Cloud Computing Security

2012 ◽  
Vol 4 (1) ◽  
pp. 52-66 ◽  
Author(s):  
Junaid Arshad ◽  
Paul Townend ◽  
Jie Xu ◽  
Wei Jie
Keyword(s):  
Cloud Computing ◽  
Large Scale ◽  
State Of The Art ◽  
Emerging Technology ◽  
The State ◽  
Computing Systems ◽  
Cloud Computing Security ◽  
On Demand ◽  
Cloud Computing Adoption ◽  
Security Challenges

The evolution of modern computing systems has lead to the emergence of Cloud computing. Cloud computing facilitates on-demand establishment of dynamic, large scale, flexible, and highly scalable computing infrastructures. However, as with any other emerging technology, security underpins widespread adoption of Cloud computing. This paper presents the state-of-the-art about Cloud computing along with its different deployment models. The authors also describe various security challenges that can affect an organization’s decision to adopt Cloud computing. Finally, the authors list recommendations to mitigate with these challenges. Such review of state-of-the-art about Cloud computing security can serve as a useful barometer for an organization to make an informed decision about Cloud computing adoption.

Towards Update-Efficient and Parallel-Friendly Content-Based Indexing Scheme in Cloud Computing

2018 ◽  
Vol 12 (02) ◽  
pp. 191-213
Author(s):  
Nan Zhu ◽  
Yangdi Lu ◽  
Wenbo He ◽  
Hua Yu ◽  
Jike Ge
Keyword(s):  
Cloud Computing ◽  
State Of The Art ◽  
High Volume ◽  
Data Partitioning ◽  
The State ◽  
Computing Systems ◽  
Indexing System ◽  
Indexing Method ◽  
Concurrent User ◽  
Art Research

The sheer volume of contents generated by today’s Internet services is stored in the cloud. The effective indexing method is important to provide the content to users on demand. The indexing method associating the user-generated metadata with the content is vulnerable to the inaccuracy caused by the low quality of the metadata. While the content-based indexing does not depend on the error-prone metadata, the state-of-the-art research focuses on developing descriptive features and misses the system-oriented considerations when incorporating these features into the practical cloud computing systems. We propose an Update-Efficient and Parallel-Friendly content-based indexing system, called Partitioned Hash Forest (PHF). The PHF system incorporates the state-of-the-art content-based indexing models and multiple system-oriented optimizations. PHF contains an approximate content-based index and leverages the hierarchical memory system to support the high volume of updates. Additionally, the content-aware data partitioning and lock-free concurrency management module enable the parallel processing of the concurrent user requests. We evaluate PHF in terms of indexing accuracy and system efficiency by comparing it with the state-of-the-art content-based indexing algorithm and its variances. We achieve the significantly better accuracy with less resource consumption, around 37% faster in update processing and up to 2.5[Formula: see text] throughput speedup in a multi-core platform comparing to other parallel-friendly designs.

A Multi-Dimensional Mean Failure Cost Model to Enhance Security of Cloud Computing Systems

2019 ◽  
pp. 211-225
Author(s):  
Mouna Jouini ◽  
Latifa Ben Arfa Rabai
Keyword(s):  
Cloud Computing ◽  
Cost Model ◽  
Quantitative Model ◽  
Security Risk ◽  
Computing Systems ◽  
Security Breaches ◽  
On Demand ◽  
Cloud Computing Adoption ◽  
Failure Cost ◽  
Security Risk Assessment

Cloud computing technology is a relatively new concept of offering reliable and virtualized resources, software and hardware on demand to users. It presents a new technology to deliver computing resources as a service. It allows several benefits for example services on demand, provisioning, shared resources and pay per use and suffers from several challenges. In fact, security presents a major obstacle in cloud computing adoption. In this paper, the authors will deal with security problems in cloud computing systems and estimate security breaches using a quantitative security risk assessment model. Finally, the authors use this quantitative model to solve these problems in cloud environments.

STATE-OF-THE-ART OF CLOUD COMPUTING ADOPTION IN MALAYSIA: A REVIEW

2015 ◽  
Vol 77 (18) ◽  
Author(s):  
Hanifah Abdul Hamid ◽  
Mokhtar Mohd Yusof
Keyword(s):  
Information Technology ◽  
Cloud Computing ◽  
State Of The Art ◽  
National Level ◽  
Research Direction ◽  
Cloud Adoption ◽  
Cloud Computing Adoption ◽  
Security Challenges ◽  
The Future ◽  
The Way

Cloud computing has made a significant transformation of information technology environment as well as the way the business is conducted in any organizations. While its advantages are obvious, its challenges need to be clearly addressed to ensure successful adoption. This article provides an insights of cloud computing adoption in Malaysia at the national level as well as a review of cloud adoption from various fields and domains in Malaysia which led to research direction in the future. Malaysia is being dedicated towards cloud adoption nationally, and keep its good progress to equip itself as a cloud-friendly country. However, security challenges seem to slow down the effort, thus these need to be dealt with properly. 

