Pitfalls in Machine Learning for Computer Security.

Authors: Arp, Daniel^1,2, d.arp@tu-berlin.de, Quiring, Erwin^3,4, erwin.quiring@rub.de, Pendlebury, Feargus⁵, feargus@trustypatch.es, Warnecke, Alexander^1,2, a.warnecke@tu-berlin.de, Pierazzi, Fabio⁶, fabio.pierazzi@kcl.ac.uk, Wressnegger, Christian^7,8, c.wressnegger@kit.edu, Cavallaro, Lorenzo⁵, l.cavallaro@ucl.ac.uk, Rieck, Konrad^1,2, rieck@tu-berlin.de

Source: Communications of the ACM; Nov2024, Vol. 67 Issue 11, p104-112, 9p

RESEARCH AND IMPLEMENTATION OF CAMPUS NETWORK INTRUSION DETECTION SYSTEM BASED ON DATA MINING AND IMAGE PROCESSING.

Authors: ZHE ZHANG¹, ZheZhang56@126.com

Source: Scalable Computing: Practice & Experience; Mar2025, Vol. 26 Issue 2, p691-698, 8p

Making a Real-Time IoT Network Intrusion-Detection System (INIDS) Using a Realistic BoT–IoT Dataset with Multiple Machine-Learning Classifiers.

Authors: Ashraf, Jawad¹, mashraf.dphd19seecs@seecs.edu.pk, Raza, Ghulam Musa², ghulammusaraza96@gmail.com, Kim, Byung-Seo², jsnbs@hongik.ac.kr, Wahid, Abdul³, a.wahid@bham.ac.uk, Kim, Hye-Young⁴, hykim@hongik.ac.kr

Source: Applied Sciences (2076-3417); Feb2025, Vol. 15 Issue 4, p2043, 19p

Deep Learning vs. Machine Learning for Intrusion Detection in Computer Networks: A Comparative Study.

Authors: Ali, Md Liakat¹, mdali@rider.edu, Thakur, Kutub², thakurk@stjohns.edu, Schmeelk, Suzanna², schmeels@stjohns.edu, Debello, Joan², debelloj@stjohns.edu, Dragos, Denise², dragosd@stjohns.edu

Source: Applied Sciences (2076-3417); Feb2025, Vol. 15 Issue 4, p1903, 19p

Adaptive Semi-Supervised Algorithm for Intrusion Detection and Unknown Attack Identification.

Authors: Li, Meng¹, horimon@163.com, Luo, Lei¹, lluo@uestc.edu.cn, Xiao, Kun¹, Wang, Geng¹, Wang, Yintao¹

Source: Applied Sciences (2076-3417); Feb2025, Vol. 15 Issue 4, p1709, 17p

Enhancing Cloud Data Center Security through Deep Learning: A Comparative Analysis of RNN, CNN, and LSTM Models for Anomaly and Intrusion Detection.

Authors: Ahmed, Shimaa A.¹, shaima.ahmad@nbu.edu, Khalifa, Entisar H.², entisar.osman@nbu.edu.sa, Nawaz, Majid², majed.nawaz@nbu.edu.sa, Abdalla, Faroug A.², faroug.abdalla@nbu.edu.sa, Mahmoud, Ashraf F. A.², ashraf.abubaker@nbu.edu.sa

Source: Engineering, Technology & Applied Science Research; Feb2025, Vol. 15 Issue 1, p20071-20076, 6p

Intrusion detection and prevention using Bayesian decision with fuzzy logic system.

Authors: Sekar, Satheeshkumar¹, satheeshkumar.sekar24@gmail.com, Parvathy, Palaniraj Rajidurai¹, palanirajrps@gmail.com, Gupta, Gopal Kumar², gopalgupta.iitbhu90@gmail.com, Rajagopalan, Thiruvenkadachari³, rajgopalant@gmail.com, Basavaraddi, Chethan Chandra Subhash Chandra Basappa⁴, raddi04@yahoo.com, Padmanaban, Kuppan⁵, padmanaban.k@yahoo.com, Murugan, Subbiah⁶, smuresjur@gmail.com

Source: International Journal of Electrical & Computer Engineering (2088-8708); Feb2025, Vol. 15 Issue 1, p1200-1208, 9p

Anomaly detection method of traction motor bearing based on multi-scale sub-band fuzzy entropy manifold fusion index.

Authors: Guangbin Wang^1,2, jxxwgb@126.com, Shubiao Zhao^1,3, zhaonne@163.com, Zhixian Zhong², 2005zhzhx@163.com, Ying Lv¹, lvying1108@163.com, Changsheng Shao⁴, shaocs@zjblab.com, Hui Zhang², 2952617612@qq.com

Source: Journal of Vibroengineering; Feb2025, Vol. 27 Issue 1, p58-77, 20p

ResInceptNet-SA: A Network Traffic Intrusion Detection Model Fusing Feature Selection and Balanced Datasets.

Authors: Liu, Guorui^1,2,3, lgr@tcu.edu.cn, Zhang, Tianlin¹, ztl12593@163.com, Dai, Hualin¹, chengxinyang0@126.comdaihualin@tcu.edu.cn, Cheng, Xinyang¹, yangdaoxuan0915@163.com, Yang, Daoxuan¹

Source: Applied Sciences (2076-3417); Jan2025, Vol. 15 Issue 2, p956, 19p

Empowering Intrusion Detection Systems: A Synergistic Hybrid Approach with Optimization and Deep Learning Techniques for Network Security.

