The paper presents intrusion detection system which informs system administrator about potential intrusion incidence in a system. The designed architecture employes statistical method of data evaluation, that allows detection based on the knowledge of user activity deviation in the computer system from learned profile representing standard user behavior.
This paper deals with the issue of the brain-computer interface (BCI)-the human-machine interface (HMI) based on acquisition, analysis and transformation of signals generated by the central nervous system (CNS) as the manifestation of its normal function. Brain-computer interface can be seen as the bridge that is building up direct one-way or two-way communication pathway between the brain and the external technical device. Paper introduces techniques based on non-invasive functional imaging of the brain used for data acquisition in non-invasive brain computer interfaces, and is focused on the technique that is reading neural activity of the brain with use of multi-channel electroencephalograph (EEG). As the part of this paper we are introducing our experience with the low-cost commercially available equipment Emotiv EPOC Neuroheadset based on this technology.
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