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Cloud computing is a universal conventional system. With the exponential development of cloud data and storage room, cloud security has turned out to be one of the intriguing exploration regions of cloud registering servers. Property based encryption is an open key encryption calculation that permits cloud users to anchor their delicate data in the general population cloud servers. Credited based Quantum cryptography will anchor the user data transmission and correspondence through cloud frame programmers. Be that as it may, daze quantum registering will anchor the moment spying or getting to of data handling in cloud from any awful cloud provider or outsider. In this paper we proposed an algorithm based on blind quantum computing for to secure the communication between data owner and CSP. And enhanced the hierarchal attribute-based encryption algorithm using BCQ key sharing which provides user data providing and group accessing of cloud data. The experimental results show that the proposed mechanism is efficient than the existing CP-ABE enhancements.

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In the last two decades lot of research and development occurs on Location-Based Authentication and Security Services (LBASSs) which allow users to see where their friends are, to search location-tagged content within their local area networks, and to meet others nearby. Previously the data can be accessed from anywhere and any time. Hence lot of unexpected misjudgment were happened due to location independent authentication protocols. The recent availability of open mobile platforms, such as Apple iPhones and any Android phones, makes LBASSs much more accessible to mobile users. After rigorous research funding into this area leads to regulate the access that resources preserved in particular locations. Therefore we improve the development of security from location. We have been study how users share their location in real world, we collected traces from a commercial LBS services operated by a startup company. In this paper, surveyed all algorithm schemes since two decades and bring out detailed analysis over geo encryption, location authentication, location privacy, enhanced location security, User authentication mobility parameters, tolerant distances under smart living applications. To the best of our knowledge, this study fills the gap between old technologies and new technologies and presents fine tuning quantitative analysis of a real-world LBS services. In this paper authors investigate the various key issues and their methodologies for location authentication in WLAN and mobile devices. This paper leaves several ideas for researchers to mitigate issues in location privacy and authentication areas for better future.

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In the distributed data-intensive computing environment, securely assigning tasks to appropriate machines is a big job scheduling problem. The complexity of this problem increases with the number of jobs and their job times. Several meta-heuristic algorithms including particle swarm optimization (PSO) technique and variable neighborhood particle swarm optimization (VNPSO) technique are employed to solve the problem to a certain extent. This paper proposes a modified PSO with scout adaptation (MPSO-SA) algorithm, which uses a cyclic term called mutation operator, to solve the job scheduling problem in the cloud environment. The comparative study between the proposed MPSO-SA scheduling mechanism and the conventional scheduling algorithms show that the proposed method decreases the probability of security risk on scheduling the jobs.