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: "precise attack synthesis for smart contracts"
  Abstract: Smart contracts are programs running on top of blockchain platforms. They interact with each other through well-defined interfaces to perform financial transactions in a distributed system with no trusted third parties. But these interfaces also provide a favorable setting for attackers, who can exploit security vulnerabilities in smart contracts to achieve financial gain. #R##N#This paper presents SmartScopy, a system for automatic synthesis of adversarial contracts that identify and exploit vulnerabilities in a victim smart contract. Our tool explores the space of \emph{attack programs} based on the Application Binary Interface (ABI) specification of a victim smart contract in the Ethereum ecosystem. To make the synthesis tractable, we introduce \emph{summary-based symbolic evaluation}, which significantly reduces the number of instructions that our synthesizer needs to evaluate symbolically, without compromising the precision of the vulnerability query. Building on the summary-based symbolic evaluation, SmartScopy further introduces a novel approach for partitioning the synthesis search space for parallel exploration, as well as a lightweight deduction technique that can prune infeasible candidates earlier. We encoded common vulnerabilities of smart contracts in our query language, and evaluated SmartScopy on the entire data set from etherscan with $>$25K smart contracts. Our experiments demonstrate the benefits of summary-based symbolic evaluation and show that SmartScopy outperforms two state-of-the-art smart contracts analyzers, Oyente and Contractfuzz, in terms of running time, precision, and soundness. Furthermore, running on recent popular smart contracts, SmartScopy uncovers 20 vulnerable smart contracts that contain the recent BatchOverflow vulnerability and cannot be precisely detected by existing tools.

Connected through hyperedge HE-1 (induced by source paper "oracle supported dynamic exploit generation for smart contracts"):
  with members:
    - "exploiting the laws of order in smart contracts"
    - "finding the greedy prodigal and suicidal contracts at scale"
    - "sereum protecting existing smart contracts against re entrancy attacks"
    - "quantitative analysis of smart contracts"
    - "evaluating fuzz testing"
    - "contractfuzzer fuzzing smart contracts for vulnerability detection"
    - "learning inputs in greybox fuzzing"
    - "towards safer smart contracts a survey of languages and verification methods"

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)