human: Given a node-centered hypergraph: <hypergraph>, where nodes represent authors and hyperedges represent groups of authors who co-authored the same paper.

Details of the hypergraph:
Center node: "Motion vector-based video steganography with preserved local optimality"
  Abstract: Current motion vector based video steganography is unable to preserve the local optimality of modified motion vectors. Thus they are vulnerable to the attack of steganalysis. In this paper, we have proposed a novel method to guarantee the local optimality of modified motion vectors. To modify a motion vector, firstly designate a search area which consists of candidate motion vectors. Second, evaluate the local optimality of each motion vector in the search area to locate all local optimum ones, from which finally select the one contributing least to video compression efficiency degradation as the modified motion vector. Highly undetectable motion vector based video steganography can be developed by combining the proposed method with steganographic codes and reasonable cost assignment. Comparative experimental results have demonstrated that video steganography based on the proposed method is capable of withstanding current best steganalysis while keeping the video compression performance.

Connected through hyperedge HE-1 (induced by source paper "Data Hiding in Motion Vectors of Compressed Video Based on Their Associated Prediction Error"):
  with members:
    - "Quantization Index Modulation Methods for Digital Watermarking and Information Embedding of Multimedia"

Question: Please tell me which research area the center author belongs to. The 4 classes are: Computer science, Mathematics, Engineering, Economics, Psychology, Business. Directly output the class name.

gpt: Computer science