Biblio

Cloud computing is a new kind of computing model which allows users to effectively rent virtualized computing resources on pay as you go model. It offers many advantages over traditional models in IT industries and healthcare as well. However, there is lack of trust between CSUs and CSPs to prevent the extensive implementation of cloud technologies amongst industries. Different models are developed to overcome the uncertainty and complexity between CSP and CSU regarding suitability. Several researchers focused on resource optimization, scheduling and service dependability in cloud computing by using fuzzy logic. But, data storage and security using fuzzy logic have been ignored. In this paper, a trust evaluation model is proposed for cloud computing security using fuzzy theory. Authors evaluates how fuzzy logic increases efficiency in trust evaluation. To validate the effectiveness of proposed FTEM, authors presents a case study of healthcare organization.

Cloud Computing is considered as a business model for providing IT resources as services through the Internet based on pay-as-you-go principle. These IT resources are provided by Cloud Service Providers (CSPs) and requested by Cloud Service Consumers (CSCs). Selecting the proper CSP to deliver services is a critical and strategic process. According to the work in this paper, a framework for trust management in cloud computing has been introduced. The proposed framework consists of five stages; Filtrating, Trusting, Similarity, Ranking and Monitoring. In the Filtrating stage, the existing CSPs in the system will be filtered based on their parameters. The CSPs trust values are calculated in the Trusting stage. Then, the similarity between the CSC requirements and the CSPs data is calculated in the Similarity stage. The ranking of CSPs will be performed in Ranking stage. According to the Monitoring stage, after finishing the service, the CSC sends his feedbacks about the CSP who delivered the service to be used to monitor this CSP. To evaluate the performance of the proposed framework, a comparative study has been done for the Ranking and Monitoring stages using Armor dataset. According to the comparative results it is found that the proposed framework increases the reliability and performance of the cloud environment.

In service-oriented computing environment (e.g. cloud computing), Cloud Customers (CCs) and Cloud Service Providers (CSPs) require to calculate the trust ranks of impending partner prior to appealing in communications. Determining trustworthiness dynamically is a demanding dilemma in an open and dynamic environment (such as cloud computing) because of many CSPs providing same types of services. Presently, there are very less number of dynamic trust evaluation scheme that permits CCs to evaluate CSPs trustworthiness from multi-dimensional perspectives. Similarly, there is no scheme that permits CSPs to evaluate trustworthiness of CCs. This paper proposes a Multidimensional Dynamic Trust Evaluation Scheme (MDTES) that facilitates CCs to evaluate the trustworthiness of CSPs from various viewpoints. Similar approach can be employed by CSPs to evaluate the trustworthiness of CCs. The proposed MDTES helps CCs to choose trustworthy CSP and to have desired QoS requirements and CSPs to choose desired and legal CCs. The simulation results illustrate the MDTES is dynamic and steady in distinguishing trustworthy and untrustworthy CSPs and CCs.

We consider the scenario where a cloud service provider (CSP) operates multiple geo-distributed datacenters to provide Internet-scale service. Our objective is to minimize the total electricity and bandwidth cost by jointly optimizing electricity procurement from wholesale markets and geographical load balancing (GLB), i.e., dynamically routing workloads to locations with cheaper electricity. Under the ideal setting where exact values of market prices and workloads are given, this problem reduces to a simple linear programming and is easy to solve. However, under the realistic setting where only distributions of these variables are available, the problem unfolds into a non-convex infinite-dimensional one and is challenging to solve. One of our main contributions is to develop an algorithm that is proven to solve the challenging problem optimally, by exploring the full design space of strategic bidding. Trace-driven evaluations corroborate our theoretical results, demonstrate fast convergence of our algorithm, and show that it can reduce the cost for the CSP by up to 20% as compared with baseline alternatives. This paper highlights the intriguing role of uncertainty in workloads and market prices, measured by their variances. While uncertainty in workloads deteriorates the cost-saving performance of joint electricity procurement and GLB, counter-intuitively, uncertainty in market prices can be exploited to achieve a cost reduction even larger than the setting without price uncertainty.

Database outsourcing is one of the important utilities in cloud computing in which the Information Proprietor (IP) transfers the database administration to the Cloud Service Provider (CSP) in order to minimize the administration cost and preservation expenses of the database. Inspite of its immense profit, it undergoes few security issues such as privacy of deployed database and provability of search results. In the recent past, few of the studies have been carried out on provability of search results of Outsourced Database (ODB) that affords correctness and completeness of search results. But in the existing schemes, since there is flow of data between the Information Proprietor and the clients frequently, huge communication cost prevails at the Information Proprietor side. To address this challenge, in this paper we propose Efficient Auditing for Outsourced Database with Token Enforced Cloud Storage (EAODBT). The proposed scheme reduces the large communication cost prevailing at the Information Proprietor side and achieves correctness and completeness of search results even if the mischievous CSP knowingly sends a null set. Experimental analysis show that the proposed scheme has totally reduced the huge communication cost prevailing between Information Proprietor and clients, and simultaneously achieves the correctness and completeness of search results.

