Anonymity systems are widely used nowadays to protect user identity, but there are various threats currently in the anonymity network, such as virtual private networks, onion routing, and proxy servers. This paper looked at the different anonymity networks that are already out there and proposed a new model to stay anonymous on the internet by using open source tools and methods. This eliminates the current threats. It works by creating a virtual instance on the cloud server and configuring it using open source technologies such as OpenVPN. This model uses elastic cloud computing technology running over existing technologies such as virtual private networks and onion routing. The framework is a new way to stay anonymous on the internet. It is made up of only open source technologies.

To improve the security and reliability of remote terminals under trusted cloud platform, an identity authentication model based on DAA optimization is proposed. By introducing a trusted third-party CA, the scheme issues a cross domain DAA certificate to the trusted platform that needs cross domain authentication. Then, privacy CA isolation measures are taken to improve the security of the platform, so that the authentication scheme can be used for identity authentication when ordinary users log in to the host equipped with TPM chip. Finally, the trusted computing platform environment is established, and the performance load distribution and total performance load of each entity in the DAA protocol in the unit of machine cycle can be acquired through experimental analysis. The results show that the scheme can take into account the requirements of anonymity, time cost and cross domain authentication in the trusted cloud computing platform, and it is a useful supplement and extension to the existing theories of web service security.

Cloud computing has been widely used because of its low price, high reliability, and generality of services. However, considering that cloud computing transactions between users and service providers are usually asynchronous, data privacy involving users and service providers may lead to a crisis of trust, which in turn hinders the expansion of cloud computing applications. In this paper, we propose DPP, a data privacypreserving cloud computing scheme based on homomorphic encryption, which achieves correctness, compatibility, and security. DPP implements data privacy-preserving by introducing homomorphic encryption. To verify the security of DPP, we instantiate DPP based on the Paillier homomorphic encryption scheme and evaluate the performance. The experiment results show that the time-consuming of the key steps in the DPP scheme is reasonable and acceptable.

Face verification is by far the most popular biometrics technology used for authentication since it is noninvasive and does not require the assistance of the user. In contrast, fingerprint and iris identification technologies require the help of a user during the identification process. Now the technology behind facial recognition has been around for years but recently as its grown more sophisticated is applications have expanded greatly. These days a third-party service provider is often hired to perform facial recognition. The sensitivity of face data raises important privacy concerns about outsourcing servers. In order to protect the privacy of users, this paper discusses privacy-preserving face recognition frameworks applied to different networks. In this survey, we focused primarily on the accuracy of face recognition, computation time, and algorithmic approaches to face recognition on edge and cloud-based networks.

Fraud detection is an integral part of financial security monitoring tool; however, the traditional fraud detection method cannot detect the existing malicious fraud, and the clouds will produce data revealing that the risk of fraud detection system can not protect the privacy of detected object, so the fraud detection data privacy security becomes a significant problem,Homomorphic encryption as a demonstrable cryptography cloud privacy computing outsourcing scheme can ensure that cloud computing can perform ciphertext polynomial calculation under the dense state data without direct contact with the accurate data of users, so as to ensure data privacy security. Aiming at the data privacy security problems in the process of fraud detection, this paper combined homomorphic encryption and Logistic regression fraud detection technology to study the Logistic regression fraud detection algorithm under homomorphic ciphertext and constructed a cloud privacy fraud detection method based on customer service and cloud computing services. CKKS encryption scheme is used to encrypt the fraud data set and realize the Logistic regression fraud detection algorithm under ciphertext. The experiment proves that the difference between the fraud detection accuracy on ciphertext and plaintext is less than 3\%. Under the condition of ensuring the privacy of sensitive data to be detected, the effect of the fraud detection model is not affected.

