Biblio

The increased use of cloud services and its various security and privacy challenges such as identity theft, data breach, data integrity and data confidentiality has made trust management, which is one of the most multifaceted aspect in cloud computing, inevitable. The growing reputation of cloud computing technology makes it immensely important to be acquainted with the meaning of trust in the cloud, as well as identify how the customer and the cloud service providers establish that trust. The traditional trust management mechanisms represent a static trust relationship which falls deficit while meeting up the dynamic requirement of cloud services. In this paper, a conceptual zero trust strategy for the cloud environment has been proposed. The model offers a conceptual typology of perceptions and philosophies for establishing trust in cloud services. Further, importance of trust establishment and challenges of trust in cloud computing have also been explored and discussed.

In transient distributed cloud computing environment, software is vulnerable to attack, which leads to software functional completeness, so it is necessary to carry out functional testing. In order to solve the problem of high overhead and high complexity of unsupervised test methods, an intelligent evaluation method for transient analysis software function testing based on active depth learning algorithm is proposed. Firstly, the active deep learning mathematical model of transient analysis software function test is constructed by using association rule mining method, and the correlation dimension characteristics of software function failure are analyzed. Then the reliability of the software is measured by the spectral density distribution method of software functional completeness. The intelligent evaluation model of transient analysis software function testing is established in the transient distributed cloud computing environment, and the function testing and reliability intelligent evaluation are realized. Finally, the performance of the transient analysis software is verified by the simulation experiment. The results show that the accuracy of the software functional integrity positioning is high and the intelligent evaluation of the transient analysis software function testing has a good self-adaptability by using this method to carry out the function test of the transient analysis software. It ensures the safe and reliable operation of the software.

Expected and unexpected risks in cloud computing, which included data security, data segregation, and the lack of control and knowledge, have led to some dilemmas in several fields. Among all of these dilemmas, the privacy problem is even more paramount, which has largely constrained the prevalence and development of cloud computing. There are several privacy protection algorithms proposed nowadays, which generally include two categories, Anonymity algorithm, and differential privacy mechanism. Since many types of research have already focused on the efficiency of the algorithms, few of them emphasized the different orientation and demerits between the two algorithms. Motivated by this emerging research challenge, we have conducted a comprehensive survey on the two popular privacy protection algorithms, namely K-Anonymity Algorithm and Differential Privacy Algorithm. Based on their principles, implementations, and algorithm orientations, we have done the evaluations of these two algorithms. Several expectations and comparisons are also conducted based on the current cloud computing privacy environment and its future requirements.

Most searchable attribute-based encryption schemes only support the search for single-keyword without attribute revocation, the data user cannot quickly detect the validity of the ciphertext returned by the cloud service provider. Therefore, this paper proposes an authorization of searchable CP-ABE scheme with attribute revocation and applies the scheme to the cloud computing environment. The data user to send the authorization information to the authorization server for authorization, assists the data user to effectively detect the ciphertext information returned by the cloud service provider while supporting the revocation of the user attribute in a fine-grained access control structure without updating the key during revocation stage. In the random oracle model based on the calculation of Diffie-Hellman problem, it is proved that the scheme can satisfy the indistinguishability of ciphertext and search trapdoor. Finally, the performance analysis shows that the scheme has higher computational efficiency.

In cloud computing environment, there are malignant nodes which create a huge problem to transfer data in communication. As there are so many models to prevent the data over the network, here we try to prevent or make secure to the network by avoiding mallicious nodes in between the communication. So the probabiliostic approach what we use here is a coherent tool to supervise the security challenges in the cloud environment. The matter of security for cloud computing is a superficial quality of service from cloud service providers. Even, cloud computing dealing everyday with new challenges, which is in process to well investigate. This research work draws the light on aspect regarding with the cloud data transmission and security by identifying the malignanat nodes in between the communication. Cloud computing network shared the common pool of resources like hardware, framework, platforms and security mechanisms. therefore Cloud Computing cache the information and deliver the secure transaction of data, so privacy and security has become the bone of contention which hampers the process to execute safely. To ensure the security of data in cloud environment, we proposed a method by implementing white box cryptography on RSA algorithm and then we work on the network, and find the malignant nodes which hampering the communication by hitting each other in the network. Several existing security models already have been deployed with security attacks. A probabilistic authentication and authorization approach is introduced to overcome this attack easily. It observes corrupted nodes before hitting with maximum probability. here we use a command table to conquer the malignant nodes. then we do the comparative study and it shows the probabilistic authentication and authorization protocol gives the performance much better than the old ones.

