HERMES: An Automatic Tool for Verification of Secrecy in Security Protocols

Approaches for securing digital assets of information systems can be classified as active approaches based on attack models, and passive approaches based on system-models. Passive approaches are inherently superior to active ones. However, taking full advantage of passive approaches calls for a rigorous standard for a low-complexity-high-integrity execution environment for security protocols. We sketch broad outlines of mirror network (MN) modules, as a candidate for such a standard. Their utility in assuring real-world information systems is illustrated with examples.

Download Full-text

Squeak and rattle noise classification using radial basis function neural networks

Noise Control Engineering Journal ◽

10.3397/1/376824 ◽

2020 ◽

Vol 68 (4) ◽

pp. 283-293

Author(s):

Oleksandr Pogorilyi ◽

Mohammad Fard ◽

John Davy ◽

Mechanical and Automotive Engineering, School ◽

...

Keyword(s):

Neural Network ◽

Neural Networks ◽

High Accuracy ◽

Training Method ◽

Vehicle Interior ◽

Trained Classifier ◽

Different Types ◽

Noise Classification ◽

Automatic Tool ◽

Multi Class Classification

In this article, an artificial neural network is proposed to classify short audio sequences of squeak and rattle (S&R) noises. The aim of the classification is to see how accurately the trained classifier can recognize different types of S&R sounds. Having a high accuracy model that can recognize audible S&R noises could help to build an automatic tool able to identify unpleasant vehicle interior sounds in a matter of seconds from a short audio recording of the sounds. In this article, the training method of the classifier is proposed, and the results show that the trained model can identify various classes of S&R noises: simple (binary clas- sification) and complex ones (multi class classification).

Download Full-text