The demand of cloud computing and 5G networks has increased in the current scenario due to their attractive features and also the security related to the data over the cloud. In the context of cloud security, there is a number of computationally hard methods available. One of the most popular methods used to secure data over the cloud is the identity-based encryption (IBE). It is an access policy that allows only authorized users to access legible data in order to avoid a malicious attack. IBE comprises of four stages, namely, setup, key generation or extract, encryption, and decryption. Key generation is one of the important and time-consuming phases in which a security key is generated. It is a computational and decisional hard problem for generating unbreakable and nonderivable secure keys. This paper proposes an enhanced identity-based encryption approach where a secure key is generated using part of an identity bit string in order to avoid leakage of users’ identity even if an adversary or attacker decodes the key or encrypted data. Experiment results show that the prosed algorithm takes less time in the encryption and decryption as compared to the competitive approach named efficient selective-ID secure identity-based encryption approach. One of the most important features of the proposed approach is that it hides the user’s identity by using the Lagrange coefficient, which consists of a polynomial interpolation function. The security of the system depends on the hardness of computing the bilinear Diffie-Hellman problem.
This article presents a comparative study of empirical power curve models to estimate the output power of the turbine as a function of the wind speed. In these models, modelling strategy relies on the objective of modelling, data being used for the modelling and targeted accuracy. It has been observed that models based on presumed shape of power curve lack desired accuracy since these are developed using the power ratings of wind turbine which are not sufficient to exactly replicate the turbine's actual behaviour. The performance of various models which comes under manufacturer power curve modelling methodology has been compared with reference to commercially available wind turbines. It has been found that power curves obtained through method of least squares and cubic spline interpolation methods exactly match with manufacturer power curve, whereas 5PL method gives sufficiently accurate results. Modelling based on actual data of wind farm has been found to be a powerful technique for developing site-specific power curves.
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