CIC-IDS2017 / CSE-CIC-IDS2018

data category: Cybersecurity and anomaly detection benchmarks · 0 papers in the last 7 days

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Network traffic, intrusion, fraud and anomaly records used to compare detection methods.

Names searched for: CIC-IDS2017, CICIDS2017, CIC-IDS-2017, CSE-CIC-IDS2018, CIC-IDS2018, CICIDS2018

Key findings#

From Nov 2023 to Oct 2026, 96 archived papers mentioned CIC-IDS2017 / CSE-CIC-IDS2018 in their title, abstract or keywords (the search of earlier months' full texts is still under way), most of them in Apr 2025 (8).
CIC-IDS2017 / CSE-CIC-IDS2018 was mentioned in 1 paper in the last 30 days (2026-10-07 to 2026-11-05), ranking #165 of the 246 datasets mentioned.
By journal category: Information Systems (1).
Most of them appeared in Computers & Security (1).
From 2017 to 2026 (so far), CIC-IDS2017 / CSE-CIC-IDS2018 was mentioned in 141 papers in the tracked journals, most of them in AI (105), information systems (35) and operations research (1).
36 of them were published in 2025, against 0 in 2017.
Since 2023, the institutions with the most of these papers were Imam Mohammad ibn Saud Islamic University (3), Al-Balqa Applied University (2) and Beihang University (2).
The journals publishing most of them were Computers & Security (21), Neural Computing and Applications (17) and Artificial Intelligence Review (14).
The most-cited of them is “A survey on intrusion detection system: feature selection, model, performance measures, application perspective, challenges, and future research directions” (Artificial Intelligence Review, 2021), with 355 citations.
Papers use CIC-IDS2017 / CSE-CIC-IDS2018 most often with NSL-KDD / KDD Cup 99 (65), UNSW-NB15 (53) and IoT intrusion data (Bot-IoT, TON_IoT, CICIoT2023) (43); it has 10 partners in the code and data network, in the group around NSL-KDD / KDD Cup 99, UNSW-NB15, CIC-IDS2017 /….

Mentions over 36 months#

Papers mentioning it by publication month, Nov 2023 to Oct 2026 (titles, abstracts and keywords; the full texts of earlier months are still being searched)
Trend	Nov 23–Oct 24	Nov 24–Oct 25	Nov 25–Oct 26	36 months
	29	38	29	96

Papers per year#

20172026 (so far)

Papers per publication year and category
Category	2019	2020	2021	2022	2023	2024	2025	2026 (so far)
AI	0	3	8	6	10	23	33	22
Information Systems	1	2	3	3	11	7	3	5
Operations Research	0	0	0	0	1	0	0	0
All categories	1	5	11	9	22	30	36	27

Where the papers come from#

Journals with the most papers, since 2023
#	Journal	Papers
1	Computers & Security	21
2	Neural Computing and Applications	17
3	Artificial Intelligence Review	14
4	Journal Of Big Data	14
5	Expert Systems with Applications	12
6	Knowledge-Based Systems	10
7	Applied Intelligence	6
8	Telematics and Informatics Reports	4
9	Knowledge and Information Systems	3
10	Information Sciences	2

Institutions with the most papers, since 2023
#	Institution	Papers
1	Imam Mohammad ibn Saud Islamic University	3
2	Al-Balqa Applied University	2
3	Beihang University	2
4	Beijing University of Posts and Telecommunications	2
5	Deakin University	2
6	Edinburgh Napier University	2
7	King Faisal University	2
8	King Saud University	2
9	Koneru Lakshmaiah Education Foundation	2
10	Lancaster University	2

Countries with the most papers, since 2023
#	Country	Papers
1	China	25
2	India	15
3	Saudi Arabia	12
4	United Kingdom	10
5	United States	8
6	Jordan	7
7	Pakistan	7
8	Australia	6
9	United Arab Emirates	5
10	Egypt	5

