Collaborative-Based Dynamic Trust Model for Bring-Your-Own-Device Access Control Management in Cloud Environment

As the bring your own device (BYOD) to work trend grows, so do the network security risks. This fast-growing trend has huge benefits for both employees and employers. With malware, spyware and other malicious downloads, tricking their way onto personal devices, organizations need to consider their information security policies. Malicious programs can download onto a personal device without a user even knowing. This can have disastrous results for both an organization and the personal device. When this happens, it risks BYODs making unauthorized changes to policies and leaking sensitive information into the public domain. A privacy breach can cause a domino effect with huge financial and legal implications, and loss of productivity for organizations. This is a difficult challenge. Organizations need to consider user privacy and rights together with protecting networks from attacks. This paper evaluates a new architectural framework to control the risks that challenge organizations and the use of BYODs. After analysis of large volumes of research, the previous studies addressed single issues. We integrated parts of these single solutions into a new framework to develop a complete solution for access control. With too many organizations failing to implement and enforce adequate security policies, the process needs to be simpler. This framework reduces system restrictions while enforcing access control policies for BYOD and cloud environments using an independent platform. Primary results of the study are positive with the framework reducing access control issues.

The Cloud Computing (CC) is an Internet-based technology which offers a shared pool of highly available, virtualized, dynamically scalable, and configurable computing resources (e.g., networks, servers, computing power, storage, applications, data, services, etc.). In the CC, the authentication as well as trust and reputation of the cloud users and service provider is a critical issue for the security of the cloud. Lots of articles previously present different trust models, but unfortunately, these trust models are not suitable for all cases as the trust is a non-measurable and subjective parameter that differs person to person. The trust involves many multi-dimensional factors such as evidence, reputation, expectations, feedback, history, risk, motivation, session behaviours, and so on. To addresses the above-mentioned issues, the paper present a novel multi-dimensional trust and reputation calculation model for the cloud computing, in which we integrate multiple trust factors that increase the novelty of the model. Additionally, we dynamically assign a weight for each trust and reputation factor using the Weighted Moving Average and Ordered Weighted Averaging (WMA-OWA) combination algorithm. The proposed model overcome the issues of the previous existing models. The detail presentation and analysis of the model shows that the model is appropriate and accurate for trust calculation in the cloud.

JCDC: A blockchain-based framework for secure data storage and circulation in JointCloud

Cloud Service Providers supply services to clients in terms of their demands. They need to be constantly under monitoring for their services with respect to consensus agreements between clients and service providers. A Third Party Auditor or TPA as a trusted organization appears to be necessary to monitor executing agreements of cloud services. Using a third party as an extra component creates cost overheads for clients in a cloud environment. Thus, introducing a cost efficient framework for a cloud environment which includes a third party is an eminent achievement to make a TPA feasible and practical in cloud environments. In this paper, we propose a TPA framework for monitoring service level agreements between cloud service providers and cloud clients using several cloud resources. This framework employs different types of service deployments from various cloud service providers excluding the cloud service provider which is being monitored. Then, we demonstrate that the framework can mitigate costs of a third party auditor in a cloud environment. Simulations of trends for costs exhibits cost efficiency of at least forty percent over ten years when a TPA follows our proposed framework in comparison to other frameworks. Finally, we provide an analysis to compare characteristics of our framework with other frameworks and discuss the advantages of our proposed framework. Our results indicate that TPA as a component of the framework not only reduces overall costs of its presentation in a cloud environment but additionally improves management efficiency and security.

Cloud computing has transformed traditional IT infrastructure, offering dynamic, configurable resources on demand.On the other hand, it brings unique cybersecurity challenges, particularly in protecting sensitive data from unauthorized access.Traditional single factor authentication does not address these risks.By implementing multi-factor authentication (MFA), which combines several factors for verification including password, tokens, and biometrics, this cloud security method has become increasingly popular.Existing authentication methods fall short in the cloud environment, so this paper presents a novel multi-factor, multi-layered cloud access authentication framework.The methodology for MFA implementation uses risk-adaptive authentication based on real-time risk assessment, adaptive policy for MFA selection, and seamless verification workflows for end-users.Moreover, the implementation of the advanced technologies that cover all aspects such as encryption, SSO, and adaptive authentication further safeguards it against evolving threats.Through experimental analyses, we show that the framework is effective to substantially reduce the vulnerabilities without compromising usability and scalability.This will help cloud service providers and organizations alike better equip themselves with an effective and agile security environment through the adoption of next generation MFA strategies.

