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 "an optimized pattern recognition algorithm for anomaly detection in iot environment"):
  Abstract: With the advent of large-scale heterogeneous search engines comes the problem of unified search control resulting in mismatches that could have otherwise avoided. A mechanism is needed to determine exact patterns in web mining and ubiquitous device searching. In this paper we demonstrate the use of an optimized string searching algorithm to recognize exact patterns from a large database. The underlying principle in designing the algorithm is that each letter that maps to a fixed real values and some arithmetic operations which are applied to compute corresponding pattern and substring values. We have implemented this algorithm in C. We have tested the algorithm using a large dataset. We created our own dataset using DNA sequences. The experimental result shows the number of mismatch occurred in string search from a large database. Furthermore, some of the inherent weaknesses in the use of this algorithm are highlighted.

Includes members:
  Member "improved parallel rabin karp algorithm using compute unified device architecture":
    also connected through other hyperedges:
      (none)
  Member "string matching with multicore cpus performing better with the aho corasick algorithm":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "analyzing large scale dna sequences on multi core architectures")

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)