human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "on the security of non linear hb nlhb protocol against passive attack"):
  Abstract: As a variant of the HB authentication protocol for RFID systems, which relies on the complexity of decoding linear codes against passive attacks, Madhavan et al. presented Non-Linear HB(NLHB) protocol. In contrast to HB, NLHB relies on the complexity of decoding a class of non-linear codes to render the passive attacks proposed against HB ineffective. Based on the fact that there has been no passive solution for the problem of decoding a random non-linear code, the authors have claimed that NLHB’s security margin is very close to its key size. In this paper, we show that passive attacks against HB protocol can still be applicable to NLHB and this protocol does not provide the desired security margin. In our attack, we first linearize the non-linear part of NLHB to obtain a HB equivalent for NLHB, and then exploit the passive attack techniques proposed for the HB to evaluate the security margin of NLHB. The results show that although NLHB’s security margin is relatively higher than HB against similar passive attack techniques, it has been overestimated and, in contrary to what is claimed, NLHB is vulnerable to passive attacks against HB, especially when the noise vector in the protocol has a low weight.

Includes members:
  Member "crossing borders security and privacy issues of the european e passport":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "practical attacks on a rfid authentication protocol conforming to epc c 1 g 2 standard")
  Member "trusted hb a low cost version of hb secure against man in the middle attacks":
    also connected through other hyperedges:
      (none)
  Member "noise tolerant learning the parity problem and the statistical query model":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "combating noisy labels by agreement a joint training method with co regularization")

Question: Please tell me which class the source paper 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)