A two-stage traitor tracing scheme for hierarchical fingerprints

Chaabane, Faten; Charfeddine, Maha; Puech, William; Amar, Chokri Ben

doi:10.1007/s11042-016-3749-8

Cited by 8 publications

(2 citation statements)

References 40 publications

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“…Stock market [18] Energy industry [19] Insurance [20] Healthcare [4,21,22] P2P multimedia content distribution platforms [23,24] In this section, we have presented a description of the blockchain. Treating an application related to the health field, we will make a state of the art on the work of blockchain applied to e-health.…”

Section: (Vi) Layer To Services (L2s)mentioning

confidence: 99%

Healthcare and Fitness Data Management Using the IoT-Based Blockchain Platform

Frikha

Chaari

Chaabane

et al. 2021

Journal of Healthcare Engineering

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Because of the availability of more than an actor and a wireless component among e-health applications, providing more security and safety is expected. Moreover, ensuring data confidentiality within different services becomes a key requirement. In this paper, we propose to collect data from health and fitness smart devices deployed in connection with the proposed IoT blockchain platform. The use of these devices helps us in extracting an amount of highly valuable heath data that are filtered, analyzed, and stored in electronic health records (EHRs). Different actors of the platform, coaches, patients, and doctors, collaborate to provide an on-time diagnosis and treatment for various diseases in an easy and cost-effective way. Our main purpose is to provide a distributed, secure, and authorized access to these sensitive data using the Ethereum blockchain technology. We have designed an integrated low-powered IoT blockchain platform for a healthcare application to store and review EHRs. This architecture, based on the blockchain Ethereum, includes a web and mobile application allowing the patient as well as the medical and paramedical staff to have a secure access to health information. The Ethereum node is implemented on an embedded platform, which should provide an efficient, flexible, and secure system despite the limited resources and low power consumption of the multiprocessor platform.

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Section: (Vi) Layer To Services (L2s)mentioning

confidence: 99%

Healthcare and Fitness Data Management Using the IoT-Based Blockchain Platform

Frikha

Chaari

Chaabane

et al. 2021

Journal of Healthcare Engineering

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“…The proposed idea takes the benefit of operating in hierarchical context to deliver a more succinct and exact accusation decision in a short time. In a second developed tracing scheme detailed in [37], we proposed a confident fingerprinting approach based on a twostage tracing strategy combining the Boneh Shaw with replication scheme and the Tardos codes. This scheme is applied to a multilevel hierarchical fingerprint hidden by using a DCT-based audio watermarking algorithm [38].…”

Section: ) Traceabilitymentioning

confidence: 99%

Audio Watermarking for Security and Non-Security Applications

et al. 2022

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The digitization of audiovisual data is significantly increasing. Thus, in order to guarantee principally the protection of intellectual properties of this digital content, watermarking has appeared as a solution. The watermarking can be used in reality in several types of applications that target two different contexts; the first for security applications and the second for non-security ones. In this paper, we carry a big interest in studying these two types of applications. Moreover, we propose a first digital watermarking scheme for security copyright protection application where we have involved Neural Network architecture in the insertion and detection processes and we have integrated some masking phenomena of the Human Psychoacoustic Model with Linear Predictive Coding spectral envelope estimation of the audio file. Experimentations proved the efficiency of exploiting perceptual masking with spectral envelope consideration in terms of imperceptibility and robustness results. Besides, we suggest a second audio watermarking technique for non-security content characterization application based on deep learning classification architecture. In this scheme, extracted watermark will advise about the audio class: music or speech, the speaker gender and emotion. Reported results indicated that the suggested scheme achieved higher performance at classification level as well as at watermarking properties.

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