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 "hydras and ipfs a decentralised playground for malware"):
  Abstract: Modern malware can take various forms, and has reached a very high level of sophistication in terms of its penetration, persistence, communication and hiding capabilities. The use of cryptography, and of covert communication channels over public and widely used protocols and services, is becoming a norm. In this work, we start by introducing Resource Identifier Generation Algorithms. These are an extension of a well-known mechanism called Domain Generation Algorithms, which are frequently employed by cybercriminals for bot management and communication. Our extension allows, beyond DNS, the use of other protocols. More concretely, we showcase the exploitation of the InterPlanetary file system (IPFS). This is a solution for the "permanent web", which enjoys a steadily growing community interest and adoption. The IPFS is, in addition, one of the most prominent solutions for blockchain storage. We go beyond the straightforward case of using the IPFS for hosting malicious content, and explore ways in which a botmaster could employ it, to manage her bots, validating our findings experimentally. Finally, we discuss the advantages of our approach for malware authors, its efficacy and highlight its extensibility for other distributed storage services.

Includes members:
  Member "detecting dga domains with recurrent neural networks and side information":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "inline detection of dga domains using side information")
  Member "a survey on malicious domains detection through dns data analysis":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "encrypted and covert dns queries for botnets challenges and countermeasures")
  Member "developing a k ary malware using blockchain":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "ransomware as a service using smart contracts and ipfs")
  Member "deepdga adversarially tuned domain generation and detection":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "inline detection of dga domains using side information")
  Member "ipfs content addressed versioned p2p file system":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "are distributed ledger technologies ready for smart transportation systems")

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)