DRSIG: Domain and Range Specific Index Generation for encrypted Cloud data

One of the most fundamental services of cloud computing is Cloud storage service. Huge amount of sensitive data is stored in the cloud for easy remote access and to reduce the cost of storage. The confidential data is encrypt before uploading to the cloud server in order to maintain privacy and security. All conventional searchable symmetric encryption(SSE) schemes enable the users to search on the entire index file. In this paper, we propose the Domain and Range Specific Index Generation(DRSIG) scheme that minimizes the Index Generation time. This scheme adopts collection sort technique to split the index file into D Domains and R Ranges. The Domain is based on the length of the keyword; the Range splits within the domain based on the first letter of the keyword. A mathematical model is used to encrypt the indexed keyword that eliminates the information leakage. The time complexity of the index generation is O(NT × 3) where NT - Number of rows in index document and 3 is Number of columns in index document. Experiments have been conducted on real world dataset to validate proposed DRSIG scheme. It is observed that DRSIG scheme is efficient and provide more secure data than Ranked Searchable Symmetric Encryption(RSSE) Scheme

Energy Concerned Clustering Mechanism to Ensure Reliable Data Transmission in Wireless Sensor Network

In wireless sensor networks, data reception capability along with higher QoS can be achieved by adapting clustering mechanisms in the network. Hierarchical networks increase data aggregation efficiently. The hierarchical network includes optimal cluster creation and cluster head (CH) selection that yield higher QoS in the network. Hybrid particle swarm optimization with firefly algorithm (HPSOFA) is proposed for CH selection to obtain optimal clustering in the network. Transmission overhead is reduced by 9% when compared with the existing method by applying a modified dynamic source routing (DSR) algorithm. The proposed algorithm addresses the adaptive congestion window size adjustment method to avoid congestion occurrences in the network. Thus, the proposed HPSOFA method improves QoS and establishes reliable communication in the network