Current Issue : January - March Volume : 2021 Issue Number : 1 Articles : 5 Articles
The existence of Internet of Things (IoT) facilitates the collection and transmission of urban data information. However, it can leak\nusersâ?? personal privacy information in smart cities. Therefore, we propose a new private information encryption method in IoT\nunder cloud computing environment. Under IoT, according to the properties and acquisition time, privacy information can be\ndivided into many subspaces. Then, we analyze the private information encryption with different levels. Based on the stream\ncipher mechanism, we design an encryption system model of information collection. In the subspace, the privacy information is\nencrypted and transferred to the relay node. After encrypting, they are segmented and restructured. The long privacy\ninformation is divided into smaller slices. Then, they are reintegrated after conversion. Finally, we use stream cipher and dualkey\nalgorithm to complete freedom nondestructive transformation between plaintext and ciphertext to ensure the integrity of\nthe encrypted private information. Experimental results show that the proposed method takes less time in the encryption and\ndecryption process, which has better ciphertext conversion output effect and suffers fewer network attacks in the same\nencryption time. The message encryption and decryption time is less than that of other methods. In terms of calculation cost,\nthe proposed method decreases by approximately 14%. What is more, it has higher security and improves the security and\nintegrity of the privacy information collection process....
With the rapid development of e-business, large volume of business processes need to be handled in a constrained time. There is\nalways a security issue related to on-time completion in many applications in the economic fields. So, how to effectively manage and\norganize business processes became very important. By using cloud computing, instance-intensive processes can be handled more\neffectively by applying just-right virtual machines. Hence, the management of cloud resources became an important issue that many\nresearchers focus on to fully utilize the advantage of cloud. In this paper, we mainly discuss the queuing theory and put forward our\nnovel dynamic process scheduling model based on queuing theory, which is namedM/G/k/l-P for business processes. This model can\nsolve the issue of allocating appropriate number of cloud resources based on the number of tasks and execution stages to ensure\nwhether the numbers of cloud resources are sufficient and adequate or not, which can improve the security issue for business process.\nThe service discipline in our model can provide a dynamic process by setting different priorities to improve the experience of users.\nEvaluations prove that the queuing model of M/G/k/l-P can work very well for business workflow scheduling....
With the widespread application of cloud computing sharing technology, the demand for cross-domain interaction is also\nincreasing. However, due to the uncertainty of interaction behaviour and the difference of network service quality, the risk of\ncross-domain interaction cannot be accurately evaluated. Therefore, this paper proposes a risk situation evaluation model based\non interdomain interactions. The model collects interactive credentials such as the frequency, credibility, and time-effectiveness of\nthe user-submitted evaluations. At the same time, it collects the evaluation of quality of service provided by the network security\ndomain. Then, we set up a risk evaluation equation based on the interaction credentials to implement the risk evaluation of crossdomain\ninteraction behaviour. Finally, we apply MATLAB platform to simulate the evolution process of evaluation. The experimental\nresults show that, compared with other models, the evaluation method proposed in this paper improves the accuracy of\nthe evaluation results and meets the security requirements of multidomain interaction....
The tremendous growth of computational clouds has attracted and enabled intensive computation on resource-constrained client\ndevices. Predominantly, smart mobiles are enabled to deploy data and computational intensive applications by leveraging on the\ndemand service model of remote data centres. However, outsourcing personal and confidential data to the remote data servers is\nchallenging for the reason of new issues involved in data privacy and security. Therefore, the traditional advanced encryption\nstandard (AES) algorithm needs to be enhanced in order to cope with the emerging security threats in the cloud environment. This\nresearch presents a framework with key features including enhanced security and ownerâ??s data privacy. It modifies the 128 AES\nalgorithm to increase the speed of the encryption process, 1000 blocks per second, by the double round key feature. However,\ntraditionally, there is a single round key with 800 blocks per second. The proposed algorithm involves less power consumption,\nbetter load balancing, and enhanced trust and resource management on the network. The proposed framework includes deployment\nof AES with 16, 32, 64, and 128 plain text bytes. Simulation results are visualized in a way that depicts suitability of the\nalgorithm while achieving particular quality attributes. Results show that the proposed framework minimizes energy consumption\nby 14.43%, network usage by 11.53%, and delay by 15.67%. Hence, the proposed framework enhances security, minimizes\nresource utilization, and reduces delay while deploying services of computational clouds....
With the proliferation of new mobile devices, mobile cloud computing technology has emerged to provide rich computing and\nstorage functions for mobile users. The explosive growth of mobile data has led to an increased demand for solutions that conserve\nstorage resources. Data deduplication is a promising technique that eliminates data redundancy for storage. For mobile cloud\nstorage services, enabling the deduplication of encrypted data is of vital importance to reduce costs and preserve data confidentiality.\nHowever, recently proposed solutions for encrypted deduplication lack the desired level of security and efficiency. In\nthis paper, we propose a novel scheme for serverless efficient encrypted deduplication (SEED) in mobile cloud computing\nenvironments. Without the aid of additional servers, SEED ensures confidentiality, data integrity, and collusion resistance for\noutsourced data. The absence of dedicated servers increases the effectiveness of SEED for mobile cloud storage services, in which\nuser mobility is essential. In addition, noninteractive file encryption with the support of lazy encryption greatly reduces latency in\nthe file-upload process. The proposed indexing structure (D-tree) supports the deduplication algorithm and thus makes SEED\nmuch more efficient and scalable. Security and performance analyses prove the efficiency and effectiveness of SEED for mobile\ncloud storage services....
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