A large number of establishments and organizations implement clouds to store their databases. More active attacks are used on clouds to get unauthorized access or to do harmful actions that may affect on user’s privacy. Therefore, many studies have proposed to increase the level of security in the clouds depended on several strategies. The behavior is one of the promising strategies that might prevent unauthorized or processes. In this paper, a set of features, are from several previous studies, and these features are based on the user activity and events in a special purpose cloud by which unauthorized process can be prevented and alert user about bad actions during his/her work in the cloud environment. The results of comparison show that the event-based features require less resources and time. Thus, they need to be enhanced by adding more informative features, or some available features form other strategies.

Cloud computing performs a significant part in sharing resources and data with other devices via data outsourcing. The data collaboration services, as a potential service given by the cloud service provider (CSP), is to assist the consistency and availability of the shared data amongst users. At the time of sharing resources, it is a complicated process for providing secure writing and access control operations. This study develops a Privacy Preserving Encryption with Optimal Key Generation Technique (PPE-OKGT) for CC environment. The presented PPE-OKGT technique secures the data prior to storing in the cloud sever via encryption process. For accomplishing this, the presented PPE-OKGT technique employs data encryption technology to secure the input data into a hidden format. Besides, in order to improve secrecy, the presented PPE-OKGT technique designs a chaotic search and rescue optimization (CSRO) algorithm for optimal generation of keys. The promising performance of the PPE-OKGT technique can be verified using a set of experimentations. A comprehensive comparison study reported the enhancements of the PPE-OKGT technique over other models.

Cloud computing platforms are the widely used state of the art platforms by various organizations. Data storage and data sharing services are the most widely used services in the cloud, while the maintenance of data integrity is a big challenge. A public cloud platform which is not reliable, users must generate digital signature of their data and then share generated signature for integrity auditing. Any attack on cloud can compromise the users valuable data which is most likely carried out by external entity. By generating signature we can write the rules of who can access update or delete the data. If data is updated by unauthorized user, then auditing can identify which data is compromised. Here we are using asymmetric keys that is when user upload his/her data over cloud then digital signature will get created with users private key, and when TPA (Third Party Auditor) wants to check the integrity of that users data then he can generate digital signature with users public key. Not only carried out low cost for data storage by compressing data but also established data access protocol to maintain data privacy.

To improve the security and reliability of remote terminals under trusted cloud platform, an identity authentication model based on DAA optimization is proposed. By introducing a trusted third-party CA, the scheme issues a cross domain DAA certificate to the trusted platform that needs cross domain authentication. Then, privacy CA isolation measures are taken to improve the security of the platform, so that the authentication scheme can be used for identity authentication when ordinary users log in to the host equipped with TPM chip. Finally, the trusted computing platform environment is established, and the performance load distribution and total performance load of each entity in the DAA protocol in the unit of machine cycle can be acquired through experimental analysis. The results show that the scheme can take into account the requirements of anonymity, time cost and cross domain authentication in the trusted cloud computing platform, and it is a useful supplement and extension to the existing theories of web service security.

In this paper, the electronic structure of selfassembled InGaN/GaN nanowire heterojunctions is investigated. By growing the "T" shaped InGaN/GaN nanowire heterojunction structure, the crystal quality of InGaN was improved, and the phase separation phenomenon of In0.5Ga0.5N nanowires was found. Firstly, it is found that the morphology of GaN self-assembled nanowires is better when the V/III ratio is 9. Then, the morphology and physical properties of InGaN/GaN nanowire heterojunctions with different in compositions were studied. It was found that with the increase of the in composition, the lateral extension of InGaN became serious and the crystal quality deteriorated. A trusted platform module with a similar mechanism but oriented to the cloud environment was proposed, which could monitor the security status of all virtual machines in the virtual group and give Validators provide a view of the trusted state of semiconductor materials.

