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 "a new result on the random residue sequence algorithm"):
  Abstract: Random residue sequences (RR) may be used in many random number applications including those related to multiple access in communications. This paper investigates variations on an algorithm to generate RR sequences that was proposed earlier by the author. This makes it possible to obtain many more random sequences than was possible to do by the previous algorithm. Experimental results are presented on a variety of sequences of length 16 and 24. To obtain a variety of RR sequences of a specific length can have obvious applications in cryptography.

Includes members:
  Member "a wireless system using random residue sequences":
    also connected through other hyperedges:
      (none)
  Member "random residue sequences and the number theoretic hilbert transform":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "survey of key distribution schemes for wireless sensor networks")
  Member "new results on the number theoretic hilbert transform":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "memory capacity of neural networks using a circulant weight matrix")
  Member "a class of orthogonal sequences":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a key set cipher for wireless sensor networks")
  Member "the 10 point and 12 point number theoretic hilbert transform":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "memory capacity of neural networks using a circulant weight matrix")
  Member "randomness of d sequences via diehard testing":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "new class of pseudorandom d sequences to generate cryptographic keys")
  Member "the number theoretic hilbert transform":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "memory capacity of neural networks using a circulant weight matrix")

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)