Cloud Security is still considered one of the main factors inhibiting the diffusion of the Cloud Computing paradigm. Potential Cloud Service Customers (CSCs) do not trust delegating every kind of resources and data to external Cloud Service Providers (CSPs). The problem grows in complexity due to the increasing adoption of complex supply chains: CSPs that offer Sofware-as-a-Service (SaaS) cloud services often do not have their own data centers, but just acquire resources and services from other CSPs. This makes ithard, if not impossible, to ascribe the responsibility of a securityincident. A possible solution is the adoption of Security ServiceLevel Agreements (SLAs): CSPs should deliver services withan SLA that details each guarantee offered in terms of security, and CSCs should be able to compare offerings from differentCSPs and verify that SLAs are respected during service lifecycle. This paper shows how it is possible to build up a per-serviceSecurity SLA in a chain of cloud services, proposing asolution based on a security evaluation technique to comparedifferent cloud service supply chains based on their SecuritySLAs.

Infeasible solutions or negative expected values of future climate information are undesired problems if climate policies are adopted under Cost-Effectiveness Analysis (CEA) to reach uncertain temperature targets. Cost-Risk Analysis (CRA) was developed to resolve these issues. It allows for a trade-off between expected welfare losses of mitigation and avoided risk of transgressing a climate target with a certain probability of compliance (Safety). Some of the significant contributions of this paper are: (i) It updates the Probabilistic Integrated model of Climate and the Economy (PRICE) as a probabilistic version of the latest version of the Dynamic Integrated Climate-Economy model (DICE) 2016, and it extends the model to run welfare-maximizing decision analytic frameworks readily. (ii) It highlights that the standard method of applying CRA (Old CRA) leads to an extra welfare cost. (iii) It proposes revised instruction on how to use CRA. (iv) It simulates and compares welfare-maximizing decision analytic frameworks on the level of risk, damages, and carbon prices. (v) It measures the value of information using risk-based methods and compares them with the value of information calculated using the damage-based method. (vi) It measures the carbon prices for the CRA scenarios for the first time. The results show that the choice of the disutility function governs the magnitude of the value of information. Using a damage function or Old CRA, the value of information is significantly high for new information arriving between 2020 and 2060. If the New CRA is applied, however, such benefits are negligible.

As the field of information technology expands, there is a huge need for cloud service providers (CSP). CSP’s vast solutions and services support Cloud, IoT, Fog, and Edge computing. In today’s competitive cloud market, customer satisfaction is critical more than ever. CSP and consumer satisfaction with service level agreement (SLA) fulfillment have always been given more attention. As a result of signing SLA and CSP agreements to supply resources in high demand, customers are now experiencing issues with resource delivery. Cloud and heterogeneous environments necessitate an intelligent recommender and negotiation agent model (IRNAM) to handle responsibilities in the current system. The Recommender system recommends CSP as per users’ priorities, which eases the filtration process. The negotiation process provided by IRNAM ensures that users’ choices are prioritized with maximum jobs to CSP. IRNAM keeps track of the most critical metrics and can reach decisions quickly and for the best possible deal. It uses an analytical concession algorithm that analyzes consumer and CSP choices to find a reliable, secure server with the simplest solution. The negotiation process uses user’s and CSP choice metrics, performance factors, evaluation measures, and success factors in the best execution time to decide. IRNAM provides a flexible and valuable way for selecting CSP and negotiating for services on the user’s terms while considering CSP satisfaction.

Utility based cloud services can efficiently provide various supportive services to different service providers. Trust negotiations with federated identity management are vital for preserving privacy in open systems such as distributed collaborative systems. However, due to the large amounts of server based communications involved in trust negotiations scalability issues prove to be less cumbersome when offloaded on to the cloud as a utility service. In this view, we propose trust based federated identity management as a cloud based utility service. The main component of this model is the trust establishment between the cloud service provider and the identity providers. We propose novel trust metrics based on the potential vulnerability to be attacked, the available security enforcements and a novel cost metric based on policy dependencies to rank the cooperativeness of identity providers. Practical use of these trust metrics is demonstrated by analyses using simulated data sets, attack history data: published by MIT Lincoln laboratory, real-life attacks and vulnerabilities extracted from Common Vulnerabilities and Exposures (CVE) repository and fuzzy rule based evaluations. The results of the evaluations imply the significance of the proposed trust model to support cloud based utility services to ensure reliable trust negotiations using federated identity management.

Cloud computing is a new concept that refers to a pool of virtual computers resources. Dynamic and scalable internet-based development which is often presented as a service has turned it into a very interesting and significant topic. The service can be a physical machine, virtual machine, software and so on. This study has investigated the problem of building up confidence in cloud environments. To this end, it has designed a model which makes it possible for the users, based on their requirements, to compare a variety of cloud server providers and make their own choice of service provider. The proposed framework enjoys the features of continual availability of trust management service, allocating concessions to cloud service providers, of course, depending on the type of service rendered, utilizing filtering to stop improper storage of ideas, having access to continual service for storing service providers’ information and of allowing transactions to unfamiliar service providers due to risk assessment, and finally storing users’ data in the cloud based on user-defined encoded algorithm. The hopes are that the designed model owing to the above mentioned characteristics can succeed in building trust between users and cloud service providers.

