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: "outrepasser les limites des techniques classiques de prise d empreintes grace aux reseaux de neurones"
  Abstract: We present an application of Artificial Intelligence techniques to the field of Information Security. The problem of remote Operating System (OS) Detection, also called OS Fingerprinting, is a crucial step of the penetration testing process, since the attacker (hacker or security professional) needs to know the OS of the target host in order to choose the exploits that he will use. OS Detection is accomplished by passively sniffing network packets and actively sending test packets to the target host, to study specific variations in the host responses revealing information about its operating system. #R##N#The first fingerprinting implementations were based on the analysis of differences between TCP/IP stack implementations. The next generation focused the analysis on application layer data such as the DCE RPC endpoint information. Even though more information was analyzed, some variation of the "best fit" algorithm was still used to interpret this new information. Our new approach involves an analysis of the composition of the information collected during the OS identification process to identify key elements and their relations. To implement this approach, we have developed tools using Neural Networks and techniques from the field of Statistics. These tools have been successfully integrated in a commercial software (Core Impact).

Connected through hyperedge HE-1 (induced by source paper "simulation of computer network attacks"):
  with members:
    - "building computer network attacks"

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.CR(Cryptography and Security)