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 "the art of the scam demystifying honeypots in ethereum smart contracts"):
  Abstract: Modern blockchains, such as Ethereum, enable the execution of so-called smart contracts - programs that are executed across the decentralised blockchain network. As smart contracts become more popular and carry more value, they become more of an interesting target for attackers. In the past few years, several smart contracts have been found to be vulnerable and thus exploited by attackers. However, a new trend towards a more proactive approach seems to be on the rise where attackers do not search for vulnerable contracts anymore. Instead, they try to lure their victims into traps by deploying vulnerable-looking contracts that contain hidden traps. This type of contracts is commonly referred to as honeypots. In this paper, we present the first systematic analysis of honeypots, by investigating their prevalence, behaviour and impact on the Ethereum blockchain. We develop a taxonomy of honeypot techniques and use this to build HONEYBADGER - a tool that employs symbolic execution and well defined heuristics to expose smart contract honeypots. We perform a large-scale analysis of more than 2 million smart contracts and show that our tool not only achieves high precision, but also high scalability. We identify 690 honeypots as well as 240 victims in the wild, with an accumulated profit of more than $90,000 for the honeypot creators. Our manual validation shows that 87% of the reported contracts are indeed honeypots.

Includes members:
  Member "exploiting the laws of order in smart contracts":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "ae gis shielding vulnerable smart contracts against attacks")
  Member "finding the greedy prodigal and suicidal contracts at scale":
    also connected through other hyperedges:
      - Hyperedge HE-2 (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-3 (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-4 (induced by source paper "ae gis shielding vulnerable smart contracts against attacks")
  Member "data mining for detecting bitcoin ponzi schemes":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "an overview on smart contracts challenges advances and platforms")
  Member "towards safer smart contracts a sequence learning approach to detecting security threats":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on the convergence of artificial intelligence and distributed ledger technology a scoping review and future research agenda")
  Member "towards safer smart contracts a sequence learning approach to detecting vulnerabilities":
    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")
  Member "vandal a scalable security analysis framework for smart contracts":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "an overview on smart contracts challenges advances and platforms")

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)