Fog computing moves computation from the cloud to edge devices to support IoT applications with faster response times and lower bandwidth utilization. IoT users and linked gadgets are at risk to security and privacy breaches because of the high volume of interactions that occur in IoT environments. These features make it very challenging to maintain and quickly share dynamic IoT data. In this method, cloud-fog offers dependable computing for data sharing in a constantly changing IoT system. The extended IoT cloud, which initially offers vertical and horizontal computing architectures, then combines IoT devices, edge, fog, and cloud into a layered infrastructure. The framework and supporting mechanisms are designed to handle trusted computing by utilising a vertical IoT cloud architecture to protect the IoT cloud after the issues have been taken into account. To protect data integrity and information flow for different computing models in the IoT cloud, an integrated data provenance and information management method is selected. The effectiveness of the dynamic scaling mechanism is then contrasted with that of static serving instances.

With the development of information networks, cloud computing, big data, and virtualization technologies promote the emergence of various new network applications to meet the needs of various Internet services. A security protection system for virtual host in cloud computing center is proposed in the article. The system takes "security as a service" as the starting point, takes virtual machines as the core, and takes virtual machine clusters as the unit to provide unified security protection against the borderless characteristics of virtualized computing. The thesis builds a network security protection system for APT attacks; uses the system dynamics method to establish a system capability model, and conducts simulation analysis. The simulation results prove the validity and rationality of the network communication security system framework and modeling analysis method proposed in the thesis. Compared with traditional methods, this method has more comprehensive modeling and analysis elements, and the deduced results are more instructive.

A huge number of cloud users and cloud providers are threatened of security issues by cloud computing adoption. Cloud computing is a hub of virtualization that provides virtualization-based infrastructure over physically connected systems. With the rapid advancement of cloud computing technology, data protection is becoming increasingly necessary. It s important to weigh the advantages and disadvantages of moving to cloud computing when deciding whether to do so. As a result of security and other problems in the cloud, cloud clients need more time to consider transitioning to cloud environments. Cloud computing, like any other technology, faces numerous challenges, especially in terms of cloud security. Many future customers are wary of cloud adoption because of this. Virtualization Technologies facilitates the sharing of recourses among multiple users. Cloud services are protected using various models such as type-I and type-II hypervisors, OS-level, and unikernel virtualization but also offer a variety of security issues. Unfortunately, several attacks have been built in recent years to compromise the hypervisor and take control of all virtual machines running above it. It is extremely difficult to reduce the size of a hypervisor due to the functions it offers. It is not acceptable for a safe device design to include a large hypervisor in the Trusted Computing Base (TCB). Virtualization is used by cloud computing service providers to provide services. However, using these methods entails handing over complete ownership of data to a third party. This paper covers a variety of topics related to virtualization protection, including a summary of various solutions and risk mitigation in VMM (virtual machine monitor). In this paper, we will discuss issues possible with a malicious virtual machine. We will also discuss security precautions that are required to handle malicious behaviors. We notice the issues of investigating malicious behaviors in cloud computing, give the scientific categorization and demonstrate the future headings. We ve identified: i) security specifications for virtualization in Cloud computing, which can be used as a starting point for securing Cloud virtual infrastructure, ii) attacks that can be conducted against Cloud virtual infrastructure, and iii) security solutions to protect the virtualization environment from DDOS attacks.

The world has seen a quick transition from hard devices for local storage to massive virtual data centers, all possible because of cloud storage technology. Businesses have grown to be scalable, meeting consumer demands on every turn. Cloud computing has transforming the way we do business making IT more efficient and cost effective that leads to new types of cybercrimes. Securing the data in cloud is a challenging task. Cloud security is a mixture of art and science. Art is to create your own technique and technologies in such a way that the user should be authenticated. Science is because you have to come up with ways of securing your application. Data security refers to a broad set of policies, technologies and controls deployed to protect data application and the associated infrastructure of cloud computing. It ensures that the data has not been accessed by any unauthorized person. Cloud storage systems are considered to be a network of distributed data centers which typically uses cloud computing technologies like virtualization and offers some kind of interface for storing data. Virtualization is the process of grouping the physical storage from multiple network storage devices so that it looks like a single storage device.

