共 50 条
- [1] Performance Evaluation of A Neural Network Based Intrusion Detection System for Tor Networks Considering Different Hidden Units PROCEEDINGS 2015 18TH INTERNATIONAL CONFERENCE ON NETWORK-BASED INFORMATION SYSTEMS (NBIS 2015), 2015, : 620 - 627
- [2] A Neural Network Based User Identification for Tor Networks: Data Analysis Using Friedman Test IEEE 30TH INTERNATIONAL CONFERENCE ON ADVANCED INFORMATION NETWORKING AND APPLICATIONS WORKSHOPS (WAINA 2016), 2016, : 7 - 13
- [3] A Neural Network Based User Identification for Tor Networks: Comparison Analysis of Different Activation Functions Using Friedman Test PROCEEDINGS OF 2016 19TH INTERNATIONAL CONFERENCE ON NETWORK-BASED INFORMATION SYSTEMS (NBIS), 2016, : 480 - 487
- [4] A Neural Network Based User Identification for Tor Networks: Comparison Analysis of Activation Function Using Friedman Test PROCEEDINGS OF 2016 10TH INTERNATIONAL CONFERENCE ON COMPLEX, INTELLIGENT, AND SOFTWARE INTENSIVE SYSTEMS (CISIS), 2016, : 477 - 483
- [5] Application of Neural Networks and Friedman Test for User Identification in Tor Networks 2015 10TH INTERNATIONAL CONFERENCE ON BROADBAND AND WIRELESS COMPUTING, COMMUNICATION AND APPLICATIONS (BWCCA 2015), 2015, : 448 - 454
- [6] Network Intrusion Detection System Using Neural Networks ICNC 2008: FOURTH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, VOL 5, PROCEEDINGS, 2008, : 242 - 246
- [7] Intrusion Detection System based on Network Traffic using Deep Neural Networks 2019 IEEE 24TH INTERNATIONAL WORKSHOP ON COMPUTER AIDED MODELING AND DESIGN OF COMMUNICATION LINKS AND NETWORKS (IEEE CAMAD), 2019,
- [8] Correlation between Deep Neural Network Hidden Layer and Intrusion Detection Performance in IoT Intrusion Detection System SYMMETRY-BASEL, 2022, 14 (10):
- [9] Increasing Performance Of Intrusion Detection System Using Neural Network 2014 INTERNATIONAL CONFERENCE ON ADVANCED COMMUNICATION CONTROL AND COMPUTING TECHNOLOGIES (ICACCCT), 2014, : 546 - 550
- [10] An Intrusion Detection System Using a Deep Neural Network With Gated Recurrent Units IEEE ACCESS, 2018, 6 : 48697 - 48707