We propose a framework for quantitative security analysis of machine learning methods. Key issus of this framework are a formal specification of the deployed learning model and a...
Pattern matching and analysis over network data streams is increasingly becoming an essential primitive of network monitoring systems. It is a fundamental part of most intrusion d...
This study investigates how customers perceive and adopt Internet Banking (IB) in Hong Kong. We developed a theoretical model based on the Technology Acceptance Model (TAM) with a...
T. C. Edwin Cheng, David Y. C. Lam, Andy C. L. Yeu...
Anomaly detection for network intrusion detection is usually considered an unsupervised task. Prominent techniques, such as one-class support vector machines, learn a hypersphere ...
We present the design and implementation of a compiler that, given high-level multiparty session descriptions, generates custom cryptographic protocols. Our sessions specify pre-a...