Hybrid chaos-based image encryption algorithm using Chebyshev chaotic map with deoxyribonucleic acid sequence and its performance evaluation

The media content shared on the internet has increased tremendously nowadays. The streaming service has major role in contributing to internet traffic all over the world. As the major content shared are in the form of images and rapid increase in computing power a better and complex encryption standard is needed to protect this data from being leaked to unauthorized person. Our proposed system makes use of chaotic maps, deoxyribonucleic acid (DNA) coding and ribonucleic acid (RNA) coding technique to encrypt the image. As videos are nothing but collection of images played at the rate of minimum 30 frames/images per second, this methodology can also be used to encrypt videos. The complexity and dynamic nature of chaotic systems makes decryption of content by unauthorized personal difficult. The hybrid usage of chaotic systems along with DNA and RNA sequencing improves the encryption efficiency of the algorithm and also makes it possible to decrypt the images at the same time without consuming too much of computation power

Optimal Task Scheduling in the Cloud Environment using a Mean Grey Wolf Optimization Algorithm

Cloud computing is one of the emerging areas in computing platforms, supporting heterogeneous, parallel and distributed environments. An important challenging issue in cloud computing is task scheduling, which directly influences system performance and its efficiency. The primary objective of task scheduling involves scheduling tasks related to resources and minimizing the time span of the schedule. In this study, we propose a Modified Mean Grey Wolf Optimization (MGWO) algorithm to enhance system performance, and consequently reduce scheduling issues. The main objective of this method is focused upon minimizing the makespan (execution time) and energy consumption.  These two objective functions are elaborated in the algorithm in order to suitably regulate the quality of results based on response, in order to achieve a near optimal solution. The implementation results of the proposed algorithm are evaluated using the CloudSim toolkit for standard workloads (normal and uniform). The advantage of the proposed method is evident from the simulation results, which show a comprehensive reduction in makespan and energy consumption. The outcomes of these results show that the proposed Mean GWO algorithm achieves a 8.85% makespan improvement compared to the PSO algorithm, and 3.09% compared to the standard GWO algorithm for the normal dataset. In addition, the proposed algorithm achieves 9.05% and 9.2% improvement in energy conservation compared to the PSO and standard GWO algorithms for the uniform dataset, respectively

Universal Keyword Classifier on Public Key Based Encrypted Multikeyword Fuzzy Search in Public Cloud

Cloud computing has pioneered the emerging world by manifesting itself as a service through internet and facilitates third party infrastructure and applications. While customers have no visibility on how their data is stored on service provider’s premises, it offers greater benefits in lowering infrastructure costs and delivering more flexibility and simplicity in managing private data. The opportunity to use cloud services on pay-per-use basis provides comfort for private data owners in managing costs and data. With the pervasive usage of internet, the focus has now shifted towards effective data utilization on the cloud without compromising security concerns. In the pursuit of increasing data utilization on public cloud storage, the key is to make effective data access through several fuzzy searching techniques. In this paper, we have discussed the existing fuzzy searching techniques and focused on reducing the searching time on the cloud storage server for effective data utilization. Our proposed Asymmetric Classifier Multikeyword Fuzzy Search method provides classifier search server that creates universal keyword classifier for the multiple keyword request which greatly reduces the searching time by learning the search path pattern for all the keywords in the fuzzy keyword set. The objective of using BTree fuzzy searchable index is to resolve typos and representation inconsistencies and also to facilitate effective data utilization

Analysis of transaction throughput in P2P environments.

Includes bibliographical references (p. 78-81).In recent years P2P systems have gained tremendous popularity. Support of a transaction processing facility in P2P systems would provide databases at a low cost. Extending distributed database algorithms such as 2PC and ROWA to P2P environments might not provide the best performance because the P2P systems are characterized by high site failure rates and an unpredictable network topology. The choice of algorithms in building P2PDB is difficult because of the lack of information about the performance of database algorithms in P2P environments. This thesis analyzes the performance of one such algorithm, the epidemic algorithm against the performance of traditional database algorithms in simulated P2P environments.[by] Arun Chokkalingam.M.S

Endothelin-1 in colorectal cancer

Abstract not available

SARS-CoV-2 seroprevalence among the general population and healthcare workers in India, December 2020–January 2021

Background: Earlier serosurveys in India revealed seroprevalence of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) of 0.73% in May–June 2020 and 7.1% in August–September 2020. A third serosurvey was conducted between December 2020 and January 2021 to estimate the seroprevalence of SARS-CoV-2 infection among the general population and healthcare workers (HCWs) in India. Methods: The third serosurvey was conducted in the same 70 districts as the first and second serosurveys. For each district, at least 400 individuals aged ≥10 years from the general population and 100 HCWs from subdistrict-level health facilities were enrolled. Serum samples from the general population were tested for the presence of immunoglobulin G (IgG) antibodies against the nucleocapsid (N) and spike (S1-RBD) proteins of SARS-CoV-2, whereas serum samples from HCWs were tested for anti-S1-RBD. Weighted seroprevalence adjusted for assay characteristics was estimated. Results: Of the 28,598 serum samples from the general population, 4585 (16%) had IgG antibodies against the N protein, 6647 (23.2%) had IgG antibodies against the S1-RBD protein, and 7436 (26%) had IgG antibodies against either the N protein or the S1-RBD protein. Weighted and assay-characteristic-adjusted seroprevalence against either of the antibodies was 24.1% [95% confidence interval (CI) 23.0–25.3%]. Among 7385 HCWs, the seroprevalence of anti-S1-RBD IgG antibodies was 25.6% (95% CI 23.5–27.8%). Conclusions: Nearly one in four individuals aged ≥10 years from the general population as well as HCWs in India had been exposed to SARS-CoV-2 by December 2020