2021 ◽  
Vol 23 (09) ◽  
pp. 1105-1121
Author(s):  
Dr. Ashish Kumar Tamrakar ◽  
◽  
Dr. Abhishek Verma ◽  
Dr. Vishnu Kumar Mishra ◽  
Dr. Megha Mishra ◽  
...  

Cloud computing is a new model for providing diverse services of software and hardware. This paradigm refers to a model for enabling on-demand network access to a shared pool of configurable computing resources, that can be rapidly provisioned and released with minimal service provider interaction .It helps the organizations and individuals deploy IT resources at a reduced total cost. However, the new approaches introduced by the clouds, related to computation outsourcing, distributed resources and multi-tenancy concept, increase the security and privacy concerns and challenges. It allows users to store their data remotely and then access to them at any time from any place .Cloud storage services are used to store data in ways that are considered cost saving and easy to use. In cloud storage, data are stored on remote servers that are not physically known by the consumer. Thus, users fear from uploading their private and confidential files to cloud storage due to security concerns. The usual solution to secure data is data encryption, which makes cloud users more satisfied when using cloud storage to store their data. Motivated by the above facts; we have proposed a solution to undertake the problem of cloud storage security. In cloud storage, there are public data that do not need any security measures, and there are sensitive data that need applying security mechanisms to keep them safe. In that context, data classification appears as the solution to this problem. The classification of data into classes, with different security requirements for each class is the best way to avoid under security and over security situation. The existing cloud storage systems use the same Journal of University of Shanghai for Science and Technology ISSN: 1007-6735 Volume 23, Issue 9, September – 2021 Page-1105 key size to encrypt all data without taking into consideration its confidentiality level. Treating the low and high confidential data with the same way and at the same security level will add unnecessary overhead and increase the processing time. In our proposal, we have combined the K-NN (K Nearest Neighbors) machine learning method and the goal programming decision-making method, to provide an efficient method for data classification. This method allows data classification according to the data owner security needs. Then, we introduce the user data to the suitable security mechanisms for each class. The use of our solution in cloud storage systems makes the data security process more flexible, besides; it increases the cloud storage system performance and decreases the needed resources, which are used to store the data.


Author(s):  
Pradeep Kumar Tiwari ◽  
Sandeep Joshi

Researchers have done tremendous works for data security, but a robust security mechanism is not available yet. Researchers are doing continuous work to build robust SaaS mechanism. SaaS has several security vulnerabilities. Data security is still the most important challenge to researcher and they can constantly do research to protect the data over the network but they are facing numerous technical challenges to completely secure the cloud network and cloud storage. This work would be helpful to understand data security and privacy problems. Researchers can find the new way to understand SaaS security vulnerabilities and currently available solutions.


Cloud Computing is a robust, less cost, and an effective platform for providing services. Nowadays, it is applied in various services such as consumer business or Information Technology (IT) carried over the Internet. This cloud computing has some risks of security because, the services which are required for its effective compilation is outsources often by the third party providers. This makes the cloud computing more hard to maintain and monitor the security and privacy of data and also its support. This sudden change in the process of storing data towards the cloud computing technology improved the concerns about different issues in security and also the various threats present in this cloud storage. In the concept of security in cloud storage, various threats and challenges are noted by recent researchers. Hence, an effective framework of providing security is required. The main aim of this paper is to analyze various issues in securing the cloud data threats present in the cloud storage and to propose a novel methodology to secure it. This paper also identifies the most crucial components that can be incorporated in the already existing security measures while designing the storage systems based on cloud. This study also provides us to identify all the available solutions for the challenges of security and privacy in cloud storage.


2019 ◽  
Author(s):  
Samankumara Hettige ◽  
Eshani Dasanayaka ◽  
Dileepa Senajith Ediriweera

Abstract Introduction Cloud storage facilities (CSF) has become popular among the internet users. There is limited data on CSF usage among university students in low middle-income countries including Sri Lanka. In this study we present the CSF usage among medical students at the Faculty of Medicine, University of Kelaniya. Methods We undertook a cross sectional study at the Faculty of Medicine, University of Kelaniya, Sri Lanka. Stratified random sampling was used to recruit students representing all the batches. A self-administrated questionnaire was given. Results Of 261 (90.9%) respondents, 181 (69.3%) were females. CSF awareness was 56.5% (95%CI: 50.3% - 62.6%) and CSF usage was 50.8% (95%CI: 44.4 - 57.2%). Awareness was higher in males (P=0.003) and was low in senior students. Google Drive was the commonest CSF followed by Dropbox and OneDrive. There was no association between CSF awareness and pre-university entrance or undergraduate examination performance. Inadequate knowledge, time, accessibility, security and privacy concerns limited CSF usage. 69.8% indicated that they would like to undergo training on CSF as an effective tool for education. Conclusion CSF awareness and usage was nearly 50% among the students and Google drive is the most popular CSF. Lack of knowledge, accessibility, concerns on security and privacy limited CSF usage among students. Majority were interested to undergo training on CSF and undergraduate ICT curricula should introduce CSF as effective educational tools.


IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 131723-131740 ◽  
Author(s):  
Pan Yang ◽  
Naixue Xiong ◽  
Jingli Ren

2019 ◽  
pp. 1440-1459
Author(s):  
Sara Usmani ◽  
Faiza Rehman ◽  
Sajid Umair ◽  
Safdar Abbas Khan

The novel advances in the field of Information Technology presented the people pleasure, luxuries and ease. One of the latest expansions in the Information Technology (IT) industry is Cloud Computing, a technology that uses the internet for storage and access of data. It is also known as on-demand computing. The end user can access personal data and applications anywhere any time with a device having internet. Cloud Computing has gained an enormous attention but it results in the issues of data security and privacy as the data is scattered on different machines in different places across the globe which is a serious threat to the technology. It has many advantages like flexibility, efficiency and scalability but many of the companies are hesitant to invest in it due to privacy concerns. In this chapter, the objective is to review the privacy and security issues in cloud storage of Big Data and to enhance the security in cloud environment so that end users can enjoy a trustworthy and reliable data storage and access.


2018 ◽  
pp. 65-83
Author(s):  
Mingzhong Wang ◽  
Don Kerr

With the features of mobility, reality augmentation, and context sensitivity, wearable devices are widely deployed into various domains. However, the sensitivity of collected data makes security and privacy protection one of the first priority in the advancement of wearable technologies. This chapter provides a study on encryption-based confidentiality protection for data storage systems in wearable platforms. The chapter first conducts a review to storage solutions in consumer wearable products and explores a two-tier, local flash memory and remote cloud storage, storage system in wearable platforms. Then encryption-based confidentiality protection and implementation methods for both flash memory and remote cloud storage are summarized. According to the interaction and integration of these two components, a categorization of confidential storage systems in wearable platforms is proposed. In addition, the benefits and selection criteria for each category are also discussed.


Author(s):  
Mingzhong Wang ◽  
Don Kerr

With the features of mobility, reality augmentation, and context sensitivity, wearable devices are widely deployed into various domains. However, the sensitivity of collected data makes security and privacy protection one of the first priority in the advancement of wearable technologies. This chapter provides a study on encryption-based confidentiality protection for data storage systems in wearable platforms. The chapter first conducts a review to storage solutions in consumer wearable products and explores a two-tier, local flash memory and remote cloud storage, storage system in wearable platforms. Then encryption-based confidentiality protection and implementation methods for both flash memory and remote cloud storage are summarized. According to the interaction and integration of these two components, a categorization of confidential storage systems in wearable platforms is proposed. In addition, the benefits and selection criteria for each category are also discussed.


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