With the advent of e-commerce, it has become extremely essential to tackle the sensitive issues of affording data security, especially in the ever-blooming open network environment of the modern era. The encrypting technologies of the time-honored cryptography are generally employed to shelter data safety extensively. The term ‘cryptography’ refers to the process of safeguarding the secret data against access by unscrupulous persons in scenarios where it is humanly impossible to furnish physical protection. It deals with the methods which convert the data between intelligible and unintelligible forms by encryption/decryption functions with the management of key(s).Nowadays cryptographic keymanagement issues that arise due to the distributed nature of IT resources, as well the distributed nature of their control. Recently these issues are solved by optimization algorithms utilized in the cryptographic algorithms. The purpose of this paper isto give a survey of optimal cryptographic keys that can be developed with the help of optimization algorithms, and to address their merits to the real-world scenarios.

Wireless Sensor Networks (WSN)become more popular due to the wide range of applications in various fields. WSNconsists of a group of sensor nodes deployed in the region of interest. Energy efficiency is the major challenge while deigning WSN. Clustering is one of the important energyefficient techniques. Clustering is the process of grouping the nodes into clusters. A cluster consists of a Cluster Head (CH) and number of cluster members. CH is responsible for collecting data from cluster members, aggregating it and forwarding the aggregated data to Base Station (BS). So, CH selection plays a vital role to preserve energy in WSN. Many researchers are carried out to select the proper CHs. CH selection influences the overall performance of the WSN. In this paper, a dynamic CH selection using Fuzzy logic is proposed. The fuzzy input parameters are residual energy and the distance to BS. The output parameter is the probability of becoming CH. The proposed method is compared to the well known clustering protocol LEACH. Simulation results shows that the proposed method produces better results than LEACH interms of energy consumption and network lifetime.