Wang Jun

TL;DR: In this paper, the authors proposed a method for detecting DDoS attacks in a big data environment by extracting a source IP address from various collected data streams, calculating information entropy of the source IP addresses, and if the information entropy is greater than a preset threshold value V, determining that the data stream corresponding to the IP address may be a DDoS attack stream, and implementing early warning.

TL;DR: In this article, a revocable attribute base encryption (RBE) method is proposed, where a master public key and a master key are generated for a system through a trusted authentication mechanism, and an attribute usergroup corresponding to each attribute is transmitted to a data management server after user attributes needing to be registered are verified and corresponding private keys are generated.

TL;DR: In this article, a low-rate denial of service attack data stream detection method for a cloud environment is proposed, which consists of the following steps: identifying various lowrate data streams of the cloud environment by calculating the Renyi information entropy, extracting local feature information of the low-Rate data streams by constructing a hierarchical model based on a convolutional neural network, and online detecting various low-RDS attack data streams; when the difference between the actual output of the LRS data stream and the expected output exceeds a threshold, determining that the low RDS data stream is

TL;DR: In this paper, a privacy protection method for storing shared data in a mobile cloud is proposed, where the privacy of a data owner is effectively protected through strategy semi-hiding, which is suitable for the situation that the encryption strategy in the mobile terminal application is far less than the system attribute.