A Data Security Framework for Cloud Computing Services

Cyberattacks are difficult to prevent because the targeted companies and organizations are often relying on new and fundamentally insecure cloudbased technologies,such as the Internet of Things.With increasing industry adoption and migration of traditional computing services to the cloud,one of the main challenges in cybersecurity is to provide mechanisms to secure these technologies.This work proposes a Data Security Framework for cloud computing services(CCS)that evaluates and improves CCS data security from a software engineering perspective by evaluating the levels of security within the cloud computing paradigm using engineering methods and techniques applied to CCS.This framework is developed by means of a methodology based on a heuristic theory that incorporates knowledge generated by existing works as well as the experience of their implementation.The paper presents the design details of the framework,which consists of three stages:identification of data security requirements,management of data security risks and evaluation of data security performance in CCS.

Intelligent Solution System for Cloud Security Based on Equity Distribution:Model and Algorithms

In the cloud environment,ensuring a high level of data security is in high demand.Data planning storage optimization is part of the whole security process in the cloud environment.It enables data security by avoiding the risk of data loss and data overlapping.The development of data flow scheduling approaches in the cloud environment taking security parameters into account is insufficient.In our work,we propose a data scheduling model for the cloud environment.Themodel is made up of three parts that together help dispatch user data flow to the appropriate cloudVMs.The first component is the Collector Agent whichmust periodically collect information on the state of the network links.The second one is the monitoring agent which must then analyze,classify,and make a decision on the state of the link and finally transmit this information to the scheduler.The third one is the scheduler who must consider previous information to transfer user data,including fair distribution and reliable paths.It should be noted that each part of the proposedmodel requires the development of its algorithms.In this article,we are interested in the development of data transfer algorithms,including fairness distribution with the consideration of a stable link state.These algorithms are based on the grouping of transmitted files and the iterative method.The proposed algorithms showthe performances to obtain an approximate solution to the studied problem which is an NP-hard(Non-Polynomial solution)problem.The experimental results show that the best algorithm is the half-grouped minimum excluding(HME),with a percentage of 91.3%,an average deviation of 0.042,and an execution time of 0.001 s.

Hybrid Prairie Dog and Beluga Whale Optimization Algorithm for Multi-Objective Load Balanced-Task Scheduling in Cloud Computing Environments

The cloud computing technology is utilized for achieving resource utilization of remotebased virtual computer to facilitate the consumers with rapid and accurate massive data services.It utilizes on-demand resource provisioning,but the necessitated constraints of rapid turnaround time,minimal execution cost,high rate of resource utilization and limited makespan transforms the Load Balancing(LB)process-based Task Scheduling(TS)problem into an NP-hard optimization issue.In this paper,Hybrid Prairie Dog and Beluga Whale Optimization Algorithm(HPDBWOA)is propounded for precise mapping of tasks to virtual machines with the due objective of addressing the dynamic nature of cloud environment.This capability of HPDBWOA helps in decreasing the SLA violations and Makespan with optimal resource management.It is modelled as a scheduling strategy which utilizes the merits of PDOA and BWOA for attaining reactive decisions making with respect to the process of assigning the tasks to virtual resources by considering their priorities into account.It addresses the problem of pre-convergence with wellbalanced exploration and exploitation to attain necessitated Quality of Service(QoS)for minimizing the waiting time incurred during TS process.It further balanced exploration and exploitation rates for reducing the makespan during the task allocation with complete awareness of VM state.The results of the proposed HPDBWOA confirmed minimized energy utilization of 32.18% and reduced cost of 28.94% better than approaches used for investigation.The statistical investigation of the proposed HPDBWOA conducted using ANOVA confirmed its efficacy over the benchmarked systems in terms of throughput,system,and response time.

Cloud Computing: Purpose and Future

Cloud computing is the new norm within business entities as businesses try to keep up with technological advancements and user needs. The concept is defined as a computing environment allowing for remote outsourcing of storage and computing resources. A hybrid cloud environment is an excellent example of cloud computing. Specifically, the hybrid system provides organizations with increased scalability and control over their data and support for a remote workforce. However, hybrid cloud systems are expensive as organizations operate different infrastructures while introducing complexity to the organization’s activities. Data security is critical among the most vital concerns that have resulted from the use of cloud computing, thus, affecting the rate of user adoption and acceptance. This article, borrowing from the hybrid cloud computing system, recommends combining traditional and modern data security systems. Traditional data security systems have proven effective in their respective roles, with the main challenge arising from their recognition of context and connectivity. Therefore, integrating traditional and modern designs is recommended to enhance effectiveness, context, connectivity, and efficiency.

