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 "ae gis shielding vulnerable smart contracts against attacks"):
  Abstract: In recent years, smart contracts have suffered major exploits, costing millions of dollars. Unlike traditional programs, smart contracts are deployed on a blockchain. As such, they cannot be modified once deployed. Though various tools have been proposed to detect vulnerable smart contracts, the majority fails to protect vulnerable contracts that have already been deployed on the blockchain. Only very few solutions have been proposed so far to tackle the issue of post-deployment. However, these solutions suffer from low precision and are not generic enough to prevent any type of attack. #R##N#In this work, we introduce AEGIS, a dynamic analysis tool that protects smart contracts from being exploited during runtime. Its capability of detecting new vulnerabilities can easily be extended through so-called attack patterns. These patterns are written in a domain-specific language that is tailored to the execution model of Ethereum smart contracts. The language enables the description of malicious control and data flows. In addition, we propose a novel mechanism to streamline and speed up the process of managing attack patterns. Patterns are voted upon and stored via a smart contract, thus leveraging the benefits of tamper-resistance and transparency provided by the blockchain. We compare AEGIS to current state-of-the-art tools and demonstrate that our solution achieves higher precision in detecting attacks. Finally, we perform a large-scale analysis on the first 4.5 million blocks of the Ethereum blockchain, thereby confirming the occurrences of well reported and yet unreported attacks in the wild.

Includes members:
  Member "slither a static analysis framework for smart contracts":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "smart contract development from the perspective of developers topics and issues discussed on social media")
  Member "soliditycheck quickly detecting smart contract problems through regular expressions":
    also connected through other hyperedges:
      (none)
  Member "harvey a greybox fuzzer for smart contracts":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "attacking the defi ecosystem with flash loans for fun and profit")
  Member "exploiting the laws of order in smart contracts":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "oracle supported dynamic exploit generation for smart contracts")
  Member "finding the greedy prodigal and suicidal contracts at scale":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "an overview on smart contracts challenges advances and platforms")
  Member "contractfuzzer fuzzing smart contracts for vulnerability detection":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "smart contract development from the perspective of developers topics and issues discussed on social media")
  Member "a semantic framework for the security analysis of ethereum smart contracts":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "formalising and verifying smart contracts with solidifier a bounded model checker for solidity")
  Member "towards safer smart contracts a sequence learning approach to detecting security threats":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "on the convergence of artificial intelligence and distributed ledger technology a scoping review and future research agenda")

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)