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With the development of big data and the increase of encryption scenarios, it 's difficult to meet the requirements of encryption performance with only software-run encryption methods, and FPGA/ ASIC encryption systems implemented using Verilog/VHDL methods have poor flexibility and difficult maintenance and upgrades problem. In response to the above problems, this paper designed and implemented an AES algorithm encryption system based on heterogeneous reconfigurable computing, including three mainstream modes of AES algorithm ECB, CBC, CTR, each mode realized 128 bit, 192 bit, 256 bit encryption of three key sizes. This paper realized the hardware acceleration of the module based on FPGA, and realized the dynamic switching of different modes and different bit width encryption modules based on the hardware reconfigurable mechanism. By implementing and verifying the system on Intel Stratix 10, the experimental results show that the throughput rates of AES-ECB, AES-CTR and AES-CBC in the system are 116.43 Gbps,60. 34 Gbps, and 4. 32 Gbps, respectively. The ECB mode compared with Intel Xeon E5-2650 V2 CPU and NVIDIA GeForce GTX 1080 GPU achieves 23.18 times and 1.43 times acceleration ratios respectively. Compared with the method just calling the CPU,the overall system has a computational acceleration ratio of 4.72. [ABSTRACT FROM AUTHOR]

In order to solve the weakness of existing medial image encryption algorithm based on chaotic system in considering the image' s texture feature, this paper proposed a medical image encryption and decryption method based on chaotic mapping and adaptive partitioning. Firstly, it used the 2D Sine Logistic chaotic system to generate two secure sequences with good chaotic characteristics . Then, it divided the original medical image into fixed size image blocks, and calculated their maximum pixel difference and variance . According to the given threshold, it divided these image blocks into texture smooth blocks and texture complex blocks. Finally, it used the first chaotic sequence with ciphertext feedback mechanism to encrypt the smooth blocks, and encrypt the complex blocks by using the second chaotic sequence with plaintext feedback mechanism. Therefore, it obtained the encrypted image. Because the presented algorithm efficiently considered the texture characteristics of image blocks and optimized the algorithm of chaotic encryption, it improved the encryption and decryption efficiency of medical images. Experimental simulation results show that the presented algorithm has high security and encryption efficiency. Compared with the existent method, it reduces the encryption and decryption time by about 0. 5 times . The presented algorithm is suitable for real-time medical images encryption and decryption with big data size. [ABSTRACT FROM AUTHOR]

This paper proposes a searchable encryption model for graph data to address the problem that most of the current searchable encryption schemes cannot deal with complex data structures. The algorithms and security models of the scheme are described. Taking the encryption index of matrix structure into account， the detailed description of the searchable encryption scheme for graph data that supports adjacency queries is presented. The scheme utilizes pseudo-random functions and pseudo-random permutations to protect the privacy of the graph data and the encrypted index. Real models and ideal models test the security of the scheme. Compared with traditional searchable encryption schemes， the proposed scheme has more flexible searching ability and higher efficiency， which promotes broader application under big data environment. [ABSTRACT FROM AUTHOR]