Cloud computing has a major role in the development of commercial systems. It enables companies like Microsoft, Amazon, IBM and Google to deliver their services on a large scale to its users. A cloud service provider manages cloud computing based services and applications. For any organization a cloud service provider (CSP) is an entity which works within it. So it suffers from vulnerabilities associated with organization, including internal and external attacks. So its challenge to organization to secure a cloud service provider while providing quality of service. Attribute based encryption can be used to provide data security with Key policy attribute based encryption (KP-ABE) or ciphertext policy attribute based encryption (CP-ABE). But these schemes has lack of scalability and flexibility. Hierarchical CP-ABE scheme is proposed here to provide fine grained access control. Data security is achieved using encryption, authentication and authorization mechanisms. Attribute key generation is proposed for implementing authorization of users. The proposed system is prevented by SQL Injection attack.

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.

It is quite common nowadays for clients to outsource their personal data to a cloud service provider. However, it causes some new challenges in the area of data confidentiality and access control. Attribute-based encryption is a promising solution for providing confidentiality and fine-grained access control in a cloud-based cryptographic system. Moreover, in some cases, to preserve the privacy of clients and data, applying hidden access structures is required. Also, a data owner should be able to update his defined access structure at any time when he is online or not. As in several real-world application scenarios like e-health systems, the anonymity of recipients, and the possibility of updating access structures are two necessary requirements. In this paper, for the first time, we propose an attribute-based access control scheme with hidden access structures enabling the cloud to update access structures on expiry dates defined by a data owner.

Internet of Things is the newfound information architecture based on the Internet that develops interactions between objects and services in a secure and reliable environment. As the availability of many smart devices rises, secure and scalable mass storage systems for aggregate data is required in IoTs applications. In this paper, we propose a new method for storing aggregate data in IoTs by use of ( t, n) -threshold secret sharing scheme in the cloud storage. In this method, original data is divided into t blocks that each block is considered as a share. This method is scalable and traceable, i.e., new data can be inserted or part of original data can be deleted, without changing shares, also cloud service providers' fault in sending invalid shares are detectable.

The biggest challenge of sharing data stored in cloud-storage is privacy-preservation. In this paper, we propose a simple yet effective solution for enforcing the security of private data stored in some cloud storage for sharing. We consider an environment where even if the cloud service provider is not-reliable or is compromised, our data still remain secure. The data Owner encrypts the private files using a secret key, file identifier and hash function and then uploads the cipher text files to the cloud. When a Data user requests access to a file, the owner establishes a key with the user and creates a new key, which is sent to the user. The user can then extract the original key by using the mutually established secret key and use it to decrypt the encrypted file. Thus we propose a system which is computationally simple yet provides a secure mechanism for sharing private data even over an untrusted cloud service provider.

As cloud services greatly facilitate file sharing online, there's been a growing awareness of the security challenges brought by outsourcing data to a third party. Traditionally, the centralized management of cloud service provider brings about safety issues because the third party is only semi-trusted by clients. Besides, it causes trouble for sharing online data conveniently. In this paper, the blockchain technology is utilized for decentralized safety administration and provide more user-friendly service. Apart from that, Ciphertext-Policy Attribute Based Encryption is introduced as an effective tool to realize fine-grained data access control of the stored files. Meanwhile, the security analysis proves the confidentiality and integrity of the data stored in the cloud server. Finally, we evaluate the performance of computation overhead of our system.

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.

Data storage in cloud should come along with high safety and confidentiality. It is accountability of cloud service provider to guarantee the availability and security of client data. There exist various alternatives for storage services but confidentiality and complexity solutions for database as a service are still not satisfactory. Proposed system gives alternative solution for database as a service that integrates benefits of different services along with advance encryption techniques. It yields possibility of applying concurrency on encrypted data. This alternative provides supporting facility to connect dispersed clients with elimination of intermediate proxy by which simplicity can acquired. Performance of proposed system evaluated on basis of theoretical analyses.

Biometric authentication has been extremely popular in large scale industries. The face biometric has been used widely in various applications. Handling large numbers of face images is a challenging task in authentication of biometric system. It requires large amount of secure storage, where the registered user information can be stored. Maintaining centralized data centers to store the information requires high investment and maintenance cost, therefore there is a need for deployment of cloud services. However as there is no guaranty of the security in the cloud, user needs to implement an additional or extra layer of security before storing facial data of all registered users. In this work a unique cloud based biometric authentication system is developed using Microsoft cognitive face API. Because most of the cloud based biometric techniques are scalable it is paramount to implement a security technique which can handle the scalability. Any users can use this system for single enterprise application base over the entire enterprise application. In this work the identification number which is text information associated with each biometric image is protected by AES algorithm. The proposed technique also works under distributed system in order to have wider accessibility. The system is also being extended to validate the registered user with an image of aadhar card. An accuracy of 96% is achieved with 100 registered users face images and aadhar card images. Earlier research carried out for the development of biometric system either suffers from development of distributed system are security aspects to handle multiple biometric information such as facial image and aadhar card image.

