d5e · outbound

This paper cites Adversarial learning targeting deep neural network classification: A comprehensive review of defenses against attacks.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Adversarial learning targeting deep neural network classification: A comprehensive review of defenses against attacks

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:44:30.798708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4a86d037-7d5a-4686-bf95-547885324d2f · outbound

This paper cites Kitsune: An Ensemble of Autoencoders for Online Network Intrusion Detection.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Kitsune: An Ensemble of Autoencoders for Online Network Intrusion Detection

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-11T12:44:28.805604Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca0c8036-29a7-441d-a911-1a71b08b2502 · outbound

This paper cites An ensemble intrusion detection technique based on proposed statistical flow features for protecting network traffic of in- ternet of things.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures An ensemble intrusion detection technique based on proposed statistical flow features for protecting network traffic of in- ternet of things

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:44:30.773678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation de7dc7af-ce9a-4244-b40e-a75d8cbf6a73 · outbound

This paper cites Machine learning for anomaly detection: A systematic review.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Machine learning for anomaly detection: A systematic review

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:44:30.748932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8e579e2b-a62d-420b-910e-b642e40106f5 · outbound

This paper cites Ciciot2023: A real-time dataset and benchmark for large-scale attacks in iot environment, 2023.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Ciciot2023: A real-time dataset and benchmark for large-scale attacks in iot environment, 2023

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:44:30.721978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 85b89969-7285-4260-9652-ba1032a171aa · outbound

This paper cites Invisible poison: A blackbox clean label backdoor attack to deep neural networks.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Invisible poison: A blackbox clean label backdoor attack to deep neural networks

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:44:30.699518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 42d43f28-f7d1-413f-8dc3-0167ae9ae0ff · outbound

This paper cites Practical black-box attacks against ma- chine learning.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Practical black-box attacks against ma- chine learning

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:44:30.679421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f82b74d7-768a-4f93-bcd4-0c71cf3cf5cb · outbound

This paper cites Distillation as a defense to adversarial perturbations against deep neural networks.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Distillation as a defense to adversarial perturbations against deep neural networks

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:44:30.656940Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0481aab3-6bfa-4baf-979e-7bf8def7a025 · outbound

This paper cites Label sanitization against label flipping poisoning attacks.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Label sanitization against label flipping poisoning attacks

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:44:30.635088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d18c6d8e-749c-4979-b339-0f89bfbe34e0 · outbound

This paper cites Defending network intrusion detec- tion systems against adversarial evasion attacks.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Defending network intrusion detec- tion systems against adversarial evasion attacks

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:44:30.606665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 37d05e1f-b562-4e90-ba66-aca35ec90d00 · outbound

This paper cites A deep learning method to detect network intrusion through flow-based features.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures A deep learning method to detect network intrusion through flow-based features

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:44:30.580885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation bc8f2ab9-023a-4355-b1f3-ad94de59ed03 · outbound

This paper cites Intriguing proper- ties of adversarial ml attacks in the problem space, 2020.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Intriguing proper- ties of adversarial ml attacks in the problem space, 2020

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:44:30.545618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7859dddd-1db5-473f-baee-3be63e8113ce · outbound

This paper cites Review of kdd cup ‘99, nsl- kdd and kyoto 2006+ datasets.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Review of kdd cup ‘99, nsl- kdd and kyoto 2006+ datasets

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:44:30.525814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 166682e8-ce85-4614-bf17-a67b94fc2748 · outbound

This paper cites Flow-based benchmark data sets for intrusion detection.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Flow-based benchmark data sets for intrusion detection

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:44:30.502356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9284e5e3-d84b-489d-9c99-48bcca332552 · outbound

This paper cites A sur- vey of network-based intrusion detection data sets.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures A sur- vey of network-based intrusion detection data sets

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:44:30.475795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b7e60136-218c-4ff0-97ce-2d569fdf8a52 · outbound

This paper cites Adversarial machine learning at- tacks and defense methods in the cyber security do- main.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Adversarial machine learning at- tacks and defense methods in the cyber security do- main

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:44:30.455303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 83a4910d-4063-41ba-9a78-92da45ba32cb · outbound

This paper cites Adversarial network traffic: Towards evaluating the robustness of deep-learning-based network traffic classification.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Adversarial network traffic: Towards evaluating the robustness of deep-learning-based network traffic classification

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:44:30.436382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2939973b-09e4-430d-8eb5-bfe6f544ecd9 · outbound

