Cloud computing (CC) plays a significant role in revolutionizing the information and communication technology (ICT) industry, allowing flexible delivery of new services and computing resources at a fraction of the costs for end-users than traditional computing. Unfortunately, many potential cyber threats impact CC-deployed services due to the exploitation of CC’s characteristics, such as resource sharing, elasticity, and multi-tenancy. This survey provides a comprehensive discussion on security issues and challenges facing CC for cloud service providers and their users. Furthermore, this survey proposes a new taxonomy for classifying CC attacks, distributed denial of service (DDoS) attacks, and DDoS attack detection approaches on CC. It also provides a qualitative comparison with the existing surveys. Finally, this survey aims to serve as a guide and reference for other researchers working on new DDoS attack detection approaches within the CC environment.

Objectives: This paper discusses about the component based software engineering approach along with its classification of various approaches of CBSE and Component Based Development [CBD] and the life cycle development model of Component Based Software Development [CBSD] has been proposed by the component re-usability concept in lieu of reducing the software cost. Method: The main focus of the software engineering and component based software engineering is the development of the software in such a manner that it might be used again for the development of some other software. Component Based Software Engineering [CBSE] includes the use of components lying in the component repository while software re-engineering focusses relies with using the concept of forward and reverse engineering. This is done for reducing the software development cost by making use of Component Based Software Engineering [CBSE] principles and s/w reengineering techniques. Findings: Now a-days the development of software from the scratch has become less prioritized and is being used very less. Component based software engineering plays a very vital role in developing of the software not from scratch but instead using the existing components for the development of new software. Hence it can be concluded or finded that the cost of the software development from the re-usability concept can be reduced to a large extent in comparison to the software development from the very scratch being a very costly measure. The proposed model will be helpful in reducing the software development cost by using the component based development strategy. Applications / Improvements: The proposed SDLC model for CBSD can be used for the real life applications as well and thereby can be re-used again and again as per the requirements of the industry.

A Model based on Effective and Intelligent Sentiment Mining: A Review

Objectives: Smart Device with Open Source Platform, cloud tools and technologies are at the key point of healthcare variation. E-Devices replacing on manual basis or automated medical reports/graphs, private or secure clouds provide private access to automated healthcare records and device based device collaboration tools are reforming information share among medical experts. Methods/Analysis: In proposed Work, We are using Open Source API like Google API within system for automatic improvement of the entire system rather than deploy each time system after new version of implemented platform. According to below mentioned Proposed Work, We are encrypt word with current timestamp middle number using sampling method and every time system will auto decrypt private data with same TIMESATMP technique on receiver side panel. Findings: All the findings are mentioned in the form of statements given below: Statement 1: Existing System: MICROSOFT [Working on Only WINDOWS based platform] Statement 2: Existing System: PREBUILD ALGORITHM [Easy to Decrypt with predefined decryption methods]. Novelty/Improvement: Smart Devices based healthcare applications will more advance with Open Source Based API and Private data will more secure.

Digital health technologies are reshaping healthcare by improving disease prevention, early diagnosis, and continuous health monitoring. This chapter delves into the expanding role of digital tools—from e-health and telemedicine to AI and ML—in advancing preventive healthcare. It emphasizes the use of wearable devices and biosensors for real-time monitoring, empowering both patients and providers to detect early health risks. The shift to AI-powered systems enables personalized care, automated diagnostics, and proactive engagement, but also raises concerns around data privacy, ethical use, adoption challenges, and equity in access—especially in underserved regions. Through global case studies, the chapter highlights successful digital health interventions and explores future directions, including digital integration in national health policies, regulation, and literacy. It also examines trends like virtual care, remote monitoring, and AI-linked EHRs, offering insights into how digital health can foster a more inclusive, responsive, and future-ready healthcare system.