A Pattern-Based and Tool-Supported Risk Analysis Method Compliant to ISO 27001 for Cloud Systems

Emerging of cloud computing with flexibility, improve accessing data, and cost-saving makes this technology accessible and growing fast. As a result of the emergence of cloud computing bring interest to industries to used cloud computing. Although cloud computing brings so many benefits to customers, the previous study reveals that cloud computing penetration in the Healthcare area is still low. With effective cloud risk assessment methodology will gain the confidence to cloud users in this technology. Study in cloud risk assessment methodology still infant and the complexity in identifying security risk still debating. This paper explores the risk assessment process by highlighting the method in the risk evaluation process. Risk evaluation is an essential phase in the risk assessment process. It compares the result from the risk analysis process and determines whether to accept or tolerate the risk criteria to decide on the risk analysis. In this study, the Nominal Group Technique (NGT) is introduced to compare risk analysis results in the earlier phase. Since risk evaluation based on organizational objectives, external and internal context and stakeholders' views, NGT is promising for effective results. This study not only contributing to the prioritizing list of risks and threats in a systematical manner but indirectly NGT process makes stakeholders aware of the current cloud security risk situation in the organization. Equal opportunity expressing views in this focus group discussion is hope can generate a brilliant solution in risk assessment results.

Models, modelling and modellers: an application to risk analysis

The SAFE FOODS Risk Analysis Framework suitable for GMOs? A case study

For accepting clouds and using cloud services by companies, security plays a decisive role. For cloud providers, one way to obtain customers’ confidence is to establish security mechanisms when using clouds. The ISO 27001 standard provides general concepts for establishing information security in an organization. Risk analysis is an essential part in the ISO 27001 standard for achieving information security. This standard, however, contains ambiguous descriptions. In addition, it does not stipulate any method to identify assets, threats, and vulnerabilities. In this paper, we present a structured and patternbased method to conduct risk analysis for cloud computing systems. It is tailored to SMEs. Our method addresses the requirements of the ISO 27001. We make use of the cloud system analysis pattern, security requirement patterns, threat patterns, and control patterns for conducting the risk analysis. The method is illustrated by a cloud logistics application example.

Risk analysis is, at best, a good general-purpose yardstick by which we can judge our security design's effectiveness. Because roughly 50 percent of security problems are the result of design flaws, performing a risk analysis at the design level is an important part of a solid software security program. Taking the trouble to apply risk-analysis methods at the design level for any application often yields valuable, business-relevant results. The risk analysis process is continuous and applies to many different levels, at once identifying system-level vulnerabilities, assigning probability arid impact, arid determining reasonable mitigation strategies. The paper looks at how, by considering the resulting ranked risks, business stakeholders can determine how to manage particular risks and what the most cost-effective controls might be.

In cloud computing, a cloud user pays proportionally to the amount of the consumed resources (bandwidth, memory, and CPU cycles etc.). We posit that such a cloud computing system is vulnerable to DDoS (Distributed Denial-of-Service) attacks against quota. Attackers can force a cloud user to pay more and more money by exhausting its quota without crippling its execution system or congesting links. In this paper, we address this issue and claim that cloud should enable users to pay only for their admitted traffic. We design and prototype such a charging model in a CoreLab testbed infrastructure and show an example application.