This paper cites Predatory Medicine: Exploring and Measuring the Vulnerability of Medical AI to Predatory Science.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Predatory Medicine: Exploring and Measuring the Vulnerability of Medical AI to Predatory Science

Reference 84

Resolution: verified exact; local_arxiv, observed 2026-08-11T12:44:29.288297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7f32ff95-fd37-40ab-881f-bdc11122578b · outbound

This paper cites Towards a standard feature set for net- work intrusion detection system datasets.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Towards a standard feature set for net- work intrusion detection system datasets

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:44:30.411368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d176da7a-088e-41f1-95a1-ecb6620e1f85 · outbound

This paper cites Just how toxic is data poisoning? a unified bench- mark for backdoor and data poisoning attacks.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Just how toxic is data poisoning? a unified bench- mark for backdoor and data poisoning attacks

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:44:30.389646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation bd1521ad-0b6a-4032-b7e9-94d08daef469 · outbound

This paper cites {Explanation-Guided} backdoor poison- ing attacks against malware classifiers.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures {Explanation-Guided} backdoor poison- ing attacks against malware classifiers

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:44:30.370260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8ba2dfe6-4f35-4f94-ad53-148474be3f6c · outbound

This paper cites Poison frogs! tar- geted clean-label poisoning attacks on neural net- works.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Poison frogs! tar- geted clean-label poisoning attacks on neural net- works

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:44:30.346733Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a1349066-78c5-4539-bfa3-ed02274ceb6d · outbound

This paper cites The sunburst hack was massive and devastating, 2021.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures The sunburst hack was massive and devastating, 2021

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:44:30.326159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8f2c1c83-de46-4373-b5ee-dd4e9ca1f5e7 · outbound

This paper cites Toward generating a new intru- sion detection dataset and intrusion traffic charac- terization.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Toward generating a new intru- sion detection dataset and intrusion traffic charac- terization

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:44:30.302543Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 95ce470f-c859-438a-98aa-fb576f5d5391 · outbound

This paper cites Developing realistic distributed denial of service (ddos) attack dataset and taxonomy.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Developing realistic distributed denial of service (ddos) attack dataset and taxonomy

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:44:30.279726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 47e95906-3ce1-4987-9466-7008192761d7 · outbound

This paper cites Evasion and causative attacks with adversarial deep learn- ing.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Evasion and causative attacks with adversarial deep learn- ing

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:44:30.256455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a6803e49-bc96-4d09-8b1f-8a4e952d4b48 · outbound

This paper cites Toward developing a systematic approach to generate benchmark datasets for intru- sion detection.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Toward developing a systematic approach to generate benchmark datasets for intru- sion detection

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:44:30.231807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1376f75a-1f4d-423a-8e00-d7dd2612b36c · outbound

This paper cites A deep learning approach to network intrusion detection.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures A deep learning approach to network intrusion detection

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:44:30.207706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2b52e142-16b6-48ce-8f85-0adcd8708de9 · outbound

This paper cites Statistical analysis of honeypot data and build- ing of kyoto 2006+ dataset for nids evaluation.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Statistical analysis of honeypot data and build- ing of kyoto 2006+ dataset for nids evaluation

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:44:30.177577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 07625a8b-bef5-496d-9b26-22bde433c8db · outbound

This paper cites Adversarial at- tacks against deep generative models on data: a survey.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Adversarial at- tacks against deep generative models on data: a survey

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:44:30.154212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8c9fa008-2823-4abc-9efb-f2909b4835cf · outbound

This paper cites Intriguing properties of neural networks.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures Intriguing properties of neural networks

Reference 97

Resolution: unresolved; no resolver link, observed 2026-08-11T12:44:28.989159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a82019e0-7cd6-4377-be61-a002570bbc3a · outbound

This paper cites A sensitivity analysis of poisoning and evasion attacks in network intrusion detection system machine learning models.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures A sensitivity analysis of poisoning and evasion attacks in network intrusion detection system machine learning models

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:44:30.121309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ab46eb1c-3bda-4a4e-b166-628cf3b98ec0 · outbound

This paper cites A detailed analysis of the kdd cup 99 data set.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures A detailed analysis of the kdd cup 99 data set

Reference 99

Resolution: unresolved; no resolver link, observed 2026-08-11T12:44:29.003027Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 062ff6a1-e741-45aa-ac6e-8f8a83ab1905 · outbound

This paper cites A review of the advancement in intrusion detection datasets.

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures A review of the advancement in intrusion detection datasets

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:44:30.074487Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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