To solve the problem that the existing hierarchical searchable encryption scheme cannot effectively resist quantum attack and cannot flexibly add and delete the level, a scheme of Adaptive Hierarchical Searchable Encryption based on learning with errors (AHSE) was proposed. Firstly, the proposed scheme was made to effectively resist the quantum attack by utilizing the multidimensional characteristic of lattices and based on the Learning With Errors (LWE) problem on lattices. Secondly, the condition key was constructed to divide the users into different levels clearly, making the user only able to search the files at his own level, so as to achieve effective level access control. At the same time, a segmented index structure with good adaptability was designed, whose levels could be added and deleted flexibly, meeting the requirements of access control with different granularities. Moreover, all users in this scheme were able to search by only sharing one segmented index table, which effectively improves the search efficiency. Finally, theoretical analysis shows that the update, deletion and level change of users and files in this scheme is simple and easy to operate, which are suitable for dynamic encrypted database, cloud medical system and other dynamic environments.

Concerning the problem that current genetic comparison protocols generally require a trusted third party, which may result in the leakage of a wide range of private data, a genetic comparison scheme based on linear scan was proposed. The gene sequences of two parties were first encoded based on Garbled Circuit (GC), and then the genome database was linearly scanned and the garbled circuit was used to compare gene sequence of user with all gene sequences in database. The above scheme can achieve genetic comparison under the premise of protecting user privacy of both parties. However, the scheme needs to scan whole database with time complexity of O( n), and is inefficient when the genome database is large. In order to improve the efficiency of genetic comparison, a genetic comparison scheme based on Oblivious Random Access Memory (ORAM) was further proposed, in which genetic data was stored at ORAM first, then only the data blocks on target path were picked out to perform genetic comparison by using garbled circuit. This scheme has the number of comparisons sub-linear to the size of database and time complexity of O (log n). The experimental results show that the genetic comparison scheme based on ORAM reduces the number of comparisons from O( n) to O(log n) while realizing privacy protection, significantly decreases the time complexity of comparison operation. It can be used for disease diagnosis, especially in the case with large genome database.

Aiming at the excessively long time consumption of round function in block cipher implementation, a new software pipelining realization method of Advanced Encryption Standard (AES) algorithm based on Reconfigurable Cipher Stream Processor (RCSP) was proposed. The operations of round function were divided into several pipelining segments. The different pipelining segments corresponded to different cipher resources. The instruction level parallelism was developed to accelerate the execution speed of round function by executing different pipelining segments of multiple round functions in parallel. The execution efficiency of block cipher algorithm was improved. The separation processes of pipelining segments and software pipelining mapping methods of AES algorithm were analyzed with the computing resources of single cluster, two clusters and four clusters of RCSP. The experimental results show that, the proposed software pipelining realization method, which makes different data fragments of one block or multiple blocks processed in parallel, can not only improve the performance of a block serial execution, but also improve the performance of multiple blocks parallel execution by developing the parallelism between the blocks.