Enhancement for Secured File Storage Using Modern Hybrid Cryptography

In a wide range of applications, from cloud storage to chat messaging, security is a major issue. In today's business world, there are several security dangers as well as a fiercely competitive environment. Thus we want a secure file storage solution to safeguard and convey their confidential data. Cryptography is a technique for encrypting or decrypting data to store information secretly and conceal its true meaning. The existing techniques include the fact that heavily encrypted, valid, and digitally signed material might be hard to obtain, even for an authorized user, at a time when access is essential for making decisions. This research suggests a modern hybrid cryptographic method to strengthen the security of file storage. The proposed algorithm follows the flow mentioned here: data collection, normalization technique is used for data preprocessing, and Advanced Encryption Standard (AES) is used for data encryption. Combining symmetric and asymmetric algorithms contributed to the growth of the modern hybrid cryptography algorithm. There are two types of encryption algorithms: Data Encryption Standard (DES), which is symmetric, and Rivest, Shamir, & Adleman (RSA), which is asymmetric. These two types of algorithms are then compared to see how well they perform in terms of encryption/decryptions time, key generation time, & file size.  The proposed algorithm is very effective in enhancement for secured file storage using modern hybrid cryptography

Assessment, Implication, and Analysis of Online Consumer Reviews: A Literature Review

The onset of e-marketplace, virtual communities and social networking has appreciated the influential capability of online consumer reviews (OCR) and therefore necessitate conglomeration of the body of knowledge. This article attempts to conceptually cluster academic literature in both management and technical domain. The study follows a framework which broadly clusters management research under two heads: OCR Assessment and OCR Implication (business implication). Parallel technical literature has been reviewed to reconcile methodologies adopted in the analysis of text content on the web, majorly reviews. Text mining through automated tools, algorithmic contribution (dominant majorly in technical stream literature) and manual assessment (derived from the stream of content analysis) has been studied in this review article. Literature survey of both the domains is analyzed to propose possible area for further research. Usage of text analysis methods along with statistical and data mining techniques to analyze review text and utilize the knowledge creation for solving managerial issues can possibly constitute further work. Available at: https://aisel.aisnet.org/pajais/vol9/iss2/4