Is the urban Indian consumer ready for environment-friendly apparel?

The textile industry is inherently unsustainable, has a wide range of environmental and toxicological impacts and has been condemned as one of the worst offenders on earth in terms of pollution. The textile industry in India has largely been driven by small units which practice age-old methods of bleaching and dyeing, which adversely affect the balance of the local ecology. Given that the role that the consumers may play could be significant in pressuring the industry to introduce clean technology and in demanding 'pollution-free' garments, this paper probes whether urban Indian consumers are ready to make this demand for 'pollution-free' garments. The study concludes that there are three segments of consumers: Green Apparel Consumers, Greener Apparel Consumers and Non-Green Apparel Consumers, of which the Greener Apparel Consumers are ready for environment-friendly clothing and are willing to pay more for such clothing. The demographics of this segment are reported and the strategies managers may adopt to reach out to the other segments after saturating the Greener consumers are discussed. The kinds of apparel for which Greener Consumers are ready to pay higher prices are investigated and the environmental issues that would be effective in communicating to the segments are set forth.urban Indians; environment-friendly apparel; segmentation; willingness to pay; textile industry; India; environmental pollution; pollution-free garments; green apparel; green clothing; environmental impact; green economics.

Investigation on storage level data integrity strategies in cloud computing: classification, security obstructions, challenges and vulnerability

Abstract Cloud computing provides outsourcing of computing services at a lower cost, making it a popular choice for many businesses. In recent years, cloud data storage has gained significant success, thanks to its advantages in maintenance, performance, support, cost, and reliability compared to traditional storage methods. However, despite the benefits of disaster recovery, scalability, and resource backup, some organizations still prefer traditional data storage over cloud storage due to concerns about data correctness and security. Data integrity is a critical issue in cloud computing, as data owners need to rely on third-party cloud storage providers to handle their data. To address this, researchers have been developing new algorithms for data integrity strategies in cloud storage to enhance security and ensure the accuracy of outsourced data. This article aims to highlight the security issues and possible attacks on cloud storage, as well as discussing the phases, characteristics, and classification of data integrity strategies. A comparative analysis of these strategies in the context of cloud storage is also presented. Furthermore, the overhead parameters of auditing system models in cloud computing are examined, considering the desired design goals. By understanding and addressing these factors, organizations can make informed decisions about their cloud storage solutions, taking into account both security and performance considerations

ZSS Signature-Based Audit Message Verification Process for Cloud Data Integrity

Online cloud data storage, a pillar of the IT industry, offers data owners a plethora of attractive developments in highly sought-after online scalable storage services for them to willing new inventive and investment business profit. Today, most cloud data security research focuses on improving the accuracy of outsourced data audits rather than paying attention to internal and external enemies who could hack a cloud server. Even though the data owner enviously envies the data auditing job of stored data to a trusted Third Party Auditor (TPA) to save communication as well as the computational overhead of data which outsourcing to a reputable Cloud Service Provider (CSP), TPA is unreliable in a realistic context. A TPA or a CSP may occasionally be a malicious attacker or be under the sway of other hostile attackers. As a result, either the message of the audit result might be faked or TPA may produce a phony audit message without carrying out any data verification work, in which case CSP would be in for a fight. Instead of establishing a secure communication route between all parties, a progressive technique is therefore required to thwart enemies’ attempts to collaborate with data owners who have outsourced their data. In this paper, we propose a model for an effective data integrity and audit message verification system based on the ZSS (Zhang, Safavi, and Susilo) signature, which protects data privacy in cloud storage and uses faked data recovery to pay back original data using a modular approach. We also consider our proposed model for a existing Blockchain-based Medical system that helps a patient party to check the intactness of their medical record in shared cloud storage via a third-party auditor. Finally, the experimental results of the performance of the proposed prototype of the system model have been measured and illustrated better efficiency of the proposed model with the comparison of the existing auditing model