{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,21]],"date-time":"2025-11-21T18:06:27Z","timestamp":1763748387209,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":34,"publisher":"Springer Singapore","isbn-type":[{"type":"print","value":"9789811629938"},{"type":"electronic","value":"9789811629945"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-981-16-2994-5_15","type":"book-chapter","created":{"date-parts":[[2021,6,7]],"date-time":"2021-06-07T16:09:57Z","timestamp":1623082197000},"page":"177-191","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["A Multi-Agent-Based System for Intrusion Detection"],"prefix":"10.1007","author":[{"given":"Younes","family":"Tesnim","sequence":"first","affiliation":[]},{"given":"Jemili","family":"Farah","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,6,8]]},"reference":[{"key":"15_CR1","doi-asserted-by":"crossref","unstructured":"Sarker, I.H., Abushark, Y.B., Alsolami, F., Khan, A.I.: IntruDTree: A Machine Learning Based Cyber Security Intrusion Detection Model, p. 754. Symmetry. Multidisciplinary Digital Publishing Institute (2020)","DOI":"10.20944\/preprints202004.0481.v1"},{"key":"15_CR2","unstructured":"Dounya, K., Okba, K., Hamza, S., Safa, S., Iman, H., Omar, B.: A new approach based mobile agent system for ensuring secure big data transmission and storage. In: 2017 International Conference on Mathematics and Information Technology (ICMIT), pp. 196\u2013200. IEEE (2017)"},{"key":"15_CR3","unstructured":"Apache Spark. Apache Spark. [Online], 6 January 2021. https:\/\/spark.apache.org\/"},{"key":"15_CR4","unstructured":"Apache Hadoop. Apache Hadoop. [Online] (2020). https:\/\/hadoop.apache.org\/"},{"key":"15_CR5","unstructured":"Benyettou, N.: Mod\u00e9lisation des Syst\u00e8mes Immunitaires Artificiel par les Syst\u00e8mes Multi-Agents Pour la D\u00e9tection d\u2019intrusion dans les r\u00e9seaux Informatique, 14 November 2017"},{"key":"15_CR6","doi-asserted-by":"crossref","unstructured":"Louati, F., Ktata, F.B.: A Deep Learning-Based Multi-agent System for Intrusion Detection, pp. 1\u201313. SN Applied Sciences. Springer (2020)","DOI":"10.1007\/s42452-020-2414-z"},{"key":"15_CR7","unstructured":"Mokhtari, S.M., Moulkhaloua, A.: Syst\u00e8me DE D\u00e9tection D\u2019intrusions Informatiquespar Syst\u00e8me Multi Agents (2018)"},{"key":"15_CR8","doi-asserted-by":"crossref","unstructured":"Ouiazzane, S., Addou, M., Barramou, F.: A multi-agent model for network intrusion detection. In: 2019 1st International Conference on Smart Systems and Data Science (ICSSD). IEEE (2019)","DOI":"10.1109\/ICSSD47982.2019.9003119"},{"key":"15_CR9","unstructured":"Hafsa, M., Jemili, F.: Comparative Study between Big Data Analysis Techniques in Intrusion Detection, p. 1. Big Data and Cognitive Computing"},{"key":"15_CR10","doi-asserted-by":"crossref","unstructured":"Belouch, M., El Hadaj, S., Idhammad, M.: Performance evaluation of intrusion detection based on machine learning using Apache Spark. Procedia Comput. Sci. 1\u20136 (2018)","DOI":"10.1016\/j.procs.2018.01.091"},{"key":"15_CR11","doi-asserted-by":"crossref","unstructured":"Zhang, H., Dai, S., Li, Y., Zhang, W.: Real-time distributed-random-forest-based network intrusion detection system using Apache spark. In: 2018 IEEE 37th International Performance Computing and Communications Conference (IPCCC), pp. 1\u20137. IEEE (2018)","DOI":"10.1109\/PCCC.2018.8711068"},{"key":"15_CR12","unstructured":"Saravanan, S., et al.: Performance evaluation of classification algorithms in the design of Apache Spark based intrusion detection system. In: 2020 5th International Conference on Communication and Electronics Systems (ICCES), pp. 443\u2013447.  IEEE (2020)"},{"key":"15_CR13","doi-asserted-by":"crossref","unstructured":"Karatas, G., Demir, O., Sahingoz, O.K.: Increasing the Performance of Machine Learning-Based IDSs on an Imbalanced and Up-to-Date Dataset, pp. 32150\u201332162. IEEE Access (2020)","DOI":"10.1109\/ACCESS.2020.2973219"},{"key":"15_CR14","doi-asserted-by":"crossref","unstructured":"Ferrag, M.A., Maglaras, L., Janicke, H., Smith, R.: Deep learning techniques for cyber security intrusion detection: a detailed analysis. In: 6th International Symposium for ICS & SCADA Cyber Security Research, pp. 126\u2013136 (2019)","DOI":"10.14236\/ewic\/icscsr19.16"},{"key":"15_CR15","unstructured":"Lypa, B., Iver, O., Kifer, V.: Application of machine learning methods for network intrusion detection system (2019)"},{"key":"15_CR16","doi-asserted-by":"crossref","unstructured":"Kim, J., Shin, Y., Choi, E., et al.: An intrusion detection model based on a convolutional neural network.  