DStore: Blockchain-Powered Decentralized Cloud Mesh

Data is a critical asset for any company, as well as for any individual as well, but it is also vulnerable to attack. In the last few years, we have seen an alarming increase in data breaches that have compromised millions of accounts and resulted in billions of dollars lost. But how do you protect something so sensitive? In response to this, we propose our Project. This project focuses on developing a Decentralized Cloud Storage to store and secure data. You don't access data simply specifying 'where it is' in Decentralised Cloud Storage. Instead, you define 'what it is'. Because data is distributed throughout a global network rather than being stored in a specific location, the concept of location is rendered obsolete in decentralised cloud storage

Cloud-based Privacy-Preserving Collaborative Consumption for Sharing Economy

Cloud computing has been a dominant paradigm for a variety of information processing platforms, particularly for enabling various popular applications of sharing economy. However, there is a major concern regarding data privacy on these cloud-based platforms. This work presents novel cloud-based privacy-preserving solutions to support collaborative consumption applications for sharing economy. In typical collaborative consumption, information processing platforms need to enable fair cost-sharing among multiple users for utilizing certain shared facilities and communal services. Our cloud-based privacy-preserving protocols, based on homomorphic Paillier cryptosystems, can ensure that the cloud-based operator can only obtain an aggregate schedule of all users in facility sharing, or a service schedule conforming to service provision rule in communal service sharing, but is unable to track the personal schedules or demands of individual users. More importantly, the participating users are still able to settle cost-sharing among themselves in a fair manner for the incurred costs, without knowing each other's private schedules or demands. Our privacy-preserving protocols involve no other third party who may compromise privacy. We also provide an extensive evaluation study and a proof-of-concept system prototype of our protocols.Comment: To appear in IEEE Trans. Cloud Computin

Enhancing healthcare services through cloud service: a systematic review

Although cloud-based healthcare services are booming, in-depth research has not yet been conducted in this field. This study aims to address the shortcomings of previous research by analyzing all journal articles from the last five years using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) systematic literature review methodology. The findings of this study highlight the benefits of cloud-based healthcare services for healthcare providers and patients, including enhanced healthcare services, data security, privacy issues, and innovative information technology (IT) service delivery models. However, this study also identifies challenges associated with using cloud services in healthcare, such as security and privacy concerns, and proposes solutions to address these issues. This study concludes by discussing future research directions and the need for a complete solution that addresses the conflicting requirements of the security, privacy, efficiency, and scalability of cloud technologies in healthcare

Optimizing Onion Crop Management: A Smart Agriculture Framework with IoT Sensors and Cloud Technology

Smart agriculture, fueled by the integration of Internet of Things (IoT) and cloud technology, has revolutionized modern farming practices. In this study, we propose a step-by-step framework for optimizing onion crop management using IoT sensors and cloud-based solutions. By deploying various IoT sensors, including soil moisture, temperature, humidity, and aerial drones, essential data about the onion crops is collected and transmitted to a central data hub. Optional edge computing devices enable real-time data processing, minimizing latency and bandwidth usage.The collected data is aggregated and stored securely on a cloud platform, which facilitates advanced data analysis and insights. Utilizing machine learning algorithms, the cloud platform can provide valuable information about the onion's growth patterns, health status, and growth trajectory. Farmers can easily access this information through a user-friendly dashboard, accessible via web or mobile applications.Automated alerts and notifications enable timely intervention, notifying farmers about any deviations from optimal conditions, such as low moisture levels or pest infestations. The system's predictive capabilities allow for precision irrigation and nutrient management, optimizing resource usage and improving crop health.The accumulated historical data offers a wealth of information, enabling the identification of trends and the prediction of growth patterns for future planting seasons. Throughout this process, data security and privacy measures are prioritized, with encrypted data transmission and storage to protect farmers' sensitive information.The integration of IoT and cloud technology provides an efficient and effective solution for monitoring onion crop growth. The proposed framework offers farmers valuable insights, improves productivity, and promotes sustainable agricultural practices

SECURING THE DATA STORAGE AND PROCESSING IN CLOUD COMPUTING ENVIRONMENT

Organizations increasingly utilize cloud computing architectures to reduce costs and en- ergy consumption both in the data warehouse and on mobile devices by better utilizing the computing resources available. However, the security and privacy issues with publicly available cloud computing infrastructures have not been studied to a sufficient depth for or- ganizations and individuals to be fully informed of the risks; neither are private nor public clouds prepared to properly secure their connections as middle-men between mobile de- vices which use encryption and external data providers which neglect to encrypt their data. Furthermore, cloud computing providers are not well informed of the risks associated with policy and techniques they could implement to mitigate those risks. In this dissertation, we present a new layered understanding of public cloud comput- ing. On the high level, we concentrate on the overall architecture and how information is processed and transmitted. The key idea is to secure information from outside attack and monitoring. We use techniques such as separating virtual machine roles, re-spawning virtual machines in high succession, and cryptography-based access control to achieve a high-level assurance of public cloud computing security and privacy. On the low level, we explore security and privacy issues on the memory management level. We present a mechanism for the prevention of automatic virtual machine memory guessing attacks

Application of Artificial Intelligence in IoT Security for Crop Yield Prediction

This research explores the application of Artificial Intelligence (AI) in the Internet of Things (IoT) for crop yield prediction in agriculture. IoT devices, like sensors and drones, collect data on temperature, humidity, soil moisture, and crop health. AI algorithms process and integrate this data to provide a comprehensive view of the agricultural environment.AI-driven anomaly detection helps identify threats to crop yield, such as pests, diseases, and adverse weather conditions. Predictive analytics, based on historical and real-time data, forecast crop yield for informed decision-making in irrigation and fertilization.AI-powered image recognition detects early signs of pests and diseases, aiding timely treatment to prevent crop losses. Resource optimization allocates water and fertilizers efficiently, minimizing waste and environmental impact.AI-driven decision support systems offer personalized recommendations for ideal planting schedules and crop rotations, maximizing yield. Autonomous farming integrates AI into machinery for precision tasks like planting and monitoring.Secure communication protocols protect sensitive agricultural data from cyber threats, ensuring data integrity and privacy