Biblio

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

As an important pillar of social informatization, e-government not only provides more convenient services for the public, but also effectively improves administrative efficiency. At the same time, the application of cloud computing technology also urgently requires the government to improve the level of digital construction. This paper proposes the concept of e-government based on cloud computing, analyze the possible hidden dangers that cloud computing brings to e-government in management, technology, and security, and build cloud computing e-government information security system from three aspects: cloud security management, cloud security technology, and cloud security assurance.

Cloud computing is becoming a demanding technology due to its flexibility, sensibility and remote accessibility. Apart from these applications of cloud computing, privacy and security are two terms that pose a circumstantial discussion. Various authors have argued on this topic that cloud computing is more secure than other data sharing and storing methods. The conventional data storing system is a computer system or smartphone storage. The argument debate also states that cloud computing is vulnerable to enormous types of attacks which make it a more concerning technology. This current study has also tried to draw the circumstantial and controversial debate on the security and privacy system of cloud computing. Primary research has been conducted with 65 cloud computing experts to understand whether a cloud computing security technique is highly secure or not. An online survey has been conducted with them where they provided their opinions based on the security and privacy system of cloud computing. Findings showed that no particular technology is available which can provide maximum security. Although the respondents agreed that blockchain is a more secure cloud computing technology; however, the blockchain also has certain threats which need to be addressed. The study has found essential encryption systems that can be integrated to strengthen security; however, continuous improvement is required.

Cloud security has become a serious challenge due to increasing number of attacks day-by-day. Intrusion Detection System (IDS) requires an efficient security model for improving security in the cloud. This paper proposes a game theory based model, named as Game Theory Cloud Security Deep Neural Network (GT-CSDNN) for security in cloud. The proposed model works with the Deep Neural Network (DNN) for classification of attack and normal data. The performance of the proposed model is evaluated with CICIDS-2018 dataset. The dataset is normalized and optimal points about normal and attack data are evaluated based on the Improved Whale Algorithm (IWA). The simulation results show that the proposed model exhibits improved performance as compared with existing techniques in terms of accuracy, precision, F-score, area under the curve, False Positive Rate (FPR) and detection rate.

With the gradual construction and implementation of cloud computing, the information security problem of the smart grid has surfaced. Therefore, in the construction of the smart grid cloud computing platform, information security needs to be considered in planning, infrastructure, and management at the same time, and it is imminent to build an information network that is secure from terminal to the platform to data. This paper introduces the concept of cloud security technology and the latest development of cloud security technology and discusses the main strategies of cloud security construction in electric power enterprises.

A unified cloud management platform is the key to efficient and secure management of cloud computing resources. To improve the operation effect of the power cloud service platform, power companies can use the micro-service architecture technology to carry out data processing, information integration, and innovative functional architecture of the power cloud service platform, realize the optimal design of the power cloud service platform and improve the power cloud service platform-security service quality. According to the technical requirements of the power cloud security management platform, this paper designs the technical architecture of the power unified cloud security management platform and expounds on the functional characteristics of the cloud security management platform to verify the feasibility and effectiveness of the cloud security management platform.

Cloud Computing (CC) has emerged as an on-demand accessible tool in different practical applications such as digital industry, academics, manufacturing, health sector and others. In this paper different security threats faced by CC are discussed with suitable examples. Moreover, an artificial intelligence based security enabled CC is also discussed based on suitable empirical data. It is found that an artificial neural network (ANN) is an effective system to detect the level of risk factors associated with CC along with mitigating those risk issues with appropriate algorithms. Hence, it provides a desired level of protection against cyber attacks, internal confidential threats and external threat of data theft from a cloud computing system. Levenberg–Marquardt (LMBP) algorithms are also found as a significant tool to estimate the level of security performance around a cloud computing system. ANN is used to improve the performance level of data security across a cloud computing network and make it security enabled to ensure a protected data transmission to clients associated with the system.

Trusted Platform Modules (TPM) have grown to be crucial safeguards from the number of software-based strikes. By giving a restricted range of cryptographic providers by way of a well-defined user interface, divided as a result of the program itself, TPM and Infrastructure as a service (IaaS) can function as a root of loyalty so when a foundation aimed at advanced equal protection methods. This information studies the works aimed at uses on TPM within the cloud computing atmosphere, by journal times composed somewhere among 2013 as well as 2020. It identifies the present fashion as well as goals from these technologies within the cloud, as well as the kind of risks that it mitigates. The primary investigation is being focused on the TPM's association to the IaaS security based on the authorization and the enabling schema for integrity. Since integrity measurement is among the key uses of TPM and IaaS, particular focus is given towards the evaluation of operating period phases as well as S/W levels it's put on to. Finally, the deep survey on recent schemes can be applied on Cloud Environment.