Security concerns are often mentioned amongst the reasons why organizations hesitate to adopt Cloud computing. Given that multiple Cloud Service Providers (CSPs) offer similar security services (e.g., encryption key management) albeit with different capabilities and prices, the customers need to comparatively assess the offered security services in order to select the best CSP matching their security requirements. However, the presence of both explicit and implicit dependencies across security related services add further challenges for Cloud customers to (i) specify their security requirements taking service dependencies into consideration and (ii) to determine which CSP can satisfy these requirements. We present a framework to address these challenges. For challenge (i), our framework automatically detects conflicts resulting from inconsistent customer requirements. Moreover, our framework provides an explanation for the detected conflicts allowing customers to resolve these conflicts. To tackle challenge (ii), our framework assesses the security level provided by various CSPs and ranks the CSPs according to the desired customer requirements. We demonstrate the framework's effectiveness with real-world CSP case studies derived from the Cloud Security Alliance's Security, Trust and Assurance Registry.

Most cloud users and officialdoms have a great interest in adoption and use cloud services like cloud storage to store their data on cloud environment. With the speedy growing in cloud computing technology, user's data security and privacy in cloud computing technology is the utmost dangerous issues because data owner stores their sensitive data onto remote cloud storage. However, successful retrieval of confidential data and computation on confidential data is hard to succeed by traditional cryptographic algorithm. Hence, to warrant the cloud security we are using the cryptographic algorithms that supports for computation over encrypted data. In this, Homomorphic cryptographic algorithm is one such technique that has interested homomorphic cryptographic algorithm used to secure user data in cloud server. It performs computation on cipher texts data can be operated directly without affecting the confidentiality of the encryption algorithms. We have established a framework for security of data on a cloud storage by using fully homomorphic cryptographic algorithm. Indeed, In this study, we have evaluated complexity of three homomorphic cryptographic algorithm those are SDC FHE, Paillier and RSA with encryption time, decryption time, throughput and memory usage

A secure and lightweight cloud data deduplication scheme with efficient access control and key management

For a cloud service provider, it necessitates an emerging cloud ecosystem to consolidate the existing users and attract more potential users, further gaining its market share. Therefore, in this article, we design a price-incentive resource auction mechanism in cloud environment. In response to the cloud resource price, each user synthesizes her bidding budget and QoS requirement, and purchases cloud resources according to her resource demand in a strategic manner. The cloud service provider, meanwhile, can regulate the resource demands of users through conducting a market-based pricing strategy, against too low prices to cover the operational costs (i.e., energy costs) or too high prices resulting in user churn. In virtue of an elaborate market-based pricing strategy, the interests of users and the cloud service provider are balanced. Our price-incentive resource auction mechanism targets to stimulate maximum users willing to purchase resources and perform their applications at the cloud, on the premise of a minimum profit rate guaranteed for the cloud service provider. It is also able to provide budge balance and truthfulness guarantee, and satisfy the envy-freeness. In order to carry out the above objectives, we carefully design the user utility function reflecting the complicated user interest, and formulate our resource pricing and auction problem as a bin packing problem, which has non-polynomial computational complexity. Regarding the NP-hardness of optimization problem and the concavity of user utility, we present a computational-efficient ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1+\epsilon $ </tex-math></inline-formula> )-approximate algorithm namely PIRA. Finally, we conduct simulations based on the real-world dataset to validate the effectiveness of our proposed approach.

Managing trust in a distributed MANET is challenging when collaboration or cooperation is critical to achieve mission and system goals such as reliability, availability, scalability, or reconfigurability. This paper discusses initiation and updation of trust values (called as TRUCE Value) over a defined trust model for mobile ad hoc networks. Each node {ni, where i ∈ 1, 2, 3, .., m} is assigned a trust level initially, while trust levels are updated dynamically based on behavior of nodes {n1, n2, .., nm} using threat detection tools and metrics, such as Intrusion Detection Systems (IDSs) (Zhang et al. (2002), between all nodes in the network. The node {nj} neighboring to a node {nk} exhibiting suspicious behavior can initiate trust reports, and based on an average set of trust reports, the node's {nj} trust value is modified. These defined trust reports are propagated through the network using one of TRUCE (proposed methods). A similar acceptable set of trust nodes can join together to evaluate the security of routes {r} from source to destination nodes. Using these trust levels as a guide, the source node can then select a route that meets the security requirements of the message to be transmitted. This paper focuses on design, development of Trust evaluation, assignment algorithm termed TRUCE over a dynamic, highly insecure MANET network. Also, it demonstrates the procedure of establishing a collaborative, dynamic trust model and uses this model as an example to enhance the security of message routing in mobile ad hoc networks. Performance by simulation reveals that existing malicious nodes behave with vulnerability over MANET routing protocols such as DSR and AODV, but TRUCE with proposed trust-based node incentive mechanism performs better than DSR in terms of packet successful delivery ratio and mean number of packets dropped.