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 survey on zero knowledge range proofs and applications"):
  Abstract: In last years, there has been an increasing effort to leverage Distributed Ledger Technology (DLT), including blockchain. One of the main topics of interest, given its importance, is the research and development of privacy mechanisms, as for example is the case of Zero Knowledge Proofs (ZKP). ZKP is a cryptographic technique that can be used to hide information that is put into the ledger, while still allowing to perform validation of this data. In this work we describe different strategies to construct Zero Knowledge Range Proofs (ZKRP), as for example the scheme proposed by Boudot in 2001; the one proposed in 2008 by Camenisch et al, and Bulletproofs, proposed in 2017. We also compare these strategies and discuss possible use cases. Since Bulletproofs is the most efficient construction, we will give a detailed description of its algorithms and optimizations. Bulletproofs is not only more efficient than previous schemes, but also avoids the trusted setup, which is a requirement that is not desirable in the context of Distributed Ledger Technology (DLT) and blockchain. In case of cryptocurrencies, if the setup phase is compromised, it would be possible to generate money out of thin air. Interestingly, Bulletproofs can also be used to construct generic Zero Knowledge Proofs (ZKP), in the sense that it can be used to prove generic statements, and thus it is not only restricted to ZKRP, but it can be used for any kind of Proof of Knowledge (PoK). Hence Bulletproofs leads to a more powerful tool to provide privacy for DLT. Here we describe in detail the algorithms involved in Bulletproofs protocol for ZKRP. Also, we present our implementation, which was open sourced.

Includes members:
  Member "sgxpectre stealing intel secrets from sgx enclaves via speculative execution":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "distributed systems and trusted execution environments trade offs and challenges")
  Member "malware guard extension using sgx to conceal cache attacks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "copycat controlled instruction level attacks on enclaves for maximal key extraction")

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)