Zhang Yi
3 Papers
7 Citations
Zhang Yi is an academic researcher. The author has contributed to research in topics: Code (cryptography) & Block (programming). The author has an hindex of 1, co-authored 3 publications.
Chat about Author
Papers
Patent
Binary software protection method by means of dynamic fine-grained code hiding and obfuscating technology
Zhang Yi,Meng Wu,Mi Xianya,Xu Binbin,Tang Yong,Yang Qiang,Xie Wei,Zhou Xu +7 more
- 10 May 2017
TL;DR: In this paper, a binary software protection method by means of a dynamic fine-grained code hiding and obfuscating technology is presented, which comprises the steps that S1, a hidden target is selected, wherein a to-be-hidden code block is selected in a target program with a basic block as a unit; S2, the selected basic block is hidden, wherein according to each to be-hidden basic block, an original code segment is replaced with a distributor function call, and other obfuscating instructions are filled in the rest positions; S3, the codes are
5
Patent
Binary software protection method based on dynamic code conversion
Zhang Yi,Xu Binbin,Mi Xianya,Tang Yong,Yu Bo,Xie Wei,Yang Qiang +6 more
- 26 Apr 2017
TL;DR: In this paper, a binary software protection method based on dynamic code conversion is proposed, which comprises the following steps of: S1: extracting the basic block of a code to be protected to obtain pieces; S2: processing the pieces: equally dividing all pieces into two parts including an upper half part and a lower half part, randomly selecting certain pieces from the upper half parts, and initializing the pieces into a ciphertext state, wherein the rest pieces of the corresponding lower half parts of the upperhalf part are under the ciphertext states; and S3: inserting a
1
Patent
Method of malicious code family identification based on incremental DBSCAN algorithm
Tang Yong,Yi Wang,Lu Zexin,Yu Xin,Zhang Yi,Yang Qiang,Zhou Xu +6 more
- 10 May 2017
TL;DR: In this paper, a method of malicious code family identification based on incremental DBSCAN algorithm is proposed, which saves malicious code feature vectors in a database using IDA Python script to extract the features of the sample, the feature is transformed into feature vectors and saved in the database.
1