Comparative study of several operation modes of AES algorithm for encryption ECG biomedical signal

Biomedical signal processing provides a cross-disciplinary international forum through which research on signal and images measurement and analysis in clinical medicine as well as biological sciences is shared. Electrocardiography (ECG) signal is more frequently used for diagnosis of cardiovascular diseases. However, the ECG signals contain sensitive private health information as well as details that serve to individually distinguish patients. For this reason, the information must be encrypted prior to transmission across public media so as to prevent unauthorized access by adversaries. In this paper, the proposed the use of the Advanced Encryption Standard algorithm (AES), which is one of a symmetric key block cipher with lightweight properties for enhances confidentiality, integrity and authentication in ECG signal transmission. However, some of the challenges arising from the use of this algorithm are computational overhead and level of security, which occur when handling more complex.The AES algorithm has different operation modes using three different key sizes which can be utilized in encrypting the whole sample of ECG biomedical signal in electronic healthcare. The experiments in this research, exhibit comparative study of using five modes of operation in AES algorithm, which are coupled with three key sizes based on the execution time and security level for the encryption of ECG biomedical signals in electronic healthcare application. Thus, we reported that the CBC mode of the AES algorithm is suitable to be applied of security purpose

Encryption by Heart (EbH)-Using ECG for time-invariant symmetric key generation

Wearable devices are a part of Internet-of-Things (IoT) that may offer valuable data of their porting user. This paper explores the use of ElectroCardioGram (ECG) records to encrypt user data. Previous attempts have shown that ECG can be taken as a basis for key generation. However, these approaches do not consider time-invariant keys. This feature enables using these so-created keys for symmetrically encrypting data (e.g. smartphone pictures), enabling their decryption using the key derived from the current ECG readings. This paper addresses this challenge by proposing EbH, a mechanism for persistent key generation based on ECG. EbH produces seeds from which encryption keys are generated. Experimental results over 24 h for 199 users show that EbH, under certain settings, can produce permanent seeds (thus time-invariant keys) computed on-the-fly and different for each user up to 95.97% of users produce unique keys. In addition, EbH can be tuned to produce seeds of different length (up to 300 bits) and with variable min-entropy (up to 93.51). All this supports the workability of EbH in a real setting. (C) 2017 Elsevier B.V. All rights reserved.Funding: This work was supported by the MINECO grants TIN2013-46469-R (SPINY: Security and Privacy in the Internet of You) and TIN2016-79095-C2-2-R (SMOG-DEV); by the CAM grant S2013/ICE-3095 (CIBERDINE: Cybersecurity, Data, and Risks), which is co-funded by European Funds (FEDER); and by the Programa de Ayudas para la Movilidad of Carlos III University of Madrid, Spain (J. M. de Fuentes and L. Gonzalez-Manzano grants). Data used for this research was provided by the Telemetric and ECG Warehouse (THEW) of University of Rochester, NY

Personalized information encryption using ECG signals with chaotic functions

The development of efficient data encryption to ensure high security of information transmission has long been a popular research subject. Because electrocardiogram (ECG) signals vary from person to person, and can be used as a new tool for biometric recognition. This study introduces an individual feature of ECG with chaotic Henon and logistic maps for personalized cryptography. This study also develops an encryption algorithm based on the chaos theory to generate initial keys for chaotic logistic and Henon maps. The proposed personalized encryption system uses a convenient handheld device to collect ECG signals from the user. High quality randomness in ECG signals results in a widely expanded key space, making it an ideal key generator for personalized data encryption. The experiments reported in this study demonstrate the use of this approach in encrypting texts and images, and applied of the proposed approach to secure communications. (C) 2012 Elsevier Inc. All rights reserved

Identification de personnes par fusion de différentes modalités biométriques

This thesis contributes to the resolution of the problems which are related to the analysis of the biometric data outcome from the iris, the fingerprint and the fusion of these two modalities, for person identification. Thus, after the evaluation of those proposed biometric systems, we have shown that the multimodal biometric system based on iris and fingerprint outperforms both monomodal biometric systems based whatsoever on the iris or on the fingerprint.Cette thèse contribue essentiellement à la résolution des problèmes liés à l'analyse des données biométriques issues de l'iris, de l'empreinte digitale et de la fusion de ces deux modalités pour l'identification de personne. Ainsi, après l'évaluation des trois systèmes biométriques proposés, nous avons prouvé que le système biométrique multimodal basé sur l'iris et l'empreinte digitale est plus performant que les deux systèmes biométriques monomodaux basés que se soit sur l'iris ou sur l'empreinte digitale