HIGHLIGHTS
- who: Reconnaissance et al. from the Science Department, COMSATS University Islamabad, Islamabad, Pakistan, Technical University of Denmark, Lyngby, Denmark have published the paper: Hybrid Deep Learning: An Efficient Reconnaissance and Surveillance Detection Mechanism in SDN, in the Journal: (JOURNAL)
- what: The analysis shows that this approach outperforms in terms of detection accuracy with a trivial trade-off speed efficiency.
- future: Section V concludes the work and defines future directions and recommendations. As part of the future work the authors plan to implement various other deep learning models to efficiently and timely detect evolving . . .
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