Cloud computing has become ubiquitous in the modern world and has offered a number of promising and transformative technological opportunities. However, organizations that use cloud platforms are also concerned about cloud security and new threats that arise due to cloud adoption. Digital forensic investigations (DFI) are undertaken when a security incident (i.e., successful attack) has been identified. Forensics data collection is an integral part of DFIs. This paper presents results from a survey of existing literature on challenges related to forensics data collection in cloud. A taxonomy of major challenges was developed to help organizations understand and thus better prepare for forensics data collection.

Data security and privacy have become an important problem while big data systems are growing dramatically fast in various application fields. Paillier additive homomorphic cryptosystem is widely used in information security fields such as big data security, communication security, cloud computing security, and artificial intelligence security. However, how to improve its computational performance is one of the most critical problems in practice. In this paper, we propose two modifications to improve the performance of the Paillier cryptosystem. Firstly, we introduce a key generation method to generate the private key with low Hamming weight, and this can be used to accelerate the decryption computation of the Paillier cryptosystem. Secondly, we propose an acceleration method based on Hensel lifting in the Paillier cryptosystem. This method can obtain a faster and improved decryption process by showing the mathematical analysis of the decryption algorithm.

The cloud infrastructure is not new to the society from past one decade. But even in recent time, the companies started migrating from local services to cloud services for better connectivity and for other requirements, this is due to companies financial limitations on existing infrastructure, they are migrating to less cost and hire and fire support based cloud infrastructures. But the proposed cloud infrastructure require security on event logs accessed by different end users on the cloud environment. To adopt the security on local services to cloud service based infrastructure, it need better identify management between end users. Therefore this paper presents the related works of user identity as a service for each user involving in cloud service and the accessing permission and protection will be monitored and controlled by the cloud security infrastructures.

Cloud computing has changed how humans use their technological expertise. It indicates a transition in the use of computers as utilitarian instruments with radical applications in general. However, as technology advances, the number of hazards increases and crucial data protection has become increasingly challenging due to extensive internet use. Every day, new encryption methods are developed, and much research is carried out in the search for a reliable cryptographic algorithm. The AES algorithm employs an overly simplistic algebraic structure. Each block employs the same encryption scheme, and AES is subject to brute force and MITM attacks. AES have not provide d sufficient levels of security; the re is still a need to put further le vels of protection over them. In this regard, DNA cryptography allows you to encrypt a large quantity of data using only a few amount of DNA. This paper combines two methodologies, a DNA-based algorithm and the AES Algorithm, to provide a consi derably more secure data security platform. The DNA cryptography technology and the AES approach are utilized for data encryption and decryption. To improve cloud security, DNA cryptography and AES provide a technologically ideal option.

Cloud storage, in general, is a collection of Computer Technology resources provided to consumers over the internet on a leased basis. Cloud storage has several advantages, including simplicity, reliability, scalability, convergence, and cost savings. One of the most significant impediments to cloud computing's growth is security. This paper proposes a security approach based on cloud security. Cloud security now plays a critical part in everyone's life. Due to security concerns, data is shared between cloud service providers and other users. In order to protect the data from unwanted access, the Security Service Algorithm (SSA), which is called as MONcrypt is used to secure the information. This methodology is established on the obfuscation of data techniques. The MONcrypt SSA is a Security as a Service (SaaS) product. When compared to current obfuscation strategies, the proposed methodology offers a better efficiency and smart protection. In contrast to the current method, MONcrypt eliminates the different dimensions of information that are uploaded to cloud storage. The proposed approach not only preserves the data's secrecy but also decreases the size of the plaintext. The exi sting method does not reduce the size of data until it has been obfuscated. The findings show that the recommended MONcrypt offers optimal protection for the data stored in the cloud within the shortest amount of time. The proposed protocol ensures the confidentiality of the information while reducing the plaintext size. Current techniques should not reduce the size of evidence once it has been muddled. Based on the findings, it is clear that the proposed MONcrypt provides the highest level of protection in the shortest amount of time for rethought data.

With the development of cloud computing technology, cloud services have been used by more and more traditional applications and products because of their unique advantages such as virtualization, high scalability and universality. In the cloud computing environment, computer networks often encounter security problems such as external attacks, hidden dangers in the network and hidden dangers in information sharing. The network security level protection system is the basic system of national network security work, which is the fundamental guarantee for promoting the healthy development of informatization and safeguarding national security, social order and public interests. This paper studies cloud computing security from the perspective of level protection, combining with the characteristics of cloud computing security. This scheme is not only an extension of information system level protection, but also a study of cloud computing security, aiming at cloud computing security control from the perspective of level protection.

