At present， researches on SQLite encryption both domestically and internationally are conducted at the file level and with the single-key， resulting in coarse encryption granularity and low decryption difficulty. In response to the security shortcomings of SQLite， a multi-key page-level encryption system was proposed. Firstly， an independent page key was assigned to each physical page， allowing for individual encryption and decryption of each page. A key file was introduced to store all page keys. Secondly， a page key cache module KeyCache was designed to generate and cache page keys for pages， thereby reducing the performance loss caused by frequent I/O read and write operations. Thirdly， an encryption and decryption module Crypto was proposed to implement the encryption and decryption functions. Crypto was used to quickly retrieve page keys through KeyCache， consequently enhancing the overall system performance. A comparative experiment was conducted between the proposed system and typical SQLCipher. Experimental results show that in read and update tests， compared with SQLCipher， the execution time of the proposed system reduced by 1.5% and 3.0% on average， achieving better performance at a higher security level. Additionally， in create and delete tests， the proposed system exhibits minimal performance loss compared to SQLCipher and the performance loss is close to SQLCipher while significantly enhancing the security level， verifying the effectiveness of the proposed system.

Splicing is the most universal image tampering operation, detection of which is effective for identifying image tamper. A blind splicing detection method was proposed. The method firstly analyzed the effects of different sub-bands on image splicing detection according to features of wavelet transform. High frequency sub-band was verified to be more appropriate for splicing detection both from theory analysis and experiment results. Secondly, the method conducted difference operation, rounded and made threshold to the coefficients as discrete Markov states, and calculated the state transition probabilities as splicing features. Finally, Support Vector Machine (SVM) was used as classifier, and the features were tested on Columbia image splicing detection evaluation datasets. The experimental results show that the proposed method performs better compared with other features and achieves a detection accuracy rate of 94.6% on the color dataset specially.

Unattended Wireless Sensor Network (UWSN) is usually deployed in a bad or hostile environment. The deployment of static aggregation node (or base station) is difficult, making real-time information aggregation impossible. Hence the node should undertake the mission of self-sustaining the data temporarily. In order to enhance the probability of data survival, this paper proposed a dependable data survival scheme based on Chinese Remainder Theorem (CRT) weighted threshold secret sharing in UWSN. The scheme built a node reputation model in the network, improving the efficiency and effectiveness of key division, distribution and reconstruction. In addition, this paper also discussed the good homomorphism properties of CRT based multi-secret sharing, and the key combination operation scheme, which further ensures the reliable survival of data.