Data Security Model Employing Hyperelliptic Curve Cryptography (HECC) and Secure Hash Algorithm-3 (Sha-3) in Cloud Computing

Data owners use the huge space offered by ‘Cloud’ Computing for storage of data and also for carrying out computations. To eliminate the burden of storing file locally, cloud stores them on remote servers using virtualization concepts. Therein arises one of the major issues in the field of cloud computing: security. Data owners lack in having direct control over files stored in the cloud and consequently, the problem of data security arises. An efficient scheme to provide data security, while storing data in the cloud has been proposed which makes use of Hyperelliptic curve cryptography (HECC) for encryption and decryption and Secure Hash Algorithm-3 (SHA-3) for data integrity verification. Implementation results clearly illustrate that HECC remains as a good alternative asymmetric key technique rather than ECC and RSA when securing documents in cloud

User Verifiable Multiple Keyword Search Scheme using the Merkle Tree for Outsourced Data in the Cloud

Cloud computing has revolutionized the IT industry by offering huge storage for data outsourcing and also for computation. Various security issues concerned with security and privacy of data arise in the context of data outsourcing. The framework enables clients to outsource encrypted data to the cloud, enables users to retrieve preferred documents using multiple keywords and allows the user to verify the response from the server. The strength of the proposed model relies on the discrete logarithmic problem of Hyper Elliptic Curve Cryptography (HECC) and the security of Merkle trees. The paper proposes a user verifiable multi-keyword search scheme, which focuses on: (i) construction of inverted index for the documents with keywords; (ii) index and document encryption by HECC; (iii) index and document authentication by the Merkle tree; and (iv) verification of the accuracy of response from server by top hash or root hash value of the Merkle tree. Security analysis and results demonstrate the correctness of proposed multiple keyword search (MKS) scheme. The search algorithm combined with the hash value verification process by the Merkle tree is strong enough to provide data security, privacy, and integrity. The proposed model reduces the storage overhead on both the client’s and user’s side. As the number of documents increases, the retrieval time is less, which reduces the storage overhead on both sides

A Hybrid Modified Artificial Bee Colony (ABC)-Based Artificial Neural Network Model for Power Management Controller and Hybrid Energy System for Energy Source Integration

Small MGS (microgrid systems) are capable of decreasing energy losses. Long-distance power transmission lines are constructed by integrating distributed power sources with energy storage subsystems, which is the current trend in the development of RES (renewable energy sources). Although energies produced by RES do not cause pollution, they are stochastic and hence challenging to manage. This disadvantage makes high penetration of RES risky for the stability, dependability, and power quality of main electrical grids. The energies obtained from RES must thus be integrated in the best possible way. To provide maximum energy sustainability and best energy usage, hybrid energy systems must manage energy efficiently. In order to improve power management and make better use of RES, this study offers a hybrid energy power management controller based on hybrid MABC (modified artificial bee colony) and ANN (artificial neural network) for MGS, PVS (photovoltaic system), and WT (wind turbine). Controlling power flows between grids and energy sources is the suggested approach for power control. D/R (demands/responses), customer reactions, offering priorities, D/R properties like COE (cost of energies), and sizes (lengths) are considered in this work. Along with current techniques, a suggested model is implemented in the MATLAB/Simulink platform

Biosorption of reactive red 2 using positively charged Metapenaeus monoceros shells

AbstractMetapenaeus monoceros shell used for the removal of reactive red 2 from an aqueous solution was studied by batch biosorption system. The maximum dye uptake capacity was examined at biosorbent dosage, different pH, contact time and initial dye concentration. From the study the maximum dye uptake capacity was obtained as 166mg/g at an optimal condition of 0.1g/L of biosorbent dosage, pH value of 2 and initial dye concentration of 100mg/L. When compared to the Langmuir isotherm model, the equilibrium data were fitted well with the Freundlich isotherm model. The kinetic data were fitted well with the pseudo second order rate equation when compared to the pseudo first order rate equation. The biosorbent characteristics were observed by SEM and FTIR analyses