DESIRABLE SOLUTION TO UPDATE THE ENCRYPTED DATA IN OPEN NETS

Attribute-Based File encryption (ABE) is really a promising technique to guarantee the finish-to-finish security of massive data within the cloud. Within this paper, we advise a manuscript plan that enabling efficient access control with dynamic policy updating for giant data within the cloud. However, the insurance policy updating happens to be a frightening issue when ABE can be used to create access control schemes. An insignificant implementation would be to let data proprietors retrieve the information and re-secure it underneath the new access policy, after which send it to the cloud. Because of the high volume and velocity of massive data, it's an effective choice to store big data within the cloud, because the cloud has abilities of storing big data and processing high amount of user access demands. This process, however, incurs a higher communication overhead and high computation burden on data proprietors. We concentrate on developing an outsourced policy updating way of ABE systems. Our method can steer clear of the transmission of encrypted data and reduce the computation work of information proprietors, by utilizing the formerly encrypted data with old access policies. Furthermore, we propose policy updating algorithms for various kinds of access policies. Case study implies that our policy updating outsourcing plan is true, complete, safe and effective. Finally, we advise a competent and secure way in which enables data owner to check on if the cloud server has updated the cipher texts properly

Algorithms for advance bandwidth reservation in media production networks

Media production generally requires many geographically distributed actors (e.g., production houses, broadcasters, advertisers) to exchange huge amounts of raw video and audio data. Traditional distribution techniques, such as dedicated point-to-point optical links, are highly inefficient in terms of installation time and cost. To improve efficiency, shared media production networks that connect all involved actors over a large geographical area, are currently being deployed. The traffic in such networks is often predictable, as the timing and bandwidth requirements of data transfers are generally known hours or even days in advance. As such, the use of advance bandwidth reservation (AR) can greatly increase resource utilization and cost efficiency. In this paper, we propose an Integer Linear Programming formulation of the bandwidth scheduling problem, which takes into account the specific characteristics of media production networks, is presented. Two novel optimization algorithms based on this model are thoroughly evaluated and compared by means of in-depth simulation results