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2020 – today
- 2024
[j9]Ahlem Abid
, Farah Jemili, Ouajdi Korbaa:
Real-time data fusion for intrusion detection in industrial control systems based on cloud computing and big data techniques. Clust. Comput. 27(2): 2217-2238 (2024)- [j8]Farah Jemili, Rahma Meddeb, Ouajdi Korbaa:
Intrusion detection based on ensemble learning for big data classification. Clust. Comput. 27(3): 3771-3798 (2024) - [j7]Farah Jemili, Ouajdi Korbaa:
Active intrusion detection and prediction based on temporal big data analytics. Int. J. Knowl. Based Intell. Eng. Syst. 28(2): 389-418 (2024) - [j6]Ahmed Aljabri, Farah Jemili, Ouajdi Korbaa:
Intrusion detection in cyber-physical system using rsa blockchain technology. Multim. Tools Appl. 83(16): 48119-48140 (2024) - 2023
- [j5]Farah Jemili:
Intelligent intrusion detection based on fuzzy Big Data classification. Clust. Comput. 26(6): 3719-3736 (2023) - [j4]Farah Jemili:
Towards data fusion-based big data analytics for intrusion detection. J. Inf. Telecommun. 7(4): 409-436 (2023) - [j3]Ahlem Abid, Farah Jemili, Ouajdi Korbaa:
Distributed deep learning approach for intrusion detection system in industrial control systems based on big data technique and transfer learning. J. Inf. Telecommun. 7(4): 513-541 (2023) - [j2]Rahma Meddeb, Farah Jemili, Bayrem Triki, Ouajdi Korbaa:
A deep learning-based intrusion detection approach for mobile Ad-hoc network. Soft Comput. 27(14): 9425-9439 (2023) - [c21]Mohamed Ala Eddine Bahri, Farah Jemili, Ouajdi Korbaa:
Towards Deep Learning and Blockchain-based Intrusion Detection System. CW 2023: 357-364 - [c20]Islem Chouchen, Farah Jemili:
Intrusion Detection based on Incremental Learning. CW 2023: 448-455 - 2022
- [c19]Ahlem Abid, Farah Jemili, Ouajdi Korbaa:
Distributed Architecture of an Intrusion Detection System in Industrial Control Systems. ICCCI (CCIS Volume) 2022: 472-484 - [c18]Kamel Yasmine Kamel, Farah Jemili, Rahma Meddeb:
Ensemble Learning Based Big Data Classification for Intrusion Detection. ISDA (1) 2022: 501-511 - 2021
- [c17]Roua Dhahbi, Farah Jemili:
A Deep Learning Approach for Intrusion Detection. HPCC/DSS/SmartCity/DependSys 2021: 1211-1218 - [c16]Tesnim Younes, Farah Jemili:
A Multi-Agent-Based System for Intrusion Detection. KES-AMSTA 2021: 177-191 - 2020
- [c15]Marwa Elayni, Farah Jemili, Ouajdi Korbaa, Basel Solaiman:
A new features vector matching for big heterogeneous data in intrusion detection context. ATSIP 2020: 1-5 - [c14]Ahlem Abid, Farah Jemili:
Intrusion Detection based on Graph oriented Big Data Analytics. KES 2020: 572-581
2010 – 2019
- 2019
- [j1]Mounir Hafsa, Farah Jemili:
Comparative Study between Big Data Analysis Techniques in Intrusion Detection. Big Data Cogn. Comput. 3(1): 1 (2019) - [c13]Rahma Meddeb, Bayrem Triki, Farah Jemili, Ouajdi Korbaa:
Dataset for Intrusion Detection in Mobile Ad-Hoc Networks. ISDA 2019: 24-34 - [c12]Mondher Essid, Farah Jemili, Ouajdi Korbaa:
Distributed Architecture of Snort IDS in Cloud Environment. ISDA 2019: 100-111 - [c11]Marwa Elayni, Farah Jemili, Ouajdi Korbaa, Basel Solaiman:
Big Data Processing for Intrusion Detection System Context: A Review. ISDA 2019: 122-131 - [c10]Rahma Meddeb, Farah Jemili, Bayrem Triki, Ouajdi Korbaa:
Anomaly-based Behavioral Detection in Mobile Ad-Hoc Networks⁎. KES 2019: 77-86 - 2018
- [c9]Rahma Meddeb, Bayrem Triki, Farah Jemili, Ouajdi Korbaa:
An Effective IDS Against Routing Attacks on Mobile Ad-Hoc Networks. SoMeT 2018: 201-214 - 2017
- [c8]Imen Gaied, Farah Jemili, Ouajdi Korbaa:
Neuro-fuzzy and genetic-fuzzy based approaches in intrusion detection: Comparative study. SoftCOM 2017: 1-6 - 2016
- [c7]Mariem Belhor, Farah Jemili:
Intrusion detection based on genetic fuzzy classification system. AICCSA 2016: 1-8 - [c6]Imen Gaied, Farah Jemili, Ouajdi Korbaa:
A Genetic-Fuzzy Classification Approach to Improve High-Dimensional Intrusion Detection System. ISDA 2016: 319-329 - [c5]Mondher Essid, Farah Jemili:
Combining intrusion detection datasets using MapReduce. SMC 2016: 4724-4728 - 2015
- [c4]Imen Gaied, Farah Jemili, Ouajdi Korbaa:
Intrusion detection based on Neuro-Fuzzy classification. AICCSA 2015: 1-8
2000 – 2009
- 2009
- [c3]Farah Jemili, Montaceur Zaghdoud, Mohamed Ben Ahmed:
Intrusion detection based on "Hybrid" propagation in Bayesian Networks. ISI 2009: 137-142 - [i1]Farah Jemili, Montaceur Zaghdoud, Mohamed Ben Ahmed:
Hybrid Intrusion Detection and Prediction multiAgent System HIDPAS. CoRR abs/0909.4889 (2009) - 2007
- [c2]Farah Jemili, Montaceur Zaghdoud, Mohamed Ben Ahmed:
A Framework for an Adaptive Intrusion Detection System using Bayesian Network. ISI 2007: 66-70 - 2006
- [c1]Najla Arfaoui, Farah Jemili, Montaceur Zaghdoud, Mohamed Ben Ahmed:
Comparative Study between Bayesian Network and Possibilistic Network in Intrusion Detection. SECRYPT 2006: 24-31
Coauthor Index
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last updated on 2024-10-07 22:11 CEST by the dblp team
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