scholarly journals A cloud computing separation model based on information flow

Open Physics ◽  
2019 ◽  
Vol 17 (1) ◽  
pp. 128-134 ◽  
Author(s):  
Wei Ma ◽  
Huanqin Li ◽  
Deden Witarsyah
Keyword(s):  
Cloud Computing ◽  
Information Flow ◽  
End Users ◽  
Separation Mechanism ◽  
Computing Systems ◽  
Cloud Computing Security ◽  
Model Based ◽  
Separation Model

Abstract Separation is the primary consideration in cloud computing security. A series of security and safety problems would arise if a separation mechanism is not deployed appropriately, thus affecting the confidence of cloud end-users. In this paper, together with characteristics of cloud computing, the separation issue in cloud computing has been analyzed from the perspective of information flow. The process of information flow in cloud computing systems is formalized to propose corresponding separation rules. These rules have been verified in this paper and it is shown that the rules conform to non-interference security, thus ensuring the security and practicability of the proposed rules.

scholarly journals Large-scale Semantic Parsing without Question-Answer Pairs

2014 ◽  
Vol 2 ◽  
pp. 377-392 ◽  
Author(s):  
Siva Reddy ◽  
Mirella Lapata ◽  
Mark Steedman
Keyword(s):  
Natural Language ◽  
Large Scale ◽  
Graph Matching ◽  
State Of The Art ◽  
The State ◽  
Semantic Parsing ◽  
Matching Problem ◽  
Weak Supervision ◽  
Benchmark Datasets

In this paper we introduce a novel semantic parsing approach to query Freebase in natural language without requiring manual annotations or question-answer pairs. Our key insight is to represent natural language via semantic graphs whose topology shares many commonalities with Freebase. Given this representation, we conceptualize semantic parsing as a graph matching problem. Our model converts sentences to semantic graphs using CCG and subsequently grounds them to Freebase guided by denotations as a form of weak supervision. Evaluation experiments on a subset of the Free917 and WebQuestions benchmark datasets show our semantic parser improves over the state of the art.

scholarly journals GATECloud.net: a platform for large-scale, open-source text processing on the cloud

2013 ◽  
Vol 371 (1983) ◽  
pp. 20120071 ◽  
Author(s):  
Valentin Tablan ◽  
Ian Roberts ◽  
Hamish Cunningham ◽  
Kalina Bontcheva
Keyword(s):  
Cloud Computing ◽  
Language Processing ◽  
Large Scale ◽  
Virtual Machines ◽  
Cost Benefit Analysis ◽  
Text Processing ◽  
Cost Benefit ◽  
Data Intensive ◽  
On Demand ◽  
Usage Evaluation

Cloud computing is increasingly being regarded as a key enabler of the ‘democratization of science’, because on-demand, highly scalable cloud computing facilities enable researchers anywhere to carry out data-intensive experiments. In the context of natural language processing (NLP), algorithms tend to be complex, which makes their parallelization and deployment on cloud platforms a non-trivial task. This study presents a new, unique, cloud-based platform for large-scale NLP research—GATECloud. net. It enables researchers to carry out data-intensive NLP experiments by harnessing the vast, on-demand compute power of the Amazon cloud. Important infrastructural issues are dealt with by the platform, completely transparently for the researcher: load balancing, efficient data upload and storage, deployment on the virtual machines, security and fault tolerance. We also include a cost–benefit analysis and usage evaluation.

scholarly journals A Conceptual Model for Cloud Computing Adoption by SMEs in Australia

2016 ◽  
pp. 307-334 ◽  
Author(s):  
Ishan Senarathna ◽  
Matthew Warren ◽  
William Yeoh ◽  
Scott Salzman
Keyword(s):  
Cloud Computing ◽  
Conceptual Model ◽  
Business Service ◽  
Perceived Benefits ◽  
Public Cloud ◽  
Total Cost ◽  
The Public ◽  
Software Applications ◽  
On Demand ◽  
Cloud Computing Adoption

Cloud Computing is an increasingly important worldwide development in business service provision. The business benefits of Cloud Computing usage include reduced IT overhead costs, greater flexibility of services, reduced TCO (Total Cost of Ownership), on-demand services, and improved productivity. As a result, Small and Medium-Sized Enterprises (SMEs) are increasingly adopting Cloud Computing technology because of these perceived benefits. The most economical deployment model in Cloud Computing is called the Public Cloud, which is especially suitable for SMEs because it provides almost immediate access to hardware resources and reduces their need to purchase an array of advanced hardware and software applications. The changes experienced in Cloud Computing adoption over the past decade are unprecedented and have raised important issues with regard to privacy, security, trust, and reliability. This chapter presents a conceptual model for Cloud Computing adoption by SMEs in Australia.

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