Authors: Chinnasamy, Ramya¹, ramya.me@gmail.com, Subramanian, Malliga¹, mallinishanth72@gmail.com, Sengupta, Nandita², ngupta@ucb.edu.bh

Source: International Arab Journal of Information Technology (IAJIT); Jan2025, Vol. 22 Issue 1, p60-76, 17p

Intrusion detection based on generative adversarial network with random forest for cloud networks.

Authors: Rosline, Gnanam Jeba¹, jebaroslineies@gmail.com, Rani, Pushpa², drpushpa.mtwu@gmail.com

Source: International Journal of Electrical & Computer Engineering (2088-8708); Apr2025, Vol. 15 Issue 2, p2491-2498, 8p

Advancing network security: a comparative research of machine learning techniques for intrusion detection.

Authors: Rysbekov, Shynggys¹, obershyngys@gmail.com, Aitbanov, Abylay¹, abylai.aitbanov@gmail.com, Abdiakhmetova, Zukhra², zuhra.abdyahmetova@kaznu.edu.kz, Kartbayev, Amandyk¹, a.kartbayev@gmail.com

Source: International Journal of Electrical & Computer Engineering (2088-8708); Apr2025, Vol. 15 Issue 2, p2271-2281, 11p

DCNN: a novel binary and multi-class network intrusion detection model via deep convolutional neural network.

Authors: Shebl, Ahmed¹, ahmed_shebl@sci.psu.edu.eg, Elsedimy, E. I.², elsodamey_sayed@himc.psu.edu.eg, Ismail, A.¹, amr_ismail@sci.psu.edu.eg, Salama, A. A.¹, drsalama44@gmail.com, Herajy, Mostafa¹, mherajy@sci.psu.edu.eg

Source: EURASIP Journal on Information Security; 12/20/2024, Vol. 2024 Issue 1, p1-23, 23p

Whale Optimization Algorithm-Enhanced Long Short-Term Memory Classifier with Novel Wrapped Feature Selection for Intrusion Detection.

Authors: AL-Husseini, Haider¹, haideren82@gmail.com, Hosseini, Mohammad Mehdi², hosseini_mm@shahroodut.ac.ir, Yousofi, Ahmad¹, a.yousofi@khuisf.ac.ir, Alazzawi, Murtadha A.³, murtadhaali@iku.edu.iq

Source: Journal of Sensor & Actuator Networks; Dec2024, Vol. 13 Issue 6, p73, 29p

Dynamic Arithmetic Optimization Algorithm with Deep Learning-based Intrusion Detection System in Wireless Sensor Networks.

Authors: Nirmal, K.¹, nirmalphd21@gmail.com, Murugan, S.², smuruganmpt79@gmail.com

Source: Engineering, Technology & Applied Science Research; Dec2024, Vol. 14 Issue 6, p18453-18458, 6p

Intrusion Detection in IoT using Gaussian Fuzzy Mutual Information-based Feature Selection.

Authors: Abu Saq, Abdullah Hussain¹, ahabusaq@nu.edu.sa, Zainal, Anazida², anazida@utm.my, Saleh Al-Rimy, Bander Ali³, bander.al-rimy@port.ac.uk, Alyami, Abdulrahman⁴, am.yami@ju.edu.sa, Abosaq, Hamad Ali⁵, haabosaq@nu.edu.sa

Source: Engineering, Technology & Applied Science Research; Dec2024, Vol. 14 Issue 6, p17564-17571, 8p

A Generalized and Robust Nonlinear Approach based on Machine Learning for Intrusion Detection.

Authors: Rahman, Jakiur¹, Singh, Jaskaran², Nayak, Soumen¹, Jena, Biswajit¹, Mohanty, Lopamudra³, Singh, Narpinder⁴, Laird, John R.⁵, Singh, Rajesh⁶, Garg, Deepak⁷, Khanna, Narendra N.⁸, Fouda, Mostafa M.⁹, Saba, Luca¹⁰, Suri, Jasjit S.^2,9,11,12, jasjit.suri@atheropoint.com

Source: Applied Artificial Intelligence; 2024, Vol. 38 Issue 1, p1-34, 34p

Intrusion Detection with Ant Colony Optimization Based Feature Selection and XGboost Classifier.

Authors: Bhardwaj, Shweta¹, sbhardwaj1@amity.edu, Rawat, Seema², Maringanti, Hima Bindu³

Source: International Journal of Performability Engineering; Nov2024, Vol. 20 Issue 11, p649-657, 9p

An Intrusion Detection Model for Internet of Medical Things Using BDA-DAN2 Model.

Authors: Alhazmi, Raid Mohsen¹, ralhazmi@ut.edu.sa

Source: International Journal of Online & Biomedical Engineering; 2024, Vol. 20 Issue 16, p145-169, 25p

Efficient Based on Improved Random Forest Defense System Against Application‐Layer DDoS Attacks.

Authors: He, Junjiang^1,2, Fang, Wenbo^1,2, fangwenbo@stu.scu.edu.cn, Lan, Xiaolong^1,2, xiaolonglan@scu.edu.cn, Yang, Geying³, Chen, Ziyu¹, Chen, Yang¹, Li, Tao^1,2, Chen, Jiangchuan¹, Li, Jin

Source: International Journal of Intelligent Systems; 11/1/2024, Vol. 2024, p1-19, 19p