In Cloud Computing Environment, using only static security measures didn't mitigate the attack considerably. Hence, deployment of sophisticated methods by the attackers to understand the network topology of complex network makes the task easier. For this reason, the use of dynamic security measure as virtual machine (VM) migration increases uncertainty to locate a virtual machine in a dynamic attack surface. Although this, not all VM's migration enhances security. Indeed, the destination server to host the VM should be selected precisely in order to avoid externality and attack at the same time. In this paper, we model migration in cloud environment by using continuous Markov Chain. Then, we analyze the probability of a VM to be compromised based on the destination server parameters. Finally, we provide some numerical results to show the effectiveness of our approach in term of avoiding intrusion.

The last decade has witnessed a growing interest in exploiting the advantages of Cloud Computing technology. However, the full migration of services and data to the Cloud is still cautious due to the lack of security assurance. Cloud Service Providers (CSPs)are urged to exert the necessary efforts to boost their reputation and improve their trustworthiness. Nevertheless, the uniform implementation of advanced security solutions across all their data centers is not the ideal solution, since customers' security requirements are usually not monolithic. In this paper, we aim at integrating the Cloud security risk into the process of resource provisioning to increase the security of Cloud data centers. First, we propose a quantitative security risk evaluation approach based on the definition of distinct security metrics and configurations adapted to the Cloud Computing environment. Then, the evaluated security risk levels are incorporated into a resource provisioning model in an InterCloud setting. Finally, we adopt two different metaheuristics approaches from the family of evolutionary computation to solve the security risk-aware resource provisioning problem. Simulations show that our model reduces the security risk within the Cloud infrastructure and demonstrate the efficiency and scalability of proposed solutions.

Most of the swarm optimization techniques are inspired by the characteristics as well as behaviour of flock of birds whereas Artificial Bee Colony is based on the foraging characteristics of the bees. However, certain problems which are solved by ABC do not yield desired results in-terms of performance. ABC is a new devised swarm intelligence algorithm and predominately employed for optimization of numerical problems. The main reason for the success of ABC algorithm is that it consists of feature such as fathomable and flexibility when compared to other swarm optimization algorithms and there are many possible applications of ABC. Cloud computing has their limitation in their application and functionality. The cloud computing environment experiences several security issues such as Dos attack, replay attack, flooding attack. In this paper, an effective classifier is proposed based on Artificial Bee Colony for cloud computing. It is evident in the evaluation results that the proposed classifier achieved a higher accuracy rate.

In the cloud computing environment, a growing number of users share their own data files through cloud storage. However, there will be some security and privacy problems due to the reason that the cloud is not completely trusted, so it needs to be resolved by access control. Attribute-based encryption (ABE) and searchable encryption (SE) can solve fine-grained access control. At present, researchers combine the two to propose an attribute-based searchable encryption scheme and achieved remarkable results. Nevertheless, most of existing attribute-based searchable encryption schemes cannot resist online/offline keyword guessing attack. To solve the problem, we present an attribute-based (CP-ABE) searchable encryption scheme that supports trapdoor updating (CSES-TU). In this scheme, the data owner can formulate an access strategy for the encrypted data. Only the attributes of the data user are matched with the strategy can the effective trapdoor be generated and the ciphertext be searched, and that this scheme will update trapdoors at the same time. Even if the keywords are the same, new trapdoors will be generated every time when the keyword is searched, thus minimizing the damage caused by online/offline keyword guessing attack. Finally, the performance of the scheme is analyzed, and the proof of correctness and security are given at the same time.

