human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "the good the bad and the ugly evaluation of wi fi steganography"
  Abstract: In this paper we propose a new method for the evaluation of network steganography algorithms based on the new concept of "the moving observer". We considered three levels of undetectability named: "good", "bad", and "ugly". To illustrate this method we chose Wi-Fi steganography as a solid family of information hiding protocols. We present the state of the art in this area covering well-known hiding techniques for 802.11 networks. "The moving observer" approach could help not only in the evaluation of steganographic algorithms, but also might be a starting point for a new detection system of network steganography. The concept of a new detection system, called MoveSteg, is explained in detail.

Connected through hyperedge HE-1 (induced by source paper "socialstegdisc application of steganography in social networks to create a file system"):
  with members:
    - "steghash new method for information hiding in open social networks"
    - "using facebook for image steganography"

Connected through hyperedge HE-2 (induced by source paper "steghash new method for information hiding in open social networks"):
  with members:
    - "stegibiza new method for information hiding in club music"
    - "using facebook for image steganography"
    - "trustmas trusted communication platform for multi agent systems"

Connected through hyperedge HE-3 (induced by source paper "movesteg a method of network steganography detection"):
  with members:
    - "on steganography in lost audio packets"
    - "using transcoding for hidden communication in ip telephony"
    - "information hiding using improper frame padding"

Question: Please tell me which class the center node belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.MM(Multimedia)