Cloud computing is a modern computing mode based on network, which is widely participated by the public, and provides virtualized dynamic computing resources in the form of services. Cloud computing builds an effective communication platform with the help of computer internet, so that users can get the same computing resources even if they are in different areas. With its unique technical characteristics and advantages, cloud computing has been deployed to practical applications more and more, and the consequent security problems of cloud computing have become increasingly prominent. In addition to the original cloud computing environment, this paper proposes to build a secure cloud with cloud technology, deploy security agents in the business cloud, connect the business cloud, security cloud and security agents through SDN (software defined network) technology, and dynamically divide the business cloud into logically isolated business areas through security agents. Therefore, security is separated from the specific implementation technology and deployment scheme of business cloud, and an information security protection scheme under cloud computing environment is proposed according to the characteristics of various factors, so as to enhance the security of network information.

This paper is focused on the topic of the use of biometrics framework and strategy for secure access identity management of cloud computing services. This paper present's a description of cloud computing security issues and explored a review of previous works that represented various ideas for a cloud access framework. This paper discusses threats like a malicious insider, data breaches, and describes ways to protect them. It describes an innovative way portrayed a framework that fingerprint access-based authentication to protect Cloud services from unauthorized access and DOS, DDoS attacks. This biometrics-based framework as an extra layer of protection, added then it can be robust to prevent unauthorized access to cloud services.

Most cyber-attacks and data breaches in cloud infrastructure are due to human errors and misconfiguration vulnerabilities. Cloud customer-centric tools are imperative for mitigating these issues, however existing cloud security models are largely unable to tackle these security challenges. Therefore, novel security mechanisms are imperative, we propose Risk-driven Fault Injection (RDFI) techniques to address these challenges. RDFI applies the principles of chaos engineering to cloud security and leverages feedback loops to execute, monitor, analyze and plan security fault injection campaigns, based on a knowledge-base. The knowledge-base consists of fault models designed from secure baselines, cloud security best practices and observations derived during iterative fault injection campaigns. These observations are helpful for identifying vulnerabilities while verifying the correctness of security attributes (integrity, confidentiality and availability). Furthermore, RDFI proactively supports risk analysis and security hardening efforts by sharing security information with security mechanisms. We have designed and implemented the RDFI strategies including various chaos engineering algorithms as a software tool: CloudStrike. Several evaluations have been conducted with CloudStrike against infrastructure deployed on two major public cloud infrastructure: Amazon Web Services and Google Cloud Platform. The time performance linearly increases, proportional to increasing attack rates. Also, the analysis of vulnerabilities detected via security fault injection has been used to harden the security of cloud resources to demonstrate the effectiveness of the security information provided by CloudStrike. Therefore, we opine that our approaches are suitable for overcoming contemporary cloud security issues.

Lightweight virtualization represented by container technology provides a virtual environment for cloud services with more flexibility and efficiency due to the kernel-sharing property. However, the shared kernel also means that the system isolation mechanisms are incomplete. Attackers can scan the shared system configuration files to explore vulnerabilities for launching attacks. Previous works mainly eliminate the problem by fixing operating systems or using access control policies, but these methods require significant modifications and cannot meet the security needs of individual containers accurately. In this paper, we present ConfigRand, a moving target defense framework to prevent the information leakages due to the shared kernel in the container-based cloud. The ConfigRand deploys deceptive system configurations for each container, bounding the scan of attackers aimed at the shared kernel. In design of ConfigRand, we (1) propose a framework applying the moving target defense philosophy to periodically generate, distribute, and deploy the deceptive system configurations in the container-based cloud; (2) establish a model to formalize these configurations and quantify their heterogeneity; (3) present a configuration movement strategy to evaluate and optimize the variation of configurations. The results show that ConfigRand can effectively prevent the information leakages due to the shared kernel and apply to typical container applications with minimal system modification and performance degradation.

Cloud computing has made the life of individual users and work of business corporations so much easier by providing them data storage services at very low costs. Individual users can store and access their data through shared cloud storage service anywhere anytime. Similarly, business corporation consumers of cloud computing can store, manage, process and access their big data with quite an ease. However, the security and privacy of users' data remains vulnerable in cloud computing Availability, integrity and confidentiality are the three primary elements that users consider before signing up for cloud computing services. Many public and private cloud services have experienced security breaches and unauthorized access incidents. This paper suggests user end cryptography of data before uploading it to a cloud storage service platform like Google Drive, Microsoft, Amazon and CloudSim etc. The proposed cryptography algorithm is based on symmetric key cryptography model and has been implemented on Amazon S3 cloud space service.

