A Trusted Model for Secure Cloud Environment

Cloud computing is an emerging technology that gives a tremendous changes in IT industry. It has ultimate features like multitenancy, elasticity, pay-per-use, self provision etc. But the customers are still hesitant to adopt cloud computing due to security and privacy. In this paper we propose a trust model which secures client’s information from both insiders and outsiders. In this model calculation of trust is based on their compliance report which has been promised in service level agreement

A Trusted Model for Secure Cloud Environment

Cloud computing is an emerging technology that gives a tremendous changes in IT industry. It has ultimate features like multitenancy, elasticity, pay-per-use, self provision etc. But the customers are still hesitant to adopt cloud computing due to security and privacy. In this paper we propose a trust model which secures client’s information from both insiders and outsiders. In this model calculation of trust is based on their compliance report which has been promised in service level agreement. Keywords: cloud computing, trust, compliance, SLA, symmetric encryption  

A Secure Spontaneous Mobile Ad Hoc Cloud Computing Network

[EN] Spontaneous ad hoc cloud computing networks let us perform complex tasks in a distributed manner by sharing computing resources. This kind of infrastructure is based on mobile devices with limited processing and storage capacity. Nodes with more processing capacity and energy in a spontaneous network store data or perform computing tasks in order to increase the whole computing and storage capacity. However, these networks can also present some problems of security and data vulnerability. In this paper, we present a secure spontaneous mobile ad hoc cloud computing network to make estimations using several information sources. The application is able to create users and manage encryption methods to protect the data sent through the network. The proposal has been simulated in several scenarios. The results show that the network performance depends mainly on the network size and nodes mobility.Sendra, S.; Lacuesta Gilaberte, R.; Lloret, J.; Macias Lopez, EM. (2017). A Secure Spontaneous Mobile Ad Hoc Cloud Computing Network. Journal of Internet Technology. 18(7):1485-1498. https://doi.org/10.6138/JIT.2017.18.7.20141221S1485149818

Trust-Based Cloud Machine Learning Model Selection For Industrial IoT and Smart City Services

With Machine Learning (ML) services now used in a number of mission-critical human-facing domains, ensuring the integrity and trustworthiness of ML models becomes all-important. In this work, we consider the paradigm where cloud service providers collect big data from resource-constrained devices for building ML-based prediction models that are then sent back to be run locally on the intermittently-connected resource-constrained devices. Our proposed solution comprises an intelligent polynomial-time heuristic that maximizes the level of trust of ML models by selecting and switching between a subset of the ML models from a superset of models in order to maximize the trustworthiness while respecting the given reconfiguration budget/rate and reducing the cloud communication overhead. We evaluate the performance of our proposed heuristic using two case studies. First, we consider Industrial IoT (IIoT) services, and as a proxy for this setting, we use the turbofan engine degradation simulation dataset to predict the remaining useful life of an engine. Our results in this setting show that the trust level of the selected models is 0.49% to 3.17% less compared to the results obtained using Integer Linear Programming (ILP). Second, we consider Smart Cities services, and as a proxy of this setting, we use an experimental transportation dataset to predict the number of cars. Our results show that the selected model's trust level is 0.7% to 2.53% less compared to the results obtained using ILP. We also show that our proposed heuristic achieves an optimal competitive ratio in a polynomial-time approximation scheme for the problem