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: "attacks and countermeasures in fingerprint based biometric cryptosystems"
  Abstract: We investigate implementations of biometric cryptosystems protecting fingerprint templates (which are mostly based on the fuzzy vault scheme by Juels and Sudan in 2002) with respect to the security they provide. We show that attacks taking advantage of the system's false acceptance rate, i.e. false-accept attacks, pose a very serious risk --- even if brute-force attacks are impractical to perform. Our observations lead to the clear conclusion that currently a single fingerprint is not sufficient to provide a secure biometric cryptosystem. But there remain other problems that can not be resolved by merely switching to multi-finger: Kholmatov and Yanikoglu in 2007 demonstrated that it is possible to break two matching vault records at quite a high rate via the correlation attack. #R##N#We propose an implementation of a minutiae fuzzy vault that is inherently resistant against cross-matching and the correlation attack. Surprisingly, achieving cross-matching resistance is not at the cost of authentication performance. In particular, we propose to use a randomized decoding procedure and find that it is possible to achieve a GAR=91% at which no false accepts are observed on a database generally used. Our ideas can be adopted into an implementation of a multibiometric cryptosystem. All experiments described in this paper can fully be reproduced using software available for download.

Connected through hyperedge HE-1 (induced by source paper "security of the improved fuzzy vault scheme in the presence of record multiplicity full version"):
  with members:
    - "performance of the fuzzy vault for multiple fingerprints extended version"
    - "fuzzy extractors how to generate strong keys from biometrics and other noisy data"
    - "maximum likelihood decoding of reed solomon codes is np hard"

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)