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Handling Trust in a Cloud based Multi Agent System
Abstract
Cloud computing is an opened and distributed network that guarantees access to a large amount of data and IT infrastructure at several levels (software, hardware...). With the increase demand, handling clients’ needs is getting increasingly challenging. Responding to all requesting clients could lead to security breaches, and since it is the provider’s responsibility to secure not only the offered cloud services but also the data, it is important to ensure clients reliability. Although filtering clients in the cloud is not so common, it is required to assure cloud safety. In this paper, by implementing multi agent systems in the cloud to handle interactions for the providers, trust is introduced at agent level to filtrate the clients asking for services by using Particle Swarm Optimization and acquaintance knowledge to determine malicious and untrustworthy clients. The selection depends on previous knowledge and overall rating of trusted peers. The conducted experiments show that the model outputs relevant results, and even with a small number of peers, the framework is able to converge to the best solution. The model presented in this paper is a part of ongoing work to adapt interactions in the cloud.
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Cloud Computing has become a promising paradigm to deliver different computing resources and services over the Internet on demand. The cloud users have to rely on the third party service providers for accessing services. With an increase in available cloud services, selecting an appropriate cloud service provider to deliver the service securely will be always challenging for users. The trust measure plays an important role while selecting proper service providers to handle user’s requests in the cloud environment. Hence, evaluation of the trustworthiness of the cloud service provider before selecting it to deliver the service has become an important requirement in the cloud environment. The paper presents a method to evaluate the trustworthiness of cloud service providers on the basis of it’s behavior and feedback given by the users. The various Quality of Service attributes are considered for computing behavioral trust values. The different parameters from the service level agreement are used to maintain the feedback and compute the feedback trust value for the service provider. The trustworthiness of the cloud service provider is judged by computing the cumulative trust, which is calculated using behavioral trust and feedback trust. Also, the proposed model includes a mechanism to judge the genuineness of feedback submitted by the users. The proposed method is compared with Evidence Based Trust Model and Enhanced QoS based Model to evaluate the performance in terms of accuracy and efficiency.
Cloud computing, like any distributed computing system, is continually exposed to many threats and attacks of various origins. Thus, cloud security is now a very important concern for both providers and users. Intrusion detection systems (IDSs) are used to detect attacks in this environment. The goal of security administrators (for both customers and providers) is to prevent and detect attacks while avoiding disruption of the smooth operation of the cloud. Making IDSs efficient is not an easy task in a distributed environment such as the cloud. This problem remains open, and to our knowledge, there are no satisfactory solutions for the automated evaluation and analysis of cloud security. The features of the multi-agent system paradigm, such as adaptability, collaboration, and distribution, make it possible to handle this evolution of cloud computing in an efficient and controlled manner. As a result, multi-agent systems are well suited to the effective management of cloud security. In this paper, we propose an efficient, reliable and secure distributed IDS (DIDS) based on a multi-agent approach to identify and prevent new and complex malicious attacks in this environment. Moreover, some experiments were conducted to evaluate the performance of our model.
The Internet of Things (IoT) provides a new paradigm for the development of heterogeneous and distributed systems, and it has increasingly become an ubiquitous computing service platform. However, due to the lack of sufficient computing and storage resources dedicated to the processing and storage of huge volumes of IoT data, it tends to adopt a cloud-based architecture to address the issues of resource constraints. Hence, a series of challenging security and trust concerns have arisen in the cloud-based IoT context. To this end, a novel trust assessment framework for the security and reputation of cloud services is proposed. This framework enables the trust evaluation of cloud services in order to ensure the security of the cloud-based IoT context via integrating security-based and reputation-based trust assessment methods. The securitybased trust assessment method employs cloud-specific security metrics to evaluate the security of a cloud service. Furthermore, the feedback ratings on the quality of cloud service are exploited in the reputationbased trust assessment method in order to evaluate the reputation of a cloud service. Experiments conducted using a synthesized dataset of security metrics and a real-world web service dataset show that our proposed trust assessment framework can efficiently and effectively assess the trustworthiness of a cloud service while outperforming other trust assessment methods.
Trustworthiness is an important indicator for service selection and recommendation in the cloud environment. However, predicting the trust rate of a cloud service based on its multifaceted QoSs is not an easy task due to the complicated and non-linear relations between service’s QoS values and the final trust rate of the service. According to the existing studies, the adoption of intelligent technique is a rational way to attack this problem. Neural network has been validated as an effective way to predict the trust rate of the service. However, the parameter setting of neural network, which plays an important role in its prediction performance, has not been properly addressed yet. In the paper, particle swarm optimization (PSO) is introduced to enhance neural network by optimizing its initial settings. In the proposed hybrid prediction algorithm named PSO-NN, PSO is used to search the appropriate parameters for neural network so as to realize accurate trust prediction of cloud services. In order to investigate the effectiveness of PSO-NN, extensive experiments are performed based on public QoS data set, as well as in-depth comparison analysis. The results show that our proposed approach has better performance than basic classification methods in most cases, and significantly outperforms the basic neural network in terms of prediction precision. In addition, PSO-NN demonstrates better stability than the basic neural network.