Cloud provides a low maintenance and affordable storage to various applications and users. The data owner allows the cloud users to access the documents placed in the cloud service provider based on the user's access control vector provided to the cloud users by the data owners. In such type of scenarios, the confidentiality of the documents exchanged between the cloud service provider and the users should be maintained. The existing approaches used to provide this facility are not computation and communication efficient for performing key updating in the data owner side and the key recovery in the user side. This paper discusses the key management services provided to the cloud users. Remote key management and client-side key management are two approaches used by cloud servers. This paper also aims to discuss the method for destroying the encryption/decryption group keys for shared data to securing the data after deletion. Crypto Shredding or Crypto Throw technique is deployed for the same.

At present, cloud computing technology has made outstanding contributions to the Internet in data unification and sharing applications. However, the problem of information security in cloud computing environment has to be paid attention to and effective measures have to be taken to solve it. In order to control the data security under cloud services, the DS evidence theory method is introduced. The trust management mechanism is established from the source of big data, and a cloud computing security assessment model is constructed to achieve the quantifiable analysis purpose of cloud computing security assessment. Through the simulation, the innovative way of quantifying the confidence criterion through big data trust management and DS evidence theory not only regulates the data credible quantification mechanism under cloud computing, but also improves the effectiveness of cloud computing security assessment, providing a friendly service support platform for subsequent cloud computing service.

The majority of security breaches in cloud infrastructure in recent years are caused by human errors and misconfigured resources. Novel security models are imperative to overcome these issues. Such models must be customer-centric, continuous, not focused on traditional security paradigms like intrusion detection and adopt proactive techniques. Thus, this paper proposes CloudStrike, a cloud security system that implements the principles of Chaos Engineering to enable the aforementioned properties. Chaos Engineering is an emerging discipline employed to prevent non-security failures in cloud infrastructure via Fault Injection Testing techniques. CloudStrike employs similar techniques with a focus on injecting failures that impact security i.e. integrity, confidentiality and availability. Essentially, CloudStrike leverages the relationship between dependability and security models. Preliminary experiments provide insightful and prospective results.

Pervasive systems over the years continuous to grow exponentially. Engagement of IoT in fields such as Agriculture, Home automation, industrial applications etc is on the rise. Self organizing networks within the IoT field give rise to engagement of various nodes for data communication. The rise in Cyber-attacks within IoT pose a lot of threat to these connected nodes and hence there is a need for data passing through nodes to be verified during communication. In this paper we proposed a nodal authentication approach in IoT using blockchain in securing the integrity of data passing through the nodes in IoT. In our work, we engaged the GOST algorithm in our approach. At the end, we achieved a nodal authentication and verification of the transmitted data. This makes it very difficult for an attacker to fake a node in the communication chain of the connected nodes. Data integrity was achieved in the nodes during the communication.

Cryptographically cloud computing may be an innovative safe cloud computing design. Cloud computing may be a huge size dispersed computing model that ambitious by the economy of the level. It integrates a group of inattentive virtualized animatedly scalable and managed possessions like computing control storage space platform and services. External end users will approach to resources over the net victimization fatal particularly mobile terminals, Cloud's architecture structures are advances in on-demand new trends. That are the belongings are animatedly assigned to a user per his request and hand over when the task is finished. So, this paper projected biometric coding to boost the confidentiality in Cloud computing for biometric knowledge. Also, this paper mentioned virtualization for Cloud computing also as statistics coding. Indeed, this paper overviewed the safety weaknesses of Cloud computing and the way biometric coding will improve the confidentiality in Cloud computing atmosphere. Excluding this confidentiality is increased in Cloud computing by victimization biometric coding for biometric knowledge. The novel approach of biometric coding is to reinforce the biometric knowledge confidentiality in Cloud computing. Implementation of identification mechanism can take the security of information and access management in the cloud to a higher level. This section discusses, however, a projected statistics system with relation to alternative recognition systems to date is a lot of advantageous and result oriented as a result of it does not work on presumptions: it's distinctive and provides quick and contact less authentication. Thus, this paper reviews the new discipline techniques accustomed to defend methodology encrypted info in passing remote cloud storage.

Multi-Writer Searchable Encryption, also known as public-key encryption with keyword search(PEKS), serves a wide spectrum of data sharing applications. It allows users to search over encrypted data encrypted via different keys. However, most of the existing PEKS schemes are built on classic security assumptions, which are proven to be untenable to overcome the threats of quantum computers. To address the above problem, in this paper, we propose a lattice-based searchable encryption scheme from the learning with errors (LWE) hardness assumption. Specifically, we observe that the keys of each user in a basic scheme are composed of large-sized matrices and basis of the lattice. To reduce the complexity of key management, our scheme is designed to enable users to directly use their identity for data encryption. We present several optimization techniques for implementation to make our design nearly practical. For completeness, we conduct rigorous security, complexity, and parameter analysis on our scheme, and perform comprehensive evaluations at a commodity machine. With a scenario of 100 users, the cost of key generation for each user is 125s, and the cost of searching a document with 1000 keywords is 13.4ms.