Visible to the public Biblio

Filters: Keyword is data size  [Clear All Filters]
Bouchaala, Mariem, Ghazel, Cherif, Saidane, Leila Azouz.  2019.  Revocable Sliced CipherText Policy Attribute Based Encryption Scheme in Cloud Computing. 2019 15th International Wireless Communications Mobile Computing Conference (IWCMC). :1860—1865.

Cloud Computing is the most promising paradigm in recent times. It offers a cost-efficient service to individual and industries. However, outsourcing sensitive data to entrusted Cloud servers presents a brake to Cloud migration. Consequently, improving the security of data access is the most critical task. As an efficient cryptographic technique, Ciphertext Policy Attribute Based Encryption(CP-ABE) develops and implements fine-grained, flexible and scalable access control model. However, existing CP-ABE based approaches suffer from some limitations namely revocation, data owner overhead and computational cost. In this paper, we propose a sliced revocable solution resolving the aforementioned issues abbreviated RS-CPABE. We applied splitting algorithm. We execute symmetric encryption with Advanced Encryption Standard (AES)in large data size and asymmetric encryption with CP-ABE in constant key length. We re-encrypt in case of revocation one single slice. To prove the proposed model, we expose security and performance evaluation.

Yue, L., Junqin, H., Shengzhi, Q., Ruijin, W..  2017.  Big Data Model of Security Sharing Based on Blockchain. 2017 3rd International Conference on Big Data Computing and Communications (BIGCOM). :117–121.

The rise of big data age in the Internet has led to the explosive growth of data size. However, trust issue has become the biggest problem of big data, leading to the difficulty in data safe circulation and industry development. The blockchain technology provides a new solution to this problem by combining non-tampering, traceable features with smart contracts that automatically execute default instructions. In this paper, we present a credible big data sharing model based on blockchain technology and smart contract to ensure the safe circulation of data resources.

Huang, J., Hou, D., Schuckers, S., Hou, Z..  2015.  Effect of data size on performance of free-text keystroke authentication. IEEE International Conference on Identity, Security and Behavior Analysis (ISBA 2015). :1–7.

Free-text keystroke authentication has been demonstrated to be a promising behavioral biometric. But unlike physiological traits such as fingerprints, in free-text keystroke authentication, there is no natural way to identify what makes a sample. It remains an open problem as to how much keystroke data are necessary for achieving acceptable authentication performance. Using public datasets and two existing algorithms, we conduct two experiments to investigate the effect of the reference profile size and test sample size on False Alarm Rate (FAR) and Imposter Pass Rate (IPR). We find that (1) larger reference profiles will drive down both IPR and FAR values, provided that the test samples are large enough, and (2) larger test samples have no obvious effect on IPR, regardless of the reference profile size. We discuss the practical implication of our findings.