Cloud computing (CC) has many benefits, so its use has spread rapidly, particularly in the business sector. An important consideration in the acceptance of CC is whether the CC system is dependable, and it can differ among industry and service type. However, little research has considered the effect of dependability (composed of availability, reliability, security, maintainability) on CC acceptance. Especially, group comparisons between high IT-intensive (Hi-ITi) and low IT-intensive (Lo-ITi) industries have not been reported, nor have comparisons between software-as-a-service (SaaS) and platform-as-a-service (PaaS)/infrastructure-as-a-service (IaaS). This study aims to explore how the dependability of CC affects users’ intent to accept it, with focus on how this intent is affected by intensity of IT use (by industry) and by the type of CC service used. To validate the proposed model, this study applied structural equation modeling and conducted multi-group analysis. A total of 230 business managers in South Korea represent the sample for our study. For the full dataset, the three dependability attributes (availability, reliability, security) do not affect the usefulness of CC, but do affect the ease of use of CC. The usefulness of CC is a determinant for positive intention to accept CC, whereas the ease of use of CC is not. Maintainability is the strongest determinant of CC adoption for the full dataset, and for all individual groups, except those that use SaaS. For Hi-ITi and Lo-ITi industries, results show that managers show no differences in their perceptions of the effect of dependability attributes (availability, reliability, security) on the usefulness and the ease of CC. The absence of such a difference in managers’ perception also applies to the relationship between two core variables of TAM (i.e., perceived usefulness, perceived ease of use) and behavioral intention to accept CC. For SaaS and PaaS/IaaS, managers have different perceptions of security on the usefulness of CC, and the effect of the usefulness of CC on the intention to accept CC. The findings can provide academic researchers and industry practitioners with a differentiated and in-depth perspective on the understanding and the spread of CC.

Global trade in ornamental fish from an Australian perspective: The case for revised import risk analysis and management strategies

A key feature of risk analysis is that risk assessment and risk management should be functionally separated. However, the usefulness of a risk assessment may be limited if the output is not designed to help with risk management decisions. The COMRISK project investigated the communication between risk assessors and risk managers. The overall goal of the project was to identify current practices and challenges in communication between risk assessors and risk managers during the risk analysis process, and thus increase and improve the understanding and the quality of the communication between them. Specific actions to achieve this aim included reviewing of historical food safety cases, analysing risk assessment requests, identifying communication guiding documents, including legislation and agreements, conducting semi-structured interviews with risk assessors and risk managers, and identifying tools for facilitating the communication between risk assessors and risk managers. It was concluded that the usefulness of a risk assessment is strongly dependent on well-defined and mutually recognised risk questions and that scarce or poor communication between risk assessors and risk managers is one of the major reasons when an output from risk assessment fails to support risk management. The communication between risk assessors and risk managers preceding the onset of the risk assessment, when the risk assessment requests with its risk questions are defined, is especially identified as one of the critical points to ensure a risk assessment that is fit for purpose. However, difficulties in understanding were also reported for the communication between risk assessors and risk managers during and after the risk assessment. Lack of communication is seldom a result of formal constraints or agreements nor can it be explained by a wish of the risk assessors or risk managers. Instead, perceived constraints or traditions appear to be possible underlying factors leading to scarce or poor communication between risk assessors and risk managers. It is essential that both risk assessors and risk managers acknowledge the crucial importance of communication between them while at the same time respect their different roles in a risk analysis.According to respondents, the best solution to facilitate the framing of the risk assessment questions isan open dialogue between risk assessors and risk managers to agree on the goal of the assessment and to build trust. Further, the interviewresults indicate that a formal systematic process may facilitate communication during the risk analysis. Where there is uncertainty, e.g due to data gaps or issues related to the methodology and models, it should be acknowledged and described properly by risk assessors to risk managers. Training of risk assessors and risk managers may improve the possibility of a timely and fit-for-purpose output.Such a training should give a deeper insight in the risk management process, give a better understanding of the risk managers role, and especially raise the awareness of the importance of the communication between risk assessors and risk managers.To improve the risk analysis process, it is also important that the risk assessor gets feedback regarding how risk assessments have met the needs of the risk managers.The present study also found that aspects of risk communication studied in this project are not extensively discussed in the guidance documents for risk analysis. More research is needed to identify the barriers for a fit for purpose communication.