J. Multimed. Inf. Syst. 165\u2013172 (2019)","DOI":"10.33851\/JMIS.2019.6.4.165"},{"key":"15_CR17","unstructured":"IDS 2018 | Datasets. unb.ca\/cic\/datasets\/ids-2018. [Online] (2018). https:\/\/www.unb.ca\/cic\/datasets\/ids-2018.html"},{"key":"15_CR18","unstructured":"Foukia, N., Hulaas, J.G., Harms, J.: Intrusion Detection with Mobile Agents (2001)"},{"key":"15_CR19","unstructured":"Achbarou, O., El Kiram, M.A., Bourkoukou, O., Elbouanani, S.: A new distributed intrusion detection system based on multi-agent system for cloud environment. Int. J. Commun. Netw. Inf. Secur. (Kohat University of Science and Technology (KUST)) 526 (2018)"},{"key":"15_CR20","doi-asserted-by":"crossref","unstructured":"Anusha, K., Usha Rani, K.: Performance evaluation of Spark SQL for batch processing. In: Emerging Research in Data Engineering Systems and Computer Communications, pp. 145\u2013153. Springer (2020)","DOI":"10.1007\/978-981-15-0135-7_13"},{"key":"15_CR21","unstructured":"Apache Spark\u2122. [Online] (2020). https:\/\/databricks.com\/spark\/about"},{"key":"15_CR22","doi-asserted-by":"crossref","unstructured":"Salloum, S., Dautov, R., Chen, X., Peng, P.X., Huang, J.Z.: Big data analytics on Apache Spark. Int. J. Data Sci. Anal. (Springer) 145\u2013164 (2016)","DOI":"10.1007\/s41060-016-0027-9"},{"key":"15_CR23","doi-asserted-by":"crossref","unstructured":"Morfino, V., Rampone, S.: Towards Near-Real-Time Intrusion Detection for IoT Devices using Supervised Learning and Apache Spark, p. 444. Electronics. Multidisciplinary Digital Publishing Institute (2020)","DOI":"10.3390\/electronics9030444"},{"key":"15_CR24","doi-asserted-by":"crossref","unstructured":"Satapathy, S.C., Bhateja, V., Das, S.: Smart intelligent computing and applications. In: Proceedings of the Second International Conference on SCI (2018)","DOI":"10.1007\/978-981-13-1927-3"},{"key":"15_CR25","unstructured":"How to Overcome the Limitations of RDD in Apache Spark? [Online]. https:\/\/data-flair.training\/blogs\/apache-spark-rdd-limitations\/"},{"key":"15_CR26","unstructured":"What-microsoft-azure-is-and-why-it-matters. [Online] (2018). https:\/\/ccbtechnology.com\/what-microsoft-azure-is-and-why-it-matters\/"},{"key":"15_CR27","unstructured":"Rachburee, N., Punlumjeak, W.: Big data analytics: feature selection and machine learning for intrusion detection on microsoft azure platform. J. Telecommun. Electron. Comput. Eng. (JTEC) 107\u2013111 (2017)"},{"key":"15_CR28","unstructured":"Blob storage. [Online]. https:\/\/azure.microsoft.com\/en-us\/services\/storage\/blobs\/"},{"key":"15_CR29","unstructured":"Quinto, B.: XGBoost, Covers and LightGBM, Spark NLP. In: Next-Generation Machine Learning with Spark. Springer"},{"key":"15_CR30","doi-asserted-by":"crossref","unstructured":"Quinto, B.: Introduction to Spark and Spark MLlib. In: Next-Generation Machine Learning with Spark, pp. 29\u201396. Springer (2020)","DOI":"10.1007\/978-1-4842-5669-5_2"},{"key":"15_CR31","unstructured":"Chourasiya, R., Patel, V., Shrivastava, A.: Classification of cyber attack using machine learning technique at microsoft azure cloud.  Int. Res. J. Eng. Appl. Sci. (2018)"},{"key":"15_CR32","doi-asserted-by":"crossref","unstructured":"Dahiya, P., Srivastava, D.K.: Network intrusion detection in big dataset using Spark. Procedia Comp. Sci. (Elsevier) 253\u2013262 (2018)","DOI":"10.1016\/j.procs.2018.05.169"},{"key":"15_CR33","doi-asserted-by":"crossref","unstructured":"Khan, M.A., Kim, J.: Toward Developing Efficient Conv-AE-Based Intrusion Detection System Using Heterogeneous Dataset, p. 1771. Electronics. Multidisciplinary Digital Publishing Institute (2020)","DOI":"10.3390\/electronics9111771"},{"key":"15_CR34","doi-asserted-by":"crossref","unstructured":"Ranjana, P., et al.: Anomaly detection of DDOS attacks using Hadoop. In: Emerging Research in Computing, Information, Communication and Applications, pp. 543\u2013552. Springer (2019)","DOI":"10.1007\/978-981-13-5953-8_45"}],"container-title":["Smart Innovation, Systems and Technologies","Agents and Multi-Agent Systems: Technologies and Applications 2021"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-16-2994-5_15","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,6,7]],"date-time":"2021-06-07T16:13:33Z","timestamp":1623082413000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-16-2994-5_15"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9789811629938","9789811629945"],"references-count":34,"URL":"https:\/\/doi.org\/10.1007\/978-981-16-2994-5_15","relation":{},"ISSN":["2190-3018","2190-3026"],"issn-type":[{"type":"print","value":"2190-3018"},{"type":"electronic","value":"2190-3026"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"8 June 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}}]}}