Internet-based online cloud services provide enormous volumes of storage space, tailor made computing resources and eradicates the obligation of native machines for data maintenance as well. Cloud storage service providers claim to offer the ability of secure and elastic data-storage services that can adapt to various storage necessities. Most of the security tools have a finite rate of failure, and intrusion comes with more complex and sophisticated techniques; the security failure rates are skyrocketing. Once we upload our data into the cloud, we lose control of our data, which certainly brings new security risks toward integrity and confidentiality of our data. In this paper, we discuss a secure file sharing mechanism for the cloud with the disintegration protocol (DIP). The paper also introduces new contribution of seamless file sharing technique among different clouds without sharing an encryption key.

In the process of big data analysis and processing, a key concern blocking users from storing and processing their data in the cloud is their misgivings about the security and performance of cloud services. There is an urgent need to develop an approach that can help each cloud service provider (CSP) to demonstrate that their infrastructure and service behavior can meet the users' expectations. However, most of the prior research work focused on validating the process compliance of cloud service without an accurate description of the basic service behaviors, and could not measure the security capability. In this paper, we propose a novel approach to verify cloud service security conformance called CloudSec, which reduces the description gap between the cloud provider and customer through modeling cloud service behaviors (CloudBeh Model) and security SLA (SecSLA Model). These models enable a systematic integration of security constraints and service behavior into cloud while using UPPAAL to check the conformance, which can not only check CloudBeh performance metrics conformance, but also verify whether the security constraints meet the SecSLA. The proposed approach is validated through case study and experiments with a cloud storage service based on OpenStack, which illustrates CloudSec approach effectiveness and can be applied in real cloud scenarios.

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.

Cloud computing paradigm is being used because of its low up-front cost. In recent years, even mobile phone users store their data at Cloud. Customer information stored at Cloud needs to be protected against potential intruders as well as cloud service provider. There is threat to the data in transit and data at cloud due to different possible attacks. Organizations are transferring important information to the Cloud that increases concern over security of data. Cryptography is common approach to protect the sensitive information in Cloud. Cryptography involves managing encryption and decryption keys. In this paper, we compare key management methods, apply key management methods to various cloud environments and analyze symmetric key cryptography algorithms.

Today, beyond a legitimate usage, the numerous advantages of cloud computing are exploited by attackers, and Botnets supporting DDoS attacks are among the greatest beneficiaries of this malicious use. Such a phenomena is a major issue since it strongly increases the power of distributed massive attacks while involving the responsibility of cloud service providers that do not own appropriate solutions. In this paper, we present an original approach that enables a source-based de- tection of UDP-flood DDoS attacks based on a distributed system behavior analysis. Based on a principal component analysis, our contribution consists in: (1) defining the involvement of system metrics in a botcoud's behavior, (2) showing the invariability of the factorial space that defines a botcloud activity and (3) among several legitimate activities, using this factorial space to enable a botcloud detection.

Today, cloud networking which is the ability to connect the user with his cloud services and to interconnect these services within an inter-cloud approach, is one of the recent research areas in the cloud computing research communities. The main drawback of cloud networking consists in the lack of Quality of Service (QoS) guarantee and management in conformance with a corresponding Service Level Agreement (SLA). Several research works have been proposed for the SLA establishing in cloud computing, but not in cloud networking. In this paper, we propose an architecture for self-establishing an end-to-end service level agreement between a Cloud Service User (CSU) and a Cloud Service Provider (CSP) in a cloud networking environment. We focus on QoS parameters for NaaS and IaaS services. The architecture ensures a self-establishing of the proposed SLA using autonomic cloud managers.
 

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.

Today, beyond a legitimate usage, the numerous advantages of cloud computing are exploited by attackers, and Botnets supporting DDoS attacks are among the greatest beneficiaries of this malicious use. Such a phenomena is a major issue since it strongly increases the power of distributed massive attacks while involving the responsibility of cloud service providers that do not own appropriate solutions. In this paper, we present an original approach that enables a source-based de- tection of UDP-flood DDoS attacks based on a distributed system behavior analysis. Based on a principal component analysis, our contribution consists in: (1) defining the involvement of system metrics in a botcoud's behavior, (2) showing the invariability of the factorial space that defines a botcloud activity and (3) among several legitimate activities, using this factorial space to enable a botcloud detection.