Role-Based Access Control Models
Computer
Digital Signal Processing: A Practical Approach
Digital Signal Processing: A Practical Approach
Journal of Medical Systems
A Decision Support System for Telemedicine Through the Mobile Telecommunications Platform
Journal of Medical Systems
A Cryptographic Key Management Solution for HIPAA Privacy/Security Regulations
IEEE Transactions on Information Technology in Biomedicine
A primer on cryptography in communications
IEEE Communications Magazine
Journal of Network and Computer Applications
Compressed ECG Biometric: A Fast, Secured and Efficient Method for Identification of CVD Patient
Journal of Medical Systems
Cardioids-based faster authentication and diagnosis of remote cardiovascular patients
Security and Communication Networks
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With cardiovascular disease as the number one killer of modern era, Electrocardiogram (ECG) is collected, stored and transmitted in greater frequency than ever before. However, in reality, ECG is rarely transmitted and stored in a secured manner. Recent research shows that eavesdropper can reveal the identity and cardiovascular condition from an intercepted ECG. Therefore, ECG data must be anonymized before transmission over the network and also stored as such in medical repositories. To achieve this, first of all, this paper presents a new ECG feature detection mechanism, which was compared against existing cross correlation (CC) based template matching algorithms. Two types of CC methods were used for comparison. Compared to the CC based approaches, which had 40% and 53% misclassification rates, the proposed detection algorithm did not perform any single misclassification. Secondly, a new ECG obfuscation method was designed and implemented on 15 subjects using added noises corresponding to each of the ECG features. This obfuscated ECG can be freely distributed over the internet without the necessity of encryption, since the original features needed to identify personal information of the patient remain concealed. Only authorized personnel possessing a secret key will be able to reconstruct the original ECG from the obfuscated ECG. Distribution of the key is extremely efficient and fast due to small size (only 0.04---0.09% of the original ECG file). Moreover, if the obfuscated ECG reaches to the wrong hand (hacker), it would appear as regular ECG without encryption. Therefore, traditional decryption techniques including powerful brute force attack are useless against this obfuscation.