Secure and Efficient Outsourced Computation in Cloud Computing Environments

Secure and efficient outsourced computation in cloud computing environments is crucial for ensuring data confidentiality, integrity, and resource optimization. In this research, we propose novel algorithms and methodologies to address these challenges. Through a series of experiments, we evaluate the performance, security, and efficiency of the proposed algorithms in real-world cloud environments. Our results demonstrate the effectiveness of homomorphic encryption-based secure computation, secure multiparty computation, and trusted execution environment-based approaches in mitigating security threats while ensuring efficient resource utilization. Specifically, our homomorphic encryption-based algorithm exhibits encryption times ranging from 20 to 1000 milliseconds and decryption times ranging from 25 to 1250 milliseconds for payload sizes varying from 100 KB to 5000 KB. Furthermore, our comparative analysis against state-of-the-art solutions reveals the strengths of our proposed algorithms in terms of security guarantees, encryption overhead, and communication latency.

A Novel LSB Steganography Technique for Enhancing Cloud Security

Steganography is a technique that is frequently used to hide hidden information in multimedia artifacts including music, video, and images. In order to protect data saved in the cloud, this paper presents a steganography method for encrypting sound utilizing LSB-based computation. By using the least significant bit (LSB) of a byte to represent a message and then substituting each LSB bit with a binary message and encrypting a significant quantity of data. The proposed system uses the LSB technique of picture steganography, Multi-Level Encryption Algorithm (MLEA) and Two-Level Encryption Algorithm (TLEA) data encryption to give the highest level of cloud security. Compared to other current schemes, the performance of the suggested method is 1.732125% better on average.

Quantum-Edge Cloud Computing for IoT: Bridging the Gap between Cloud, Edge, and Quantum Technologies

The rapid expansion of the Internet of Things (IoT) has driven the need for advanced computational frameworks capable of handling the complex data processing and security challenges that modern IoT applications demand. However, traditional cloud computing frameworks face significant latency, scalability, and security issues. Quantum-Edge Cloud Computing (QECC) offers an innovative solution by integrating the computational power of quantum computing with the low-latency advantages of edge computing and the scalability of cloud computing resources. This study is grounded in an extensive literature review, performance improvements, and metrics data from Bangladesh, focusing on smart city infrastructure, healthcare monitoring, and the industrial IoT sector. The discussion covers vital elements, including integrating quantum cryptography to enhance data security, the critical role of edge computing in reducing response times, and cloud computing’s ability to support large-scale IoT networks with its extensive resources. Through case studies such as the application of quantum sensors in autonomous vehicles, the practical impact of QECC is demonstrated. Additionally, the paper outlines future research opportunities, including developing quantum-resistant encryption techniques and optimizing quantum algorithms for edge computing. The convergence of these technologies in QECC has the potential to overcome the current limitations of IoT frameworks, setting a new standard for future IoT applications.

QoS-Constrained,Reliable and Energy-Efficient Task Deployment in Cloud Computing

Reliability,QoS and energy consumption are three important concerns of cloud service providers.Most of the current research on reliable task deployment in cloud computing focuses on only one or two of the three concerns.However,these three factors have intrinsic trade-off relationships.The existing studies show that load concentration can reduce the number of servers and hence save energy.In this paper,we deal with the problem of reliable task deployment in data centers,with the goal of minimizing the number of servers used in cloud data centers under the constraint that the job execution deadline can be met upon single server failure.We propose a QoS-Constrained,Reliable and Energy-efficient task replica deployment(QSRE)algorithm for the problem by combining task replication and re-execution.For each task in a job that cannot finish executing by re-execution within deadline,we initiate two replicas for the task:main task and task replica.Each main task runs on an individual server.The associated task replica is deployed on a backup server and completes part of the whole task load before the main task failure.Different from the main tasks,multiple task replicas can be allocated to the same backup server to reduce the energy consumption of cloud data centers by minimizing the number of servers required for running the task replicas.Specifically,QSRE assigns the task replicas with the longest and the shortest execution time to the backup servers in turn,such that the task replicas can meet the QoS-specified job execution deadline under the main task failure.We conduct experiments through simulations.The experimental results show that QSRE can effectively reduce the number of servers used,while ensuring the reliability and QoS of job execution.

Toward Cloud Computing QoS Architecture:Analysis of Cloud Systems and Cloud Services

Cloud can be defined as a new computing paradigm that provides scalable, on-demand, and virtualized resources for users. In this style of computing, users can access a shared pool of computing resources which are provisioned with minimal management efforts of users. Yet there are some obstacles and concerns about the use of clouds. Guaranteeing quality of service QoS by service providers can be regarded as one of the main concerns for companies tending to use it. Service provisioning in clouds is based on service level agreements representing a contract negotiated between users and providers. According to this contract, if a provider cannot satisfy its agreed application requirements, it should pay penalties as compensation. In this paper, we intend to carry out a comprehensive survey on the models proposed in literature with respect to the implementation principles to address the QoS guarantee issue. © 2014 Chinese Association of Automation.

