scholarly journals Calibration Factors based intrusion detection (CFID) in Cloud Computing

2019 ◽  
Vol 8 (6) ◽  
pp. 3748-3757
Keyword(s):  
Cloud Computing ◽  
Intrusion Detection ◽  
Data Storage ◽  
Defense Mechanisms ◽  
Cloud Platform ◽  
Recent Past ◽  
Sensitive Data ◽  
Detection Mechanism ◽  
Public And Private ◽  
Private Cloud Computing

The distributed computing is the buzz in recent past, cloud computing stands first in this category. This is since, the users can adapt anything related to data storage, magnificent computing facilities on a system with less infrastructure from anywhere at any time. On other dimension such public and private cloud computing strategies would also attracts the foul players to perform intrusion practices. This is since, the comfortability that the cloud platform providing to end users intends them to adapt these services in regard to save or compute the sensitive data. The scope of vulnerability to breach the data or services over cloud computing is more frequent and easier, which is since, these services relies on internet protocol. In this regard, the research in intrusion detection defense mechanisms is having prominent scope. This manuscript, projecting a novel intrusion detection mechanism called "calibration factors-based intrusion detection (CFID)" for cloud computing networks. The experimental study portrayed the significant scope of the proposal CFID to detect the intrusion activities listed as remoteto-Local, Port Scanning, and Virtual-Machine-Trapping.

Research on Security and Defense Technologies in the Cloud Computing

2013 ◽  
Vol 347-350 ◽  
pp. 3312-3316
Author(s):  
Hong Jun Chen ◽  
Xue Qin Wu
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Service Providers ◽  
Cloud Platform ◽  
Computing Environment ◽  
Security Risks ◽  
Cloud Computing Environment ◽  
Virtualization Technology ◽  
Legal Constraints ◽  
Secure Cloud Computing

The positive factors of the cloud computing: the great commercial value, the cheap and convenient use, has been recognized widely. But there are many risks on security. These security risks will greatly restrict the development of cloud computing. Cloud security risks such as: the cloud platform is easily vulnerable, cloud resources is easily abused, the cloud platform data is accessed by unauthorized user or the data is missing, the violations in the network is difficult to trace and survey, and the service providers replacement will affect the migration of the users data and services. So we research the virtualization technology, data backup and disaster recovery technology, encryption technology of data storage and transmission, the authentication technology of service providers and users, risk assessment, and legal constraints and safety training. Our research is strived to obtain a secure cloud computing environment.

scholarly journals Construction of foundation pit monitoring information cloud platform based on SaaS mode

2020 ◽  
Vol 165 ◽  
pp. 03012
Author(s):  
Liu Qiong ◽  
Zeng Dongling ◽  
Ouyang Zhengping ◽  
Zhang Yinzu ◽  
Yang Yongchang ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Design Thinking ◽  
New Technologies ◽  
Rapid Development ◽  
Cloud Platform ◽  
Computing Technology ◽  
Foundation Pit ◽  
Favorable Conditions ◽  
Monitoring Information

With the rapid development of Internet cloud computing technology, big data and visualization and other new technologies, the powerful data storage, calculation and analysis capabilities of new technologies provide favorable conditions for improving the timeliness, reliability and informatization level of foundation pit monitoring. By using SaaS mode and cloud computing technology, this paper subdivides the requirements of foundation pit monitoring work, and puts forward solutions according to design thinking and design means. The foundation pit monitoring information cloud platform is built in the way of Cloud Architecture, which greatly improves the efficiency of foundation pit monitoring, and realizes the high sharing of monitoring data information and platform resources.

An Approach to Data Confidentiality Protection in Cloud Environments

2012 ◽  
Vol 9 (3) ◽  
pp. 67-83 ◽  
Author(s):  
Stephen S. Yau ◽  
Ho G. An ◽  
Arun Balaji Buduru
Keyword(s):  
Cloud Computing ◽  
Data Processing ◽  
Data Storage ◽  
Service Providers ◽  
Data Confidentiality ◽  
Sensitive Data ◽  
Computing Systems ◽  
Cloud Application ◽  
Cloud Infrastructures ◽  
Processing Service

In current cloud computing systems, because users’ data is stored and processed by computing systems managed and operated by various service providers, users are concerned with the risks of unauthorized usage of their sensitive data by various entities, including service providers. The current cloud computing systems protect users’ data confidentiality from all entities, except service providers. In this paper, an approach is presented for improving the protection of users’ data confidentiality in cloud computing systems from all entities, including service providers. The authors’ approach has the following features: (1) separation of cloud application providers, data processing service providers and data storage providers, (2) anonymization of users’ identities, (3) grouping cloud application components and distributing their execution to distinct cloud infrastructures of data processing service providers, and (4) use of data obfuscation and cryptography for protecting the sensitive data from unauthorized access by all entities, including service providers. The proposed approach ensures that users’ sensitive data can be protected from their service providers even if the users do not have full cooperation from their service providers.

