Building a trust model system to avoid cloud services reputation attacks

Alshammari, Salah T.; Albeshri, Aiiad; Alsubhi, Khalid

doi:10.1016/j.eij.2021.04.001

Cited by 11 publications

(5 citation statements)

References 19 publications

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“…Alshammari et al [11] have designed a trust model system which contains various trust conditions to estimate the trustworthiness of cloud services. Only the responses with good trust scores are accepted from the cloud service providers.…”

Section: Trust Based Attack Detectionmentioning

confidence: 99%

Gaussian Flower Pollination Optimization Based Trusted Service Selection for Cloud Computing Environment

2024

IJIES

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As cloud computing is a combination of variety of technologies, there are a number of security concerns need to be addressed. To protect from various attacks and to improve the security of cloud users, it is required to analyze the trust relationships among the cloud resources and tasks. Most of the trust management systems did not consider the significance of interactions, which affects the correctness of trust evaluations. This paper proposes Gaussian flower pollination optimization (GFPO) based trusted service selection (TSS) technique. In this technique, each cloud service provider's reputation values are computed from the trust value of its servers. The individual trust values of cloud servers are determined based on interaction success rate (ISR), service success index (SSI) and service response time (SRT) parameters. The optimal weight values of these parameters are adaptively determined using GFPO algorithm. During the data transfer from server to the user, the user checks the server's trust value and ignores the response if its trust value is low. Experimental results from Cloudsim show that GFPO-TSS minimizes the computation overhead and access delay, maximizes the accuracy and success rate. GFPO-TSS has 45% reduced computation cost, 10% increased data correctness.

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Section: Trust Based Attack Detectionmentioning

confidence: 99%

Gaussian Flower Pollination Optimization Based Trusted Service Selection for Cloud Computing Environment

2024

IJIES

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“…5. The reputation of the targeted NFV provider could be negatively affected as they will appear to have security breaches [62]. Actor: NFV consumer (attacker) Precondition: The attacker has a valid account and active network services.…”

Section: Consequencesmentioning

confidence: 99%

“…The reputation of the targeted NFV provider could be negatively affected as they will appear to have security breaches [62].…”

mentioning

confidence: 99%

Misuse Patterns from the Threat of Modification of Non-Control Data in Network Function Virtualization

Alnaim

2022

Future Internet

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Network Function Virtualization (NFV) is a virtual network model, the goal of which is a cost-efficient transition of the hardware infrastructure into a flexible and reliable software platform. However, this transition comes at the cost of more security threats. A key part of this virtualization environment is the hypervisor, which emulates the hardware resources to provide a runtime environment for virtual machines (VMs). The hypervisor is considered a major attack vector and must be secured to ensure network service continuity. The virtualization environment contains critical non-control data where compromise could lead to several misuses, including information leakage and privilege and resource modification. In this paper, we present a misuse pattern for an attack that exploits the security vulnerabilities of the hypervisor to compromise the integrity of non-control data in the NFV environment. Misuse patterns are used to describe how attacks are carried out from the attackers’ perspective. The threat of modification of non-control data can lead to several misuses, and in this paper, we discuss three of them. The defenses to this attack can be incorporated into the Security Reference Architecture (SRA) of the NFV system to prevent these misuses.

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“…Any type of trust management service is vulnerable to a variety of attacks [31]. These attacks have the potential to either enhance or destroy the reputation of a specific entity [32,33]. In order to build an accurate and secure trust model system, we focus on implementing various metrics to prevent these attacks, which enables us to create a stable, reliable, and accurate trust model framework.…”

Section: Comparison Of Security and Accuracymentioning

confidence: 99%

Building a Reputation Attack Detector for Effective Trust Evaluation in a Cloud Services Environment

Alshammari

Alsubhi

2021

Applied Sciences

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Cloud computing is a widely used technology that has changed the way people and organizations store and access information. This technology is versatile, and extensive amounts of data can be stored in the cloud. Businesses can access various services over the cloud without having to install applications. However, cloud computing services are provided over a public domain, which means that both trusted and non-trusted users can access the services. Although there are a number of advantages to cloud computing services, especially for business owners, various challenges are posed in terms of the privacy and security of information and online services. A threat that is widely faced in the cloud environment is the on/off attack, in which entities exhibit proper behavior for a given time period to develop a positive reputation and gather trust, after which they exhibit deception. Another threat often faced by trust management services is a collusion attack, which is also known as collusive malicious feedback behavior. This is carried out when a group of people work together to make false recommendations with the intention of damaging the reputation of another party, which is referred to as a slandering attack, or to enhance their own reputation, which is referred to as a self-promoting attack. In this paper, a viable solution is provided with the given trust model for preventing these attacks. This method works by providing effective security to cloud services by identifying malicious and inappropriate behaviors through the application of trust algorithms that can identify on/off attacks and collusion attacks by applying different security criteria. Finally, the results show that the proposed trust model system can provide high security by decreasing security risk and improving the quality of decisions of data owners and cloud operators.

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Building a trust model system to avoid cloud services reputation attacks

Cited by 11 publications

References 19 publications

Gaussian Flower Pollination Optimization Based Trusted Service Selection for Cloud Computing Environment

Gaussian Flower Pollination Optimization Based Trusted Service Selection for Cloud Computing Environment

Misuse Patterns from the Threat of Modification of Non-Control Data in Network Function Virtualization

Building a Reputation Attack Detector for Effective Trust Evaluation in a Cloud Services Environment

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