Cloud computing has since been turned into the most transcendental growth. This creative invention provides forms of technology and software assistance to companies. Cloud computing is a crucial concept for the distribution of information on the internet. Virtualization is a focal point for supporting cloud resources sharing. The secrecy of data management is the essential warning for the assurance of computer security such that cloud processing will not have effective privacy safety. All subtleties of information relocation to cloud stay escaped the clients. In this review, the effective mobility techniques for privacy and secured cloud computing have been studied to support the infrastructure as service.

With the rapid development of Internet of Things technology, the requirements for edge node data processing capability are increasing, and GPU processors are becoming more widely applied in edge nodes. Current research on GPU virtualization technology mainly focuses on cloud data centers, with little research on embedded GPU virtualization in scenarios with limited edge node resources. In contrast to cloud data centers, embedded GPUs in edge nodes typically do not have access to GPU utilization and video memory usage within each container. As a result, traditional GPU virtualization technologies are ineffective for resource virtualization on embedded devices. This paper presents a method to virtualize embedded GPU resources in an edge computing environment, called sGPU. We integrated edge nodes with embedded GPUs into Kubernetes via the device-plugin mechanism. Users can package GPU applications in containers and deploy them using Kubernetes on edge nodes with embedded GPUs. sGPU allows containers to share embedded GPU computing resources and divides a physical GPU into multiple virtual GPUs that can be allocated to containers on demand. To achieve GPU computing power division, we proposed a multi-container sharing GPU algorithm and implemented it in sGPU, which ensures the most accurate computing power segmentation under the competition of computing resources of a GPU used by multiple containers at the same time. According to the experimental results, the average overhead of sGPU is 3.28\%. The accuracy of computing power segmentation is 92.7\% when a single container uses GPU.

The 5G technology ensures reliable and affordable broadband access worldwide, increases user mobility, and assures reliable and affordable connectivity of a wide range of electronic devices such as the Internet of Things (IoT).SDN (Software Defined Networking), NFV ( Network Function Virtualization), and cloud computing are three technologies that every technology provider or technology enabler tries to incorporate into their products to capitalize on the useability of the 5th generation.The emergence of 5G networks and services expands the range of security threats and leads to many challenges in terms of user privacy and security. The purpose of this research paper is to define the security challenges and threats associated with implementing this technology, particularly those affecting user privacy. This research paper will discuss some solutions related to the challenges that occur when implementing 5G, and also will provide some guidance for further development and implementation of a secure 5G system.

The incredible speed with which Information Technology (IT) has evolved in recent decades has brought about a major change in people s daily lives and in practically all areas of knowledge. The diversification of means of access using mobile devices, the evolution of technologies such as virtualization, added to a growing demand from users for new systems and services adapted to these new market trends, were the fuel for the emergence of a new paradigm, Cloud Computing. The general objective of this paper is to enable the offer of privacy preservation system provided by third parties through which Cloud Data Storage Services customers can continuously monitor the integrity of their files.

In the era of big data, more and more applications of smart devices are computing-intensive, thus raising the strong demand for task offloading to cloud data centers. However, it gives rise to network delay and privacy data leak issues. Edge computing can effectively solve latency, bandwidth occupation and data privacy problems, but the deployment of applications are also limited by hardware architectures and resources, i.e., computing and storage resources. Therefore, the combination of virtualization technology and edge computing become important in order to realize the rapid deployment of intelligent application in an edge server or an edge node by virtualization technology. The traditional virtual machine (VM) is no longer suitable for resource-constrained devices. Container technique including Docker can effectively solve these problems, but it also depends on an operating system. Unikernel is the state-of-art virtualization technology. In this paper, we combine Unikernel with edge computing to explore its application in an edge computing system. An application architecture of edge computing based on Unikernel is proposed. It is suitable for application in edge computing.

By analyzing the design requirements of a secure desktop virtualization information system, this paper proposes the security virtualization technology of "whitelist" security mechanism, the virtualization layer security technology of optimized design, and the virtual machine security technology of resource and network layer isolation. On this basis, this paper constructs the overall architecture of the secure desktop virtualization information system. This paper studies the desktop virtualization technology research based on VMware using VMware server virtualization solution to transform and upgrade the traditional intelligent desktop virtualization system, improve server resource utilization rate, and reduce operation and maintenance costs.