Research on Key Technologies of Massive Videos Management Under the Background of Cloud Platform

2019 ◽  
Vol 23 (1) ◽  
pp. 72-77
Author(s):  
Lin Jin ◽  
◽  
Changhong Yan
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Management System ◽  
Rapid Development ◽  
Mobile Internet ◽  
Video Data ◽  
Cloud Platform ◽  
Module Design ◽  
Management Platform ◽  
Key Technologies

With the rapid development of mobile internet and smart city, video surveillance is popular in areas such as transportation, schools, homes, and shopping malls. It is important subject to manage the massive videos quickly and accurately. This paper tries to use Hadoop cloud platform for massive video data storage, transcoding and retrieval. The key technologies of cloud computing and Hadoop are introduced firstly in the paper. Then, we analyze the functions of video management platform, such as user management, videos storage, videos transcoding, and videos retrieval. According to the basic functions and cloud computing, each module design process and figure are provided in the paper. The massive videos management system based on cloud platform will be better than the traditional videos management system in the aspects of storage capacity, transcoding performance and retrieval speed.

scholarly journals A Framework for Implementing Prediction Algorithm over Cloud Data as a Procedure for Cloud Data Mining

2021 ◽  
Vol 2 (2) ◽  
pp. 1-8
Author(s):  
Safwan A. S. Al-Shaibani ◽  
Keyword(s):  
Data Storage ◽  
Model Building ◽  
Cloud Services ◽  
Prediction Algorithm ◽  
Easy Access ◽  
Cloud Platform ◽  
Recent Past ◽  
Cloud Data ◽  
Platform As A Service ◽  
Post Surgery

The cloud has become an important phrase in data storage for many reasons. Cloud services and applications are widespread in many industries including healthcare due to easy access. The limitless quantity of data available on the clouds has triggered the interest of many researchers in the recent past. It has forced us to deploy machine learning for analyzing the data to get insights as well as model building. In this paper, we have built a service on Heroku Cloud which is a cloud platform as a service (PaaS) and has 15 thousand records with 25 features. The data belongs to healthcare and is related to post-surgery complications. The boost prediction algorithm was applied for analysis and implementation was done in python. The results helped us to determine and tune some of the hyperparameters which have correlations with complications and the reported accuracy of training and testing was found to be 91% and 88% respectively.

scholarly journals Enhance the Security of Data Storage and Retrieval in Cloud Computing Through Authentication Based Encryption

2019 ◽  
Vol 8 (4) ◽  
pp. 11927-11931
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Virtual Machines ◽  
Public Key ◽  
Sensitive Data ◽  
Cloud Data ◽  
Finger Print ◽  
Additional Level ◽  
Cloud Users ◽  
Cloud User

The digital computing infrastructure is rapidly moving towards cloud based architecture. The protection of data is becoming a difficult task in the current scenario as more and more confidential and sensitive data is stored in cloud environment and transmitted between cloud users. In a cloud computing environment, the entire data reside over a set of networked resources of remote servers and locations. These data has been accessed by unauthorized cloud users through virtual machines. To provide additional level of cloud data security, Biometric based authentication with encryption using public key cryptography is proposed in this paper. The proposed model Authentication Based Encryption (ABE) helps to enhance the security of data as well as the authentication of cloud user. The sensitive data is initially encrypted and then stored secretly with biometric finger print image. The resultant image is transmitted through the in-secured channel. However to avoid unauthorized access, the image is decomposed and stored in cloud separately as encrypted message and finger print. Before beginning the decryption process, the finger print of the cloud user is being compared with the stored image for authentication. If the match is found, the encrypted data is decrypted by the authenticated cloud user. Otherwise access to the data is denied to ensure security. Thus, the proposed framework provides an additional level of protection to public key algorithm with authentication

Analysis of the Join Performance in Vertically Distributed Cloud Databases

2015 ◽  
Vol 6 (2) ◽  
pp. 65-87 ◽  
Author(s):  
Jens Kohler ◽  
Kiril Simov ◽  
Thomas Specht
Keyword(s):  
Cloud Computing ◽  
Data Security ◽  
Security And Privacy ◽  
Sensitive Data ◽  
Public And Private ◽  
Huge Data ◽  
Cloud Databases ◽  
Accounting Model ◽  
Privacy Constraints ◽  
Distributed Cloud

Cloud Computing becomes interesting for enterprises across all branches. Renting computing capabilities from external providers avoids initial investments, as only those resources have to be paid that were used eventually. Especially in the context of “Big Data” this pay-as-you-go accounting model is particularly important. The dynamically scalable resources from the Cloud enable enterprises to store or analyze these huge amounts of unstructured data without using their own hardware infrastructure. However, Cloud Computing is currently facing severe data security and protection issues. These challenges require new ways to store and analyze data, especially when huge data volumes with sensitive data are stored at external locations. The presented approach separates data on database table level into independent chunks and distributes them across several clouds. Hence, this work is a contribution to a more secure and resilient cloud architecture as multiple public and private cloud providers can be used independently to store data without losing data security and privacy constraints.

Adoption of Cloud Computing: A Study with Public and Private Hospitals in a Developing Country

2018 ◽  
Vol 15 (05) ◽  
pp. 1850044 ◽  
Author(s):  
Gabriela Labres Mallmann ◽  
Antônio Carlos Gastaud Maçada
Keyword(s):  
Cloud Computing ◽  
Developing Country ◽  
It Professionals ◽  
Sensitive Data ◽  
Private Hospitals ◽  
Public And Private ◽  
Private Organizations ◽  
Expected Benefits ◽  
Public And Private Hospitals ◽  
It Executives

This research aims to analyze the factors influencing the adoption of cloud computing (CC) in public and private hospitals in a developing country setting, specifically in Brazil’s hospital industry. We interviewed IT professionals from four hospitals. The study demonstrates that concerns with security and availability matter more to the hospitals than the expected benefits of CC, such as flexibility and cost reduction. In addition, the findings show that there are relevant differences between public and private organizations, such as regulatory issues and cost, which influence the adoption of cloud computing in each context. Cloud-based resources continue to worry companies that deal with sensitive data as healthcare institutions. Knowledge acquired from this study is particularly beneficial to IT executives to guide their decision to create or adjust CC initiatives in healthcare.

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