In the Internet environment, documents are easily leaked, and divulged files spread rapidly. Therefore, it is important for privacy institutions to actively check the documents on the Internet to find out whether some...In the Internet environment, documents are easily leaked, and divulged files spread rapidly. Therefore, it is important for privacy institutions to actively check the documents on the Internet to find out whether some private files have been leaked. In this paper, we put forward a scheme for active image betrayal checking on the Intemet based on the digital fingerprint, which embeds fingerprints into privacy documents, extracts codes from the Intemet images, and then fmds out the divulged files by matching two groups of codes. Due to so many documents on the Internet, the number of times of code comparison is huge, which leads to a large running time. To overcome the deficiency in practical application, we optimized the process by accurate matching methods and approximate matching method. Then a method was proposed to group objects by locality sensitive hashing （LSH） process before code comparison, in order to eliminate the vast majority of unrelated pairs. Experiments prove that this method could operate with less running time and less memory.展开更多
基金National High-Tech Research and Development Program of China(863 Program)(No.2007AA01Z309)
文摘In the Internet environment, documents are easily leaked, and divulged files spread rapidly. Therefore, it is important for privacy institutions to actively check the documents on the Internet to find out whether some private files have been leaked. In this paper, we put forward a scheme for active image betrayal checking on the Intemet based on the digital fingerprint, which embeds fingerprints into privacy documents, extracts codes from the Intemet images, and then fmds out the divulged files by matching two groups of codes. Due to so many documents on the Internet, the number of times of code comparison is huge, which leads to a large running time. To overcome the deficiency in practical application, we optimized the process by accurate matching methods and approximate matching method. Then a method was proposed to group objects by locality sensitive hashing （LSH） process before code comparison, in order to eliminate the vast majority of unrelated pairs. Experiments prove that this method could operate with less running time and less memory.