Preface. 1 LNG Properties and Overview of Hazards. 1.1 LNG Properties. 1.2 Hazards of LNG with Respect to Public Risk. 1.3 Risk Analysis Requires Adequate Modeling. 1.4 Flammability. 1.5 Regulations in Siting Onshore LNG Import Terminals. 1.6 Regulation for Siting Offshore LNG Import Terminals. 1.7 Controversial Claims of LNG Opponents. 2 LNG Incidents and Marine History. 2.1 LNG Ship Design History. 2.2 Designs and Issues First Commercial LNG Ships. 2.3 LNG Trade History. 2.4 LNG Accident History. 2.5 Summary of LNG History and Relevant Technical Developments. 3 Current LNG Carriers. 3.1 Design Requirements. 3.2 Membrane Tanks. 3.3 Moss Spheres. 4 Risk Analysis and Risk Reduction. 4.1 Background. 4.2 Risk Analysis Process. 4.3 Frequency: Data Sources and Analysis. 4.4 Frequency: Predictive Methods. 4.5 Consequence Modeling. 4.6 Ignition Probability. 4.7 Risk Results. 4.8 Special Issues Terrorism. 4.9 Risk Reduction and Mitigation Measures for LNG. 5 LNG Discharge on Water. 5.1 Type 1 Above Water Breaches at Sea. 5.2 Type 2 At Waterline Breaches at Sea. 5.3 Type 3 Below Waterline Breaches at Sea. 5.4 Discharges from Ship's Pipework. 5.5 Cascading Failures at Sea. 5.6 Initial Discharge Rate. 5.7 Time-Dependent Discharge (Blowdown). 5.8 Vacuum Breaking and Glug-Glug Effects. 6 Risk Analysis for Onshore Terminals and Transport. 6.1 Typical Basis for LNG Receiving Terminal. 6.2 Features of LNG Receiving Terminals. 6.3 Standards for Receiving Terminal Design. 6.4 U.S. Guidelines and Regulations for Receiving Terminals. 6.5 European Regulations for LNG Receiving Terminals. 6.6 Empirical Formula for Required Land Area of Terminal. 6.7 Leak in Loading Arm or in Storage Tank. 6.8 Rollover. 6.9 LNG Land Transport Risk. 6.10 Offshore LNG Terminals. 7 LNG Pool Modeling. 7.1 Flashing and Droplet Evaporation in Jet Flow. 7.2 Pool Spread and Evaporation Modeling. 7.3 Rapid Phase Transition Explosions. 7.4 Aerosol Drop Size. 7.5 Heat Balance Terms to LNG Pool. 7.6 Nomenclature. 8 Vapor Cloud Dispersion Modeling. 8.1 Atmospheric Transport Processes. 8.2 Model Types. 8.3 LNG Dispersion Test Series. 8.4 Factors Affecting Plume Length. 8.5 Effect of Wind, Currents, and Waves on LNG Plume. 8.6 Comparison of Dispersion Model Predictions. 8.7 Descriptions of Dispersion Test Series. 8.8 Vapor Intrusion Indoors. 8.9 Theoretical Basis for Suppression of Turbulence. 9 LNG Pool Fire Modeling. 9.1 Types of Fires from LNG Facilities. 9.2 The Challenge for Pool Fire Modeling. 9.3 Pool Fire Characteristics. 9.4 Summary of LNG Fire Experiments. 9.5 Burning Rate Data and Correlations From Fire Tests. 9.6 Point Source Fire Model. 9.7 Solid Flame Models: Flame Length Correlations. 9.8 Flame Tilt Correlations. 9.9 Flame Drag Near Pools. 9.10 Sep Correlations and Smoke Shielding. 9.11 Atmospheric Transmissivity. 9.12 Trench Fires. 9.13 View Factors. 9.14 CFD Modeling. 9.15 Comparison of Model Predictions. 9.16 Fire Engulfment of LNG Carrier. 10 Other LNG Hazards. 10.1 Fire and Explosion Scenarios. 10.2 Jet Fires. 10.3 Flash Fires. 10.4 BLEVEs, Fireballs. 10.5 LNG Vapor Cloud Explosions. 10.6 Asphyxiation and Cryogenic Hazard from LNG Spills. 11 Fire Effects. 11.1 Fire Radiation Effects on Individuals. 11.2 Effects of Thermal Radiation on Property. 12 Research Needs. 12.1 Uncertainties. 12.2 Recommendations of GAO Survey. 12.3 LNG Model Evaluation Protocols (MEPs). 12.4 Special Topics. 12.5 Conclusions. References. Index.