The experimental results demonstrated that, With the development of cloud computing, more and more people use cloud computing to do all kinds of things. However, for cloud computing, the most important thing is to ensure the stability of user data and improve security at the same time. From an analysis of the experimental results, it can be found that Cloud computing makes extensive use of technical means such as computing virtualization, storage system virtualization and network system virtualization, abstracts the underlying physical facilities into external unified interfaces, maps several virtual networks with different topologies to the underlying infrastructure, and provides differentiated services for external users. By comparing and analyzing the experimental results, it is clear that virtualization technology will be the main way to solve cloud computing security. Virtualization technology introduces a virtual layer between software and hardware, provides an independent running environment for applications, shields the dynamics, distribution and differences of hardware platforms, supports the sharing and reuse of hardware resources, provides each user with an independent and isolated computer environment, and facilitates the efficient and dynamic management and maintenance of software and hardware resources of the whole system. Applying virtualization technology to cloud security reduces the hardware cost and management cost of "cloud security" enterprises to a certain extent, and improves the security of "cloud security" technology to a certain extent. This paper will outline the basic cloud computing security methods, and focus on the analysis of virtualization cloud security technology.

Cloud computing is a cutting-edge innovation that will improve the design of applications in terms of elasticity, functionality, and collaborative execution. It is a computer system that mainly depends on the Internet. The most important feature of cloud computing is virtualization, which enables on-site dynamic allocation of academic computing resources or industrial resources. Virtualization can be defined as "forming a virtual version of something, such as a server, desktop, storage device, operating system, or network resource," according to Wikipedia. The goal of this study is to demonstrate how virtualization can contribute to the improvement of cloud computing services. This study also takes a deeper look at source virtualization strategies, as well as emerging security challenges and future research goals.

Wearables Security 2022 - In the twenty-first century, given the worldwide situation, the first concern of any female is her personal protection. Women Labor Day and night to sustain themselves and their families. These women are more susceptible to attacks and assaults, and their security and safety are paramount issues. This technique proposed several new goods to safeguard women. Among the products that may be employed is a smart jacket for women s safety. The proposed approach also includes features to send alert notification to family members with Geo location live tracking and live camera video streaming placed on the jacket for the emergency attention when women are not secure. This gadget is an appeal to all women to earn the right to a safe and secure planet.

Quantum Computing Security 2022 - Cloud computing has turned into an important technology of our time. It has drawn attention due to its, availability, dynamicity, elasticity and pay as per use pricing mechanism this made multiple organizations to shift onto the cloud platform. It leverages the cloud to reduce administrative and backup overhead. Cloud computing offers a lot of versatility. Quantum technology, on the other hand, advances at a breakneck pace. Experts anticipate a positive outcome and predict that within the next decade, powerful quantum computers will be available. This has and will have a substantial impact on various sciences streams such as cryptography, medical research, and much more. Sourcing applications for business and informational data to the cloud, presents privacy and security concerns, which have become crucial in cloud installation and services adoption. To address the current security weaknesses, researchers and impacted organizations have offered several security techniques in the literature. The literature also gives a thorough examination of cloud computing security and privacy concerns.

Provenance 2022 - The Function-as-a-Service cloud computing paradigm has made large-scale application development convenient and efficient as developers no longer need to deploy or manage the necessary infrastructure themselves. However, as a consequence of this abstraction, developers lose insight into how their code is executed and data is processed. Cloud providers currently offer little to no assurance of the integrity of customer data. One approach to robust data integrity verification is the analysis of data provenance—logs that describe the causal history of data, applications, users, and non-person entities. This paper introduces ProProv, a new domain-specific language and graphical user interface for specifying policies over provenance metadata to automate provenance analyses.