human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "detecting token systems on ethereum"
  Abstract: We propose and compare two approaches to identify smart contracts as token systems by analyzing their public bytecode. The first approach symbolically executes the code in order to detect token systems by their characteristic behavior of updating internal accounts. The second approach serves as a comparison base and exploits the common interface of ERC-20, the most popular token standard. We present quantitative results for the Ethereum blockchain, and validate the effectiveness of both approaches using a set of curated token systems as ground truth. We observe 100% recall for the second approach. Recall rates of 89% (with well explainable missed detections) indicate that the first approach may also be able to identify "hidden" or undocumented token systems that intentionally do not implement the standard. One possible application of the proposed methods is to facilitate regulator' tasks of monitoring and policing the use of token systems and their underlying platforms.

Connected through hyperedge HE-1 (induced by source paper "a true concurrent model of smart contracts executions"):
  with members:
    - "a minimal core calculus for solidity contracts"
    - "verisolid correct by design smart contracts for ethereum"
    - "scilla a smart contract intermediate level language"
    - "a semantic framework for the security analysis of ethereum smart contracts"
    - "hyperledger fabric a distributed operating system for permissioned blockchains"
    - "an efficient framework for optimistic concurrent execution of smart contracts"
    - "securify practical security analysis of smart contracts"
    - "designing secure ethereum smart contracts a finite state machine based approach"

Connected through hyperedge HE-2 (induced by source paper "truffle tests for free replaying ethereum smart contracts for transparency"):
  with members:
    - "probabilistic smart contracts secure randomness on the blockchain"
    - "finding the greedy prodigal and suicidal contracts at scale"
    - "contractfuzzer fuzzing smart contracts for vulnerability detection"
    - "rethinking blockchain security position paper"
    - "securify practical security analysis of smart contracts"
    - "new kids on the block an analysis of modern blockchains"

Connected through hyperedge HE-3 (induced by source paper "the operational cost of ethereum airdrops"):
  with members:
    - "flash boys 2 0 frontrunning transaction reordering and consensus instability in decentralized exchanges"
    - "airdrops and privacy a case study in cross blockchain analysis"
    - "an adaptive gas cost mechanism for ethereum to defend against under priced dos attacks"
    - "under optimized smart contracts devour your money"

Connected through hyperedge HE-4 (induced by source paper "resolving the multiple withdrawal attack on erc20 tokens"):
  with members:
    - "sok transparent dishonesty front running attacks on blockchain"
    - "the ico phenomenon and its relationships with ethereum smart contract environment"

Question: Please tell me which class the center node 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)