Service Security Architecture and Access Control Model for Cloud Computing

Security is a key problem for the development of Cloud Computing. A common service security architecture is a basic abstract to support security research work. The authorization ability in the service security faces more complex and variable users and environment. Based on the multidimensional views, the service security architecture is described on three dimensions of service security requirement integrating security attributes and service layers. An attribute-based dynamic access control model is presented to detail the relationships among subjects, objects, roles, attributes, context and extra factors further. The model uses dynamic control policies to support the multiple roles and flexible authority. At last, access control and policies execution mechanism were studied as the implementation suggestion.

Research on cloud computing and services framework of marine environmental information management

Based on the features of marine environmental data and processing requirements, a cloud computing archi- tecture of marine environment information is proposed, which provides a new cloud technology framework for the integration and sharing of marine environmental information resources. A physical layer, software platform layer and an application layer are illustrated systematically, at the same time, a corresponding solu- tions for many difficult technical problems such as parallel query processing of multi-dimensional, spatio- temporal information, data slice storage, software service flow customization, analysis, reorganization and so on. A prototype system is developed and many different data-size experiments and a comparative analy- sis are done based on it. The experiment results show that the cloud platform based on this framework can achieve high performance and scalability when dealing with large-scale marine data.

Information Flow Security Models for Cloud Computing

Cloud computing provides services to users through Internet.This open mode not only facilitates the access by users,but also brings potential security risks.In cloud computing,the risk of data leakage exists between users and virtual machines.Whether direct or indirect data leakage,it can be regarded as illegal information flow.Methods,such as access control models can control the information flow,but not the covert information flow.Therefore,it needs to use the noninterference models to detect the existence of illegal information flow in cloud computing architecture.Typical noninterference models are not suitable to certificate information flow in cloud computing architecture.In this paper,we propose several information flow models for cloud architecture.One model is for transitive cloud computing architecture.The others are for intransitive cloud computing architecture.When concurrent access actions execute in the cloud architecture,we want that security domain and security domain do not affect each other,that there is no information flow between security domains.But in fact,there will be more or less indirect information flow between security domains.Our models are concerned with how much information is allowed to flow.For example,in the CIP model,the other domain can learn the sequence of actions.But in the CTA model,the other domain can’t learn the information.Which security model will be used in an architecture depends on the security requirements for that architecture.

An Effective QoS-Constrained Scheduling Scheme for Cloud Computing Services

Cloud computing is becoming a hot topic of the information industry in recent years. Many companies provide the cloud services, such as Google Apps and Apple multimedia services. In general, by applying the virtulization technologies, the data center is built for cloud computing to provide users with the eomputing and storage resources, as well as the software environment. Thus, the quality of service （QoS） must be considered to satisfy users＇ requirements. This paper proposes a high efficiency scheduling scheme for supporting cloud computing. The virtual machine migration technique has been applied to the proposed scheduling scheme for improving the resources utilization and satisfying the QoS requirement of users. The experimental results show that in addition to satisfying the QoS requirement of users, the proposed scheme can improve the resources utilization effectively.

Security analysis and improvement on resilient storage outsourcing schemes in mobile cloud computing

The resilient storage outsourcing schemes in mobile cloud computing are analyzed. It is pointed out that the sharing-based scheme （ShS） has vulnerabilities regarding confidentiality and integrity; meanwhile, the coding-based scheme （COS） and the encryption-based scheme （EnS） have vulnerabilities on integrity. The corresponding attacks on these vulnerabilities are given. Then, the improved protocols such as the secure sharing-based protocol （SShP）, the secure coding-based protocol （SCoP） and the secure encryption- based protocol （SEnP）, are proposed to overcome these vulnerabilities. The core elements are protected through public key encryptions and digital signatures. Security analyses show that the confidentiality and the integrity of the improved protocols are guaranteed. Meanwhile, the improved protocols can keep the frame of the former schemes and have higher security. The simulation results illustrate that compared with the existing protocols, the communication overhead of the improved protocols is not significantly increased.

Analysis of Hot Topics in Cloud Computing

In the field of cloud computing, topics such as computing resource virtualization, differences between grid and cloud computing, relationship between high-performance computers and cloud computing centers, and cloud security and standards have attracted much research interest. This paper analyzes these topics and highlights that resource virtualization allows information services to be scalable, intensive, and specialized; grid computing involves using many computers for large-scale computing tasks, while cloud computing uses one platform for multiple services; high-performance computers may not be suitable for a cloud computing; security in cloud computing focuses on trust management between service suppliers and users; and based on the existing standards, standardization of cloud computing should focus on interoperability between services.

