Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                

Hashem et al., 2015 - Google Patents

Towards insider threat detection using psychophysiological signals

Hashem et al., 2015

View PDF
Document ID
12038610688924680359
Author
Hashem Y
Takabi H
GhasemiGol M
Dantu R
Publication year
Publication venue
Proceedings of the 7th ACM CCS international workshop on managing insider security threats

External Links

Snippet

Insider threat is one of the greatest concerns for the information security system that could cause greater financial losses and damages than any other attacks. Recently many studies have been proposed to monitor and detect the insider attacks. However, implementing an …
Continue reading at isyou.info (PDF) (other versions)
  • 238000001514 detection method 0 title abstract description 17

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/32—Medical data management, e.g. systems or protocols for archival or communication of medical images, computerised patient records or computerised general medical references
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/60—Protecting data
    • G06F21/62—Protecting access to data via a platform, e.g. using keys or access control rules
    • G06F21/6218—Protecting access to data via a platform, e.g. using keys or access control rules to a system of files or objects, e.g. local or distributed file system or database
    • G06F21/6245—Protecting personal data, e.g. for financial or medical purposes
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/04—Detecting, measuring or recording bioelectric signals of the body of parts thereof
    • A61B5/0402—Electrocardiography, i.e. ECG
    • A61B5/0452—Detecting specific parameters of the electrocardiograph cycle
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/04—Detecting, measuring or recording bioelectric signals of the body of parts thereof
    • A61B5/0476—Electroencephalography
    • A61B5/0484—Electroencephalography using evoked response
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/16—Devices for psychotechnics; Testing reaction times; Devices for evaluating the psychological state
    • A61B5/164—Lie detection
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/04—Detecting, measuring or recording bioelectric signals of the body of parts thereof
    • A61B5/0488—Electromyography

Similar Documents

Publication Publication Date Title
Hashem et al. Towards insider threat detection using psychophysiological signals
US7689272B2 (en) Method for brain fingerprinting, measurement, assessment and analysis of brain function
McManus et al. Changes in motor unit behavior following isometric fatigue of the first dorsal interosseous muscle
Farwell et al. Brain fingerprinting field studies comparing P300-MERMER and P300 brainwave responses in the detection of concealed information
Winograd et al. Mock crime application of the Complex Trial Protocol (CTP) P300‐based concealed information test
Almehmadi et al. On the possibility of insider threat prevention using intent-based access control (IBAC)
Hu et al. Driver fatigue detection from electroencephalogram spectrum after electrooculography artefact removal
Tamburro et al. A new ICA-based fingerprint method for the automatic removal of physiological artifacts from EEG recordings
US20140228701A1 (en) Brain-Computer Interface Anonymizer
Matsuda et al. Event‐related potentials increase the discrimination performance of the autonomic‐based concealed information test
Gao et al. A novel concealed information test method based on independent component analysis and support vector machine
Ghaderyan et al. Time-varying singular value decomposition analysis of electrodermal activity: A novel method of cognitive load estimation
Farwell et al. Brain fingerprinting classification concealed information test detects US Navy military medical information with P300
Vallejo et al. Neuromuscular disease detection by neural networks and fuzzy entropy on time‐frequency analysis of electromyography signals
Lopes-dos-Santos et al. Extracting information in spike time patterns with wavelets and information theory
Rajaguru et al. KNN classifier and K-means clustering for robust classification of epilepsy from EEG signals. A detailed analysis
Lian et al. Pair-wise matching of EEG signals for epileptic identification via convolutional neural network
Liang et al. Identity recognition using biological electroencephalogram sensors
Asharindavida et al. A forecasting tool for prediction of epileptic seizures using a machine learning approach
Yeng et al. Healthcare staffs' information security practices towards mitigating data breaches: a literature survey
Yap et al. Person authentication based on eye-closed and visual stimulation using EEG signals
Krishnamani et al. Variational mode decomposition based differentiation of fatigue conditions in muscles using surface electromyography signals
Sun et al. Validation of SOBI‐DANS method for automatic identification of horizontal and vertical eye movement components from EEG
Valecha et al. Investigating phishing susceptibility—An analysis of neural measures
Hashem et al. A multi-modal neuro-physiological study of malicious insider threats