scholarly journals Anomaly Detection for Application Layer User Browsing Behavior Based on Attributes and Features

2018 ◽  
Vol 1069 ◽  
pp. 012072 ◽  
Author(s):  
Xiong Luo ◽  
Xiaoqiang Di ◽  
Xu Liu ◽  
Hui Qi ◽  
Jinqing Li ◽  
...  
Keyword(s):  
Anomaly Detection ◽  
Application Layer ◽  
Behavior Based ◽  
Browsing Behavior

AutoGuard: A Dual Intelligence Proactive Anomaly Detection at Application-Layer in 5G Networks

2021 ◽  
pp. 715-735
Author(s):  
Taous Madi ◽  
Hyame Assem Alameddine ◽  
Makan Pourzandi ◽  
Amine Boukhtouta ◽  
Moataz Shoukry ◽  
...  
Keyword(s):  
Anomaly Detection ◽  
Application Layer ◽  
5G Networks

Detecting zero-day attacks using context-aware anomaly detection at the application-layer

2016 ◽  
Vol 16 (5) ◽  
pp. 475-490 ◽  
Author(s):  
Patrick Duessel ◽  
Christian Gehl ◽  
Ulrich Flegel ◽  
Sven Dietrich ◽  
Michael Meier
Keyword(s):  
Anomaly Detection ◽  
Context Aware ◽  
Application Layer

Research on Software Trusted Dynamic Measurement

2012 ◽  
Vol 268-270 ◽  
pp. 1869-1872
Author(s):  
Rui Hao ◽  
Xin Guang Peng ◽  
Lei Xiu
Keyword(s):  
Trusted Computing ◽  
Dynamic Measurement ◽  
System Call ◽  
Application Layer ◽  
Software Application ◽  
Trust Chain ◽  
Behavior Based ◽  
System Resources

For the problem of trust chain of Trusted Computing Group (TCG), which only measures static integrity to the system resources, we extend the TCG chain to the software application layer and propose to extract return addresses of functions in call stacks dynamically for obtaining system call short sequences as software behavior and By monitoring softare behavior based on SVM,we realize software trusted dynamic measurement.

scholarly journals SuperB: Superior Behavior-based Anomaly Detection Defining Authorized Users’ Traffic Patterns

2020 ◽  
Author(s):  
Daniel Y. Karasek ◽  
Jeehyeong Kim ◽  
Victor Youdom Kemmoe ◽  
Md Zakirul Alam Bhuiyan ◽  
Sunghyun Cho ◽  
...  
Keyword(s):  
Anomaly Detection ◽  
Traffic Patterns ◽  
Behavior Based
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