A Cloud Computing Security Assessment Framework for Small and Medium Enterprises

Cloud computing plays a very important role in the development of business and competitive edge for many organisations including SMEs (Small and Medium Enterprises). Every cloud user continues to expect maximum service, and a critical aspect to this is cloud security which is one among other specific challenges hindering adoption of the cloud technologies. The absence of appropriate, standardised and self-assessing security frameworks of the cloud world for SMEs becomes an endless problem in developing countries and can expose the cloud computing model to major security risks which threaten its potential success within the country. This research presents a security framework for assessing security in the cloud environment based on the Goal Question Metrics methodology. The developed framework produces a security index that describes the security level accomplished by an evaluated cloud computing environment thereby providing the first line of defence. This research has concluded with an eight-step framework that could be employed by SMEs to assess the information security in the cloud. The most important feature of the developed security framework is to devise a mechanism through which SMEs can have a path of improvement along with understanding of the current security level and defining desired state in terms of security metric value.

Representing Increasing Virtual Machine Security Strategy in Cloud Computing Computations

This paper proposes algorithm for Increasing Virtual Machine Security Strategy in Cloud Computing computations.Imbalance between load and energy has been one of the disadvantages of old methods in providing server and hosting,so that if two virtual severs be active on a host and energy load be more on a host,it would allocated the energy of other hosts(virtual host)to itself to stay steady and this option usually leads to hardware overflow errors and users dissatisfaction.This problem has been removed in methods based on cloud processing but not perfectly,therefore,providing an algorithm not only will implement a suitable security background but also it will suitably divide energy consumption and load balancing among virtual severs.The proposed algorithm is compared with several previously proposed Security Strategy including SC-PSSF,PSSF and DEEAC.Comparisons show that the proposed method offers high performance computing,efficiency and consumes lower energy in the network.

An Evolution, Present, and Future Changes of Cloud Computing Services

This study presents a clear evolution of computing and its key applications. Cloud computing services evolved from distributed, grid, and utility computing. Critical companies such as Salesforce,Amazon, Google, and Microsoft play important roles in cloud computing. Dramatic changes in the technology environment have created new challenges for current information technologies. This study discusses four significant challenges for cloud computing services,including the next-generation Internet, data synchronization, cloud security, and competitive advantages.And then it also discusses how managers can learn about the future of cloud computing services.

Towards Developing Privacy-Preserved Data Security Approach(PP-DSA)in Cloud Computing Environment

In the present scenario of rapid growth in cloud computing models,several companies and users started to share their data on cloud servers.However,when the model is not completely trusted,the data owners face several security-related problems,such as user privacy breaches,data disclosure,data corruption,and so on,during the process of data outsourcing.For addressing and handling the security-related issues on Cloud,several models were proposed.With that concern,this paper develops a Privacy-Preserved Data Security Approach(PP-DSA)to provide the data security and data integrity for the out-sourcing data in Cloud Environment.Privacy preservation is ensured in this work with the Efficient Authentication Technique(EAT)using the Group Signature method that is applied with Third-Party Auditor(TPA).The role of the auditor is to secure the data and guarantee shared data integrity.Additionally,the Cloud Service Provider(CSP)and Data User(DU)can also be the attackers that are to be handled with the EAT.Here,the major objective of the work is to enhance cloud security and thereby,increase Quality of Service(QoS).The results are evaluated based on the model effectiveness,security,and reliability and show that the proposed model provides better results than existing works.

Safeguarding Cloud Computing Infrastructure:A Security Analysis

Cloud computing is the provision of hosted resources,comprising software,hardware and processing over the World Wide Web.The advantages of rapid deployment,versatility,low expenses and scalability have led to the widespread use of cloud computing across organizations of all sizes,mostly as a component of the combination/multi-cloud infrastructure structure.While cloud storage offers significant benefits as well as cost-effective alternatives for IT management and expansion,new opportunities and challenges in the context of security vulnerabilities are emerging in this domain.Cloud security,also recognized as cloud computing security,refers to a collection of policies,regulations,systematic processes that function together to secure cloud infrastructure systems.These security procedures are designed to safeguard cloud data,to facilitate regulatory enforcement and to preserve the confidentiality of consumers,as well as to lay down encryption rules for specific devices and applications.This study presents an overview of the innovative cloud computing and security challenges that exist at different levels of cloud infrastructure.In this league,the present research work would be a significant contribution in reducing the security attacks on cloud computing so as to provide sustainable and secure services.