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Security and Privacy Issues in Fog Computing
Published in Ravi Tomar, Avita Katal, Susheela Dahiya, Niharika Singh, Tanupriya Choudhury, Fog Computing, 2023
Smriti Gaba, Susheela Dahiya, Keshav Kaushik
To preserve privacy of data, strong authentication algorithms must be used so that data is transmitted encrypted. The following techniques can be used: Homomorphic encryption allows computations on encrypted data without actually decrypting it (Lu et al., 2012), which along with providing security also reduces computations of the decryption mechanism so that resource-constrained devices can process services and operations efficiently.Differential privacy (Dwork, 2011) can be utilised to collect and transmit data while maintaining privacy.
Trusted Digital Solutions and Cybersecurity in Healthcare
Published in Rajarshi Gupta, Dwaipayan Biswas, Health Monitoring Systems, 2019
The need for privacy protection of health and organizational data collected and managed by healthcare service providers and consumers triggered research on the use of cryptographic techniques in the processing of these data. Homomorphic encryption is a form of encryption that allows computation on ciphertexts, generating an encrypted result which, when decrypted, matches the result of the operations as if they had been performed on the plaintext. The purpose of homomorphic encryption is to allow computation on encrypted data. Cloud computing platforms can perform difficult computations on homomorphically encrypted data without ever having access to the unencrypted data. Α list of potential applications for homomorphic encryption in healthcare includes applications in genomics, for example, when sharing genomics data to understand the clinical significance of genetic variants or when executing combined analysis of genotype and phenotype data in powerful cloud infrastructures [21].
Security and Privacy in Big Data Cyber-Physical Systems
Published in Yassine Maleh, Mohammad Shojafar, Ashraf Darwish, Abdelkrim Haqiq, Cybersecurity and Privacy in Cyber-Physical Systems, 2019
L. Josephine Usha, J. Jesu Vedha Nayahi
One of the techniques that supports both security and privacy is homomorphic encryption (Naehrig et al. 2011; Ogburn et al. 2013; Potey et al. 2016; Rahul et al. 2017). Homomorphic encryption allows the users to do basic computations on ciphertext, and generate an encrypted result as an output. When this encrypted result is decrypted, it will give similar results as applied to the plaintext. The main purpose of using homomorphic encryption is to perform computation on encrypted data without knowing the original data. It involves four functions, namely, key generation, encryption, evaluation and decryption. Homomorphic encryption is of two types, namely, partially homomorphic encryption and fully homomorphic encryption. Partially homomorphic encryption schemes including RSA, ElGamal and Paillier allows only a restricted number of addition and multiplication on encrypted data, which have only limited practical applications.
Privacy-Preserving with Zero Trust Computational Intelligent Hybrid Technique to English Education Model
Published in Applied Artificial Intelligence, 2023
This approach utilizes the concept of homomorphic encryption to ensure a robust level of privacy and adheres to the principles of zero trust architecture. This is achieved by incorporating a noise component into the original message. Homomorphic encryption is a cryptographic technique that allows computations to be performed on encrypted data without requiring decryption. By applying this method, sensitive information remains protected throughout the entire computation process, minimizing the risk of unauthorized access or data leakage. To bolster privacy, we introduce an additional layer of security by introducing noise to the original message. This noise is designed to obfuscate the underlying data and prevent any meaningful information from being discerned by unauthorized parties. By employing this technique, we ensure that even if an attacker gains access to the encrypted data, they will be unable to extract valuable insights or sensitive details without the necessary decryption keys.
PrivBCS: a privacy-preserving and efficient crowdsourcing system with fine-grained worker selection based on blockchain
Published in Connection Science, 2023
Juan Chen, Wei Liang, Lijun Xiao, Ce Yang, Ronglin Zhang, Zhenwen Gui, Aneta Poniszewska-Marańda
In this paper, we combine the worker's reputation value and the spatial distance between the worker and the crowdsourcing task to evaluate which of the two workers, and , is more suitable for the crowdsourcing task according to the following equation. denotes the distance between two entities. It is worth noting that all operations should be performed by ciphertext. The computational cost of full homomorphic encryption is extremely high, resulting in limited application scenarios in practice. Therefore, this paper will choose to use partial homomorphic encryption schemes (Paillier and El-Gamal), which are much more computationally efficient than FHE, but also have certain problems. Specifically, each scheme only supports partial homomorphism and cannot perform the above equation computation individually and completely. The solution to this problem will be shown in the next section.
A Comparative Review on Homomorphic Encryption for Cloud Security
Published in IETE Journal of Research, 2021
Ganesh Kumar Mahato, Swarnendu Kumar Chakraborty
An encryption technique which is used to perform operations on secured (encrypted) data without having to decrypt the information is Homomorphic Encryption (HE) [12]. Without the use of a secret key, it enables us to apply operations to the encrypted data. Mathematical operations of any complexity level can be carried out on encrypted data without compromising the security. The term “homo” is a Greek word meaning “same” and “morphic” means “structure”. When similar mathematical operations are carried out on encrypted data, the HE system retains the same result. After the decryption of the data, the output is the same and it seems that the operations have been performed on the unencrypted data. Algebraic operations are used to perform a variety of computations on encrypted data [13].