Keywords with the most papers, since 2023
#	Keyword	Papers
1	CICIDS2017	44
2	intrusion detection	38
3	network intrusion detection	30
4	Internet of Things security	24
5	network traffic classification	24
6	CSE-CIC-IDS2018	23
7	feature selection	19
8	NSL-KDD dataset	17
9	class imbalance	16
10	intrusion detection systems	16

Most-cited papers#

Most-cited papers since 2017
#	Citations	Per month	Title	Journal	Published	Authors
1	355	5.5	A survey on intrusion detection system: feature selection, model, performance measures, application perspective, challenges, and future research directions	Artificial Intelligence Review	2021-07-01	Ankit Thakkar, Ritika Lohiya
2	338	4.9	Dynamically Weighted Balanced Loss: Class Imbalanced Learning and Confidence Calibration of Deep Neural Networks	IEEE Transactions on Neural Networks and Learning Systems	2021-01-14	K. Ruwani M. Fernando, Chris P. Tsokos
3	315	9.7	Machine learning-based network intrusion detection for big and imbalanced data using oversampling, stacking feature embedding and feature extraction	Journal Of Big Data	2024-02-22	Md. Alamin Talukder, Md. Manowarul Islam, Md. Ashraf Uddin et al.
4	269	3.8	A survey and analysis of intrusion detection models based on CSE-CIC-IDS2018 Big Data	Journal Of Big Data	2020-11-23	Joffrey L. Leevy, Taghi M. Khoshgoftaar
5	266	6.0	DCNNBiLSTM: An Efficient Hybrid Deep Learning-Based Intrusion Detection System	Telematics and Informatics Reports	2023-03-07	Vanlalruata Hnamte, Jamal Hussain

Archive counts by publication year: a paper counts when its title, abstract or keywords name the dataset, or when OpenAlex's full-text search finds it there (searched for the last 30 days' papers and, by a pass over the past years, for older ones). Names added to the list later are looked for in older papers as the archive is read again.

Used together with#

Papers use CIC-IDS2017 / CSE-CIC-IDS2018 most often with NSL-KDD / KDD Cup 99 (65), UNSW-NB15 (53) and IoT intrusion data (Bot-IoT, TON_IoT, CICIoT2023) (43); it has 10 partners in the code and data network, in the group around NSL-KDD / KDD Cup 99, UNSW-NB15, CIC-IDS2017 /…. The whole network →

What papers use CIC-IDS2017 / CSE-CIC-IDS2018 together with (at least 3 papers; lift 1 = chance)
Used with	Type	Papers using both	Lift
NSL-KDD / KDD Cup 99	Dataset	65	95.1
UNSW-NB15	Dataset	53	113.1
IoT intrusion data (Bot-IoT, TON_IoT, CICIoT2023)	Dataset	43	143.0
Kaggle	Dataset	8	4.7
CIFAR-10 / CIFAR-100	Dataset	6	1.5
MNIST / Fashion-MNIST	Dataset	5	1.5
MODIS	Dataset	4	3.3
UCI Machine Learning Repository	Dataset	4	2.1
Hugging Face Hub	Dataset	3	2.2
lightgbm-org/LightGBM	Code repository	3	113.1

Papers mentioning CIC-IDS2017 / CSE-CIC-IDS2018 in the last 30 days, newest first.
Date	Title	Journal	Authors	Affiliations
2026-10-24	How evaluation protocol choices inflate intrusion detection accuracy: A three-dataset systematic study	Computers & Security	Mohammed BERHILI, Omar Chaieb, Mohammed Benabdellah	Mohamed I University

Cite this page

Scholar4AI. (2026). CIC-IDS2017 / CSE-CIC-IDS2018. Journal and Conference Research Rankings. Retrieved November 5, 2026, from https://scholar4ai.com/datasets/cic-ids2017-cse-cic-ids2018

@misc{scholar4ai-datasets-cic-ids2017-cse-cic-ids2018,
  author = {{Scholar4AI}},
  title = {CIC-IDS2017 / CSE-CIC-IDS2018},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/datasets/cic-ids2017-cse-cic-ids2018}},
  urldate = {2026-11-05},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

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