When making reservations for Cloud services, consumers and providers need to establish service-level agreements through negotiation. Whereas it is essential for both a consumer and a provider to reach an agreement on the price of a service and when to use the service, to date, there is little or no negotiation support for both price and time-slot negotiations (PTNs) for Cloud service reservations. This paper presents a multi-issue negotiation mechanism to facilitate the following: 1) PTNs between Cloud agents and 2) tradeoff between price and time-slot utilities. Unlike many existing negotiation mechanisms in which a negotiation agent can only make one proposal at a time, agents in this work are designed to concurrently make multiple proposals in a negotiation round that generate the same aggregated utility, differing only in terms of individual price and time-slot utilities. Another novelty of this work is formulating a novel time-slot utility function that characterizes preferences for different time slots. These ideas are implemented in an agent-based Cloud testbed. Using the testbed, experiments were carried out to compare this work with related approaches. Empirical results show that PTN agents reach faster agreements and achieve higher utilities than other related approaches. A case study was carried out to demonstrate the application of the PTN mechanism for pricing Cloud resources.
FABR´ICIOFABR´FABR´ICIO ENEMBRECK, PPGIa: Graduate Program on Informatics – Pontifical Catholic University of ParanáParan´Paraná – PUCPR Finding reliable partners to interact with in open environments is a challenging task for software agents, and trust and reputation mechanisms are used to handle this issue. From this viewpoint, we can observe the growing body of research on this subject, which indicates that these mechanisms can be considered key elements to design multiagent systems (MASs). Based on that, this article presents an extensive but not exhaustive review about the most significant trust and reputation models published over the past two decades, and hundreds of models were analyzed using two perspectives. The first one is a combination of trust dimensions and principles proposed by some relevant authors in the field, and the models are discussed using an MAS perspective. The second one is the discussion of these dimensions taking into account some types of interaction found in MASs, such as coalition, argumentation, negotiation, and recommendation. By these analyses, we aim to find significant relations between trust dimensions and types of interaction so it would be possible to construct MASs using the most relevant dimensions according to the types of interaction, which may help developers in the design of MASs.
Agent-based Cloud computing is concerned with the design and development of software agents for bolstering Cloud service discovery, service negotiation and service composition. The significance of this work is introducing an agent-based paradigm for constructing software tools and testbeds for Cloud resource management. Novel contributions of this work include: 1) developing Cloudle: an agent-based search engine for Cloud service discovery, 2) showing that agent-based negotiation mechanisms can be effectively adopted for bolstering Cloud service negotiation and Cloud commerce, and 3) showing that agent-based cooperative problem-solving techniques can be effectively adopted for automating Cloud service composition. Cloudle consists of a service discovery agent that consults a Cloud ontology for determining the similarities between providers' service specifications and consumers' service requirements. To support Cloud commerce, this work devised a complex Cloud negotiation mechanism that supports parallel negotiation activities in interrelated markets. Empirical results show that using such mechanism, agents achieved high utilities and high success rates in negotiating for Cloud resources. To automate Cloud service composition, agents adopt the contract net protocol (CNP) and use acquaintance networks (AN). Empirical results show that using CNP and AN, agents can successfully compose Cloud services by autonomously selecting services.
The concept of an agent has become important in both Artificial Intelligence (AI) and mainstream computer science. Our aim in this paper is to point the reader at what we perceive to be the most important theoretical and practical issues associated with the design and construction of intelligent agents. For convenience, we divide these issues into three areas (though as the reader will see, the divisions are at times somewhat arbitrary). Agent theory is concerned with the question of what an agent is, and the use of mathematical formalisms for representing and reasoning about the properties of agents. Agent architectures can be thought of as software engineering models of agents; researchers in this area are primarily concerned with the problem of designing software or hardware systems that will satisfy the properties specified by agent theorists. Finally, agent languages are software systems for programming and experimenting with agents; these languages may embody principl...
This article is a literature survey on trust theory, the relationship between trust and security and distribution of trust in networks, especially in distributed and open networks. The article is divided into three sections: trust theory, security principles and trust distribution. The trust theory section looks at the theoretical aspects of trust and shows some of the methods researchers use to quantify trust. The security theory section explains the fundamentals of security and tries to establish a relationship between security and trust. This section also attempts to highlight the significance of trust in distributed network security. The final section considers ad hoc networks as one of the latest paradigms in wireless networking and looks at some proposals and initiatives aimed at establishing trust distribution in ad hoc networks.
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