Brain computer interface for smart hardware device

Nagarajan, G.; Minu, R. I.; Jayanthiladevi, A.

doi:10.3233/rft-180167

Cited by 31 publications

(4 citation statements)

References 6 publications

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“…Consider two messages pt1 and pt2 in the message space, their corresponding ciphertexts are ct1, ct2. The partially homomorphic encryption [20] which has multiplicative property can be proved as follows.…”

Section: Homomorphic Property Of Sphementioning

confidence: 99%

RETRACTED ARTICLE: Securing medical data by role-based user policy with partially homomorphic encryption in AWS cloud

Boomija

Raja

2022

Soft Comput

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Cloud technology provides services for storing and accessing a large amount of data with ease of access and less cost. Sensitive data like patients' electronic health information should be encrypted before outsourcing into the cloud. Many traditional encryption methods are used for protecting data in the cloud, but unable to perform computation on encrypted data. Homomorphic encryption operates directly on the ciphertext. In this study, a Secure Partially Homomorphic Encryption (SPHE) algorithm is proposed to secure the outsourced data and perform multiplication and division operations on the ciphertext. The access control policy in the cloud environment is more exible. An attacker can easily collect sensitive data by abusing the access policy of another user. So the database privacy is compromised. Creating a role hierarchy and managing the session is di cult in the cloud environment. The above issues motivate us to develop a model which is the integration of the proposed scheme SPHE with role-based user policy.The model is implemented in Eclipse IDE and AWS Toolkit for Eclipse and deployed in Amazon Elastic Beanstalk (EB) environment. This model is particularly used for securing the patient e-health details and performing computation on outsourced data. The patient details are encrypted by the algorithm SPHE and uploaded in AWS (Amazon Web Service) S3 bucket. The users are created by AWS Identity and Access Management (IAM) service and the access level policy is de ned based on user roles in EB environment. The proposed model performance is studied by comparing with other partially homomorphic methods Elgamal, Pailler, and Benaloh. This model achieves data integrity and data con dentiality using the role-based user policy with SPHE.

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Section: Homomorphic Property Of Sphementioning

confidence: 99%

RETRACTED ARTICLE: Securing medical data by role-based user policy with partially homomorphic encryption in AWS cloud

Boomija

Raja

2022

Soft Comput

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“…The approach uses a homomorphic encryption method to ensure patient privacy. Nagarajan et al (2019) discussed the connectivity issues in smart hardware devices. Carpov et al (2016) implemented a practical medical diagnosis model, which is privacy‐preserving using a homomorphic scheme.…”

Section: Related Workmentioning

confidence: 99%

Threshold multiparty multi‐randomness secure partially homomorphic encryption for data security in cloud

Boomija

Raja

2022

Expert Systems

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Threshold cryptography is used to secure a cryptographic secret by dividing it into N shares and storing each claim on a diverse server. Any subgroup of t servers can use the secret without re‐making it. However, an adversary cannot recover the secret by compromising t − 1 servers. Homomorphic encryption operates directly on the ciphertext. In this study, a Threshold multiparty multi‐randomness secure partially homomorphic encryption (TM‐MR‐SPHE) algorithm is proposed to secure the outsourced data and perform multiplication and division operations on the ciphertext. The model is implemented in Eclipse IDE and AWS Toolkit for Eclipse and deployed in Amazon Elastic Beanstalk (EB) environment. This model is mainly used to secure the patient e‐health details and perform computation on outsourced data. The patient details are encrypted by the algorithm MR‐SPHE and uploaded in AWS (Amazon Web Service) S3 bucket. AWS identity and access management (IAM) creates the users' service and secret shares among multiple users in the EB environment. The proposed model performance is studied by comparing with other partially homomorphic Elgamal, Pailler, and Benaloh. This model achieves data integrity and confidentiality using the threshold multiparty with multi‐randomness secure partially homomorphic encryption.

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“…An height-clearance riddle can be utilized to cause a pic to seem more honed. The above-mentioned method accentuates adequate [24] subtleties in the image-something contrary to the low-transmit sieve. High-pass separating works similarly as low-transmit sieving.…”

Section: High Transmit Sievesmentioning

confidence: 99%