Now a days, Cloud computing has brought a unbelievable change in companies, organizations, firm and institutions etc. IT industries is advantage with low investment in infrastructure and maintenance with the growth of cloud computing. The Virtualization technique is examine as the big thing in cloud computing. Even though, cloud computing has more benefits; the disadvantage of the cloud computing environment is ensuring security. Security means, the Cloud Service Provider to ensure the basic integrity, availability, privacy, confidentiality, authentication and authorization in data storage, virtual machine security etc. In this paper, we presented a Local outlier factors mechanism, which may be helpful for the detection of Distributed Denial of Service attack in a cloud computing environment. As DDoS attack becomes strong with the passing of time, and then the attack may be reduced, if it is detected at first. So we fully focused on detecting DDoS attack to secure the cloud environment. In addition, our scheme is able to identify their possible sources, giving important clues for cloud computing administrators to spot the outliers. By using WEKA (Waikato Environment for Knowledge Analysis) we have analyzed our scheme with other clustering algorithm on the basis of higher detection rates and lower false alarm rate. DR-LOF would serve as a better DDoS detection tool, which helps to improve security framework in cloud computing.

With the extensive application of cloud computing technology developing, security is of paramount importance in Cloud Computing. In the cloud computing environment, surveys have been provided on several intrusion detection techniques for detecting intrusions. We will summarize some literature surveys of various attack taxonomy, which might cause various threats in cloud environment. Such as attacks in virtual machines, attacks on virtual machine monitor, and attacks in tenant network. Besides, we review massive existing solutions proposed in the literature, such as misuse detection techniques, behavior analysis of network traffic, behavior analysis of programs, virtual machine introspection (VMI) techniques, etc. In addition, we have summarized some innovations in the field of cloud security, such as CloudVMI, data mining techniques, artificial intelligence, and block chain technology, etc. At the same time, our team designed and implemented the prototype system of CloudI (Cloud Introspection). CloudI has characteristics of high security, high performance, high expandability and multiple functions.

In order to improve the efficiency of the existing homomorphic encryption method, based on the DGHV scheme, an improved fully homomorphic scheme over the integer is proposed. Under the premise of ensuring data owner and user data security, the scheme supports the addition and multiplication operations of ciphertext, and ensures faster execution efficiency and meets the security requirements of cloud computing. Security analysis shows that our scheme is safe. Performance assessment demonstrates that our scheme can more efficiently implement data than DGHV scheme.

Along with the growing popularisation of Cloud Computing. Cloud storage technology has been paid more and more attention as an emerging network storage technology which is extended and developed by cloud computing concepts. Cloud computing environment depends on user services such as high-speed storage and retrieval provided by cloud computing system. Meanwhile, data security is an important problem to solve urgently for cloud storage technology. In recent years, There are more and more malicious attacks on cloud storage systems, and cloud storage system of data leaking also frequently occurred. Cloud storage security concerns the user's data security. The purpose of this paper is to achieve data security of cloud storage and to formulate corresponding cloud storage security policy. Those were combined with the results of existing academic research by analyzing the security risks of user data in cloud storage and approach a subject of the relevant security technology, which based on the structural characteristics of cloud storage system.

The Cloud Computing is a developing IT concept that faces some issues, which are slowing down its evolution and adoption by users across the world. The lack of security has been the main concern. Organizations and entities need to ensure, inter alia, the integrity and confidentiality of their outsourced sensible data within a cloud provider server. Solutions have been examined in order to strengthen security models (strong authentication, encryption and fragmentation before storing, access control policies...). More particularly, data remanence is undoubtedly a major threat. How could we be sure that data are, when is requested, truly and appropriately deleted from remote servers? In this paper, we aim to produce a survey about this interesting subject and to address the problem of residual data in a cloud-computing environment, which is characterized by the use of virtual machines instantiated in remote servers owned by a third party.

