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2018-04-02
Mamun, A. Al, Salah, K., Al-maadeed, S., Sheltami, T. R..  2017.  BigCrypt for Big Data Encryption. 2017 Fourth International Conference on Software Defined Systems (SDS). :93–99.

as data size is growing up, cloud storage is becoming more familiar to store a significant amount of private information. Government and private organizations require transferring plenty of business files from one end to another. However, we will lose privacy if we exchange information without data encryption and communication mechanism security. To protect data from hacking, we can use Asymmetric encryption technique, but it has a key exchange problem. Although Asymmetric key encryption deals with the limitations of Symmetric key encryption it can only encrypt limited size of data which is not feasible for a large amount of data files. In this paper, we propose a probabilistic approach to Pretty Good Privacy technique for encrypting large-size data, named as ``BigCrypt'' where both Symmetric and Asymmetric key encryption are used. Our goal is to achieve zero tolerance security on a significant amount of data encryption. We have experimentally evaluated our technique under three different platforms.

2017-02-27
Gonzalez-Longatt, F., Carmona-Delgado, C., Riquelme, J., Burgos, M., Rueda, J. L..  2015.  Risk-based DC security assessment for future DC-independent system operator. 2015 International Conference on Energy Economics and Environment (ICEEE). :1–8.

The use of multi-terminal HVDC to integrate wind power coming from the North Sea opens de door for a new transmission system model, the DC-Independent System Operator (DC-ISO). DC-ISO will face highly stressed and varying conditions that requires new risk assessment tools to ensure security of supply. This paper proposes a novel risk-based static security assessment methodology named risk-based DC security assessment (RB-DCSA). It combines a probabilistic approach to include uncertainties and a fuzzy inference system to quantify the systemic and individual component risk associated with operational scenarios considering uncertainties. The proposed methodology is illustrated using a multi-terminal HVDC system where the variability of wind speed at the offshore wind is included.