<p>Development of a globally integrated framework, intended for implementation in a private on-premise cloud computing framework, structurally based on virtualization technologies, cloud computing, encryption, high availability and redundancy systems, data protection systems, governance, active steering, network monitoring systems, risk analysis and physical infrastructure protection.</p>

High energy consumption is one of the key issues of cloud computing systems. Incoming jobs in cloud computing environments have the nature of randomness, and compute nodes have to be powered on all the time to await incoming tasks. This results in a great waste of energy. An energy-saving task scheduling algorithm based on the vacation queuing model for cloud computing systems is proposed in this paper. First, we use the vacation queuing model with exhaustive service to model the task schedule of a heterogeneous cloud computing system. Next, based on the busy period and busy cycle under steady state, we analyze the expectations of task sojourn time and energy consumption of compute nodes in the heterogeneous cloud computing system. Subsequently, we propose a task scheduling algorithm based on similar tasks to reduce the energy consumption. Simulation results show that the proposed algorithm can reduce the energy consumption of the cloud computing system effectively while meeting the task performance.

With the constant development of socialist modernization construction in our country, our country's computer information technology has made effective progress, and makes the world into an information age. People's production and life style experience a series of change. However, with the emergence of information diversity and multi-user mode, traditional computer information technology already can't satisfy people's needs, and the development and application of cloud computing technology come to the stage. This article focuses on analyzing the big data user behavior engine design under cloud computing technology, covering big data flow management, multi-user system design, and other aspects to explore the effect of the system test. In recent years, China's mobile Internet technology has made full development, which makes the Internet operators in our country face a new development opportunity and began from traffic management to flow management. The law of user behavior is analyzed to explore the real demand of market and the users. In order to fully meet the changing needs of users, operators must constantly develop and launch new products and strengthen the function of computer technology. Cloud computing technology is such kind of engine system which can satisfy the analysis and processing of huge amounts of data. RESEARCH ON CLOUD COMPUTING SYSTEM OVERALL DESIGN The overall architecture of cloud computing system This study mainly uses cloud computing technology’s huge amounts of data computing to set up complete mobile Internet data mining analysis system. Realize the analysis for Internet user behavior engine, and according to the user's preferences online habits and behavior, provide users with targeted personalized service and form a unified organic whole of data collection, analysis and service type and marketing strategy to improve enterprise's marketing efficiency. In addition, cloud computing system mainly realizes data collection with the help of FTP server, and makes distributed computing and data batch processing at the system interface. Large data shall be deposited in Hbase database. The system can not only realize mass data storage, but those unstructured data storage. Then through Hive integration layer and summary EIL processing, use MapReduce data analysis model to transmit the processing result into the database. The system’s overall structure is shown in Figure 1: 3rd International Conference on Materials Engineering, Manufacturing Technology and Control (ICMEMTC 2016) © 2016. The authors Published by Atlantis Press 1351 Figure 1 The overall architecture of cloud computing system System topology and function distribution System topology mainly refers that a server is taken as Hapdoop platform’s master node server, and the others are Hapdoop platform’s node servers. In general, node server can be dynamically extended according to the actual need, and the master node server not only assigns tasks and flow to node server, but also monitors the work execution of the node server. More than one node server participates to complete the task, and it can improve data processing efficiency. The master node server’s software running status is shown in Figure 2: Figure 2 Master node server function structure

Deep neural networks in the cloud: Review, applications, challenges and research directions

Cloud computing has different meaning to different people, the privacy and security issues also differ between a consumer using a public cloud application, a medium-sized Company using a customized Design of business on a cloud platform, and Some Companies are using Platform on Public level which are Public to Public Network The security requirements in cloud computing environment is to find the Security threats in the Structure of clouds To find the security solutions, and finding basis so that Pre Security Step Should be taken in concerned with security future model. In this paper is to build a trusted computing environment for cloud computing system by Combining the trusted computing platform into cloud computing system Which is free from attacks and threats and system is designed with a model system in which cloud computing system is combined with trusted computing platform and trusted platform models. Keywords: cloud computing, data breaches, Api Attack Deniel Attack, Account high Jacking, Deniel of Services