Separation of network control from devices in Software Defined Network (SDN) allows for centralized implementation and management of security policies in a cloud computing environment. The ease of programmability also makes SDN a great platform implementation of various initiatives that involve application deployment, dynamic topology changes, and decentralized network management in a multi-tenant data center environment. Dynamic change of network topology, or host reconfiguration in such networks might require corresponding changes to the flow rules in the SDN based cloud environment. Verifying adherence of these new flow policies in the environment to the organizational security policies and ensuring a conflict free environment is especially challenging. In this paper, we extend the work on rule conflicts from a traditional environment to an SDN environment, introducing a new classification to describe conflicts stemming from cross-layer conflicts. Our framework ensures that in any SDN based cloud, flow rules do not have conflicts at any layer; thereby ensuring that changes to the environment do not lead to unintended consequences. We demonstrate the correctness, feasibility and scalability of our framework through a proof-of-concept prototype.

An identity authentication scheme is proposed combining with biometric encryption, public key cryptography of homomorphism and predicate encryption technology under the cloud computing environment. Identity authentication scheme is proposed based on the voice and homomorphism technology. The scheme is divided into four stages, register and training template stage, voice login and authentication stage, authorization stage, and audit stage. The results prove the scheme has certain advantages in four aspects.

The term Cloud Computing is not something that appeared overnight, it may come from the time when computer system remotely accessed the applications and services. Cloud computing is Ubiquitous technology and receiving a huge attention in the scientific and industrial community. Cloud computing is ubiquitous, next generation's in-formation technology architecture which offers on-demand access to the network. It is dynamic, virtualized, scalable and pay per use model over internet. In a cloud computing environment, a cloud service provider offers “house of resources” includes applications, data, runtime, middleware, operating system, virtualization, servers, data storage and sharing and networking and tries to take up most of the overhead of client. Cloud computing offers lots of benefits, but the journey of the cloud is not very easy. It has several pitfalls along the road because most of the services are outsourced to third parties with added enough level of risk. Cloud computing is suffering from several issues and one of the most significant is Security, privacy, service availability, confidentiality, integrity, authentication, and compliance. Security is a shared responsibility of both client and service provider and we believe security must be information centric, adaptive, proactive and built in. Cloud computing and its security are emerging study area nowadays. In this paper, we are discussing about data security in cloud at the service provider end and proposing a network storage architecture of data which make sure availability, reliability, scalability and security.

As a new computing mode, cloud computing can provide users with virtualized and scalable web services, which faced with serious security challenges, however. Access control is one of the most important measures to ensure the security of cloud computing. But applying traditional access control model into the Cloud directly could not solve the uncertainty and vulnerability caused by the open conditions of cloud computing. In cloud computing environment, only when the security and reliability of both interaction parties are ensured, data security can be effectively guaranteed during interactions between users and the Cloud. Therefore, building a mutual trust relationship between users and cloud platform is the key to implement new kinds of access control method in cloud computing environment. Combining with Trust Management(TM), a mutual trust based access control (MTBAC) model is proposed in this paper. MTBAC model take both user's behavior trust and cloud services node's credibility into consideration. Trust relationships between users and cloud service nodes are established by mutual trust mechanism. Security problems of access control are solved by implementing MTBAC model into cloud computing environment. Simulation experiments show that MTBAC model can guarantee the interaction between users and cloud service nodes.

The term Cloud Computing is not something that appeared overnight, it may come from the time when computer system remotely accessed the applications and services. Cloud computing is Ubiquitous technology and receiving a huge attention in the scientific and industrial community. Cloud computing is ubiquitous, next generation's in-formation technology architecture which offers on-demand access to the network. It is dynamic, virtualized, scalable and pay per use model over internet. In a cloud computing environment, a cloud service provider offers “house of resources” includes applications, data, runtime, middleware, operating system, virtualization, servers, data storage and sharing and networking and tries to take up most of the overhead of client. Cloud computing offers lots of benefits, but the journey of the cloud is not very easy. It has several pitfalls along the road because most of the services are outsourced to third parties with added enough level of risk. Cloud computing is suffering from several issues and one of the most significant is Security, privacy, service availability, confidentiality, integrity, authentication, and compliance. Security is a shared responsibility of both client and service provider and we believe security must be information centric, adaptive, proactive and built in. Cloud computing and its security are emerging study area nowadays. In this paper, we are discussing about data security in cloud at the service provider end and proposing a network storage architecture of data which make sure availability, reliability, scalability and security.