Anomaly Detection in Encrypted Internet Traffic Using Hybrid Deep Learning
An increasing number of Internet application services are relying on encrypted traffic to offer adequate consumer privacy. Anomaly detection in encrypted traffic to circumvent and mitigate cyber security threats is, however, an open and ongoing research challenge due to the limitation of existing tr...
Main Authors: | Taimur Bakhshi, Bogdan Ghita |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi-Wiley
2021-01-01
|
Series: | Security and Communication Networks |
Online Access: | http://dx.doi.org/10.1155/2021/5363750 |
Similar Items
-
On Internet Traffic Classification: A Two-Phased Machine Learning Approach
by: Taimur Bakhshi, et al.
Published: (2016-01-01) -
Anomaly Detection in Encrypted WLAN Traffic
by: Svensson, Carolin
Published: (2020) -
Network Traffic Anomaly Detection via Deep Learning
by: Konstantina Fotiadou, et al.
Published: (2021-05-01) -
Encrypted Traffic Analysis on Smart Speakers with Deep Learning
by: Kennedy, Sean M.
Published: (2019) -
Contributions on detection and classification of internet traffic anomalies
by: Farraposo, Silvia
Published: (2009)