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: "bitcoin transaction graph analysis"
  Abstract: Bitcoins have recently become an increasingly popular cryptocurrency through which users trade electronically and more anonymously than via traditional electronic transfers. Bitcoin's design keeps all transactions in a public ledger. The sender and receiver for each transaction are identified only by cryptographic public-key ids. This leads to a common misconception that it inherently provides anonymous use. While Bitcoin's presumed anonymity offers new avenues for commerce, several recent studies raise user-privacy concerns. We explore the level of anonymity in the Bitcoin system. Our approach is two-fold: (i) We annotate the public transaction graph by linking bitcoin public keys to "real" people - either definitively or statistically. (ii) We run the annotated graph through our graph-analysis framework to find and summarize activity of both known and unknown users.

Connected through hyperedge HE-1 (induced by source paper "characterizing eosio blockchain"):
  with members:
    - "evulhunter detecting fake transfer vulnerabilities for eosio s smart contracts at webassembly level"
    - "characterizing code clones in the ethereum smart contract ecosystem"
    - "contractfuzzer fuzzing smart contracts for vulnerability detection"
    - "securify practical security analysis of smart contracts"
    - "deanonymisation of clients in bitcoin p2p network"

Connected through hyperedge HE-2 (induced by source paper "a prevention and a traction system for ransomware attacks"):
  with members:
    - "ransomware payments in the bitcoin ecosystem"

Connected through hyperedge HE-3 (induced by source paper "predictive analysis of bitcoin price considering social sentiments"):
  with members:
    - "on the properties of neural machine translation encoder decoder approaches"

Connected through hyperedge HE-4 (induced by source paper "exploring the attack surface of blockchain a systematic overview"):
  with members:
    - "scalable byzantine consensus via hardware assisted secret sharing"
    - "security services using blockchains a state of the art survey"
    - "a survey on the security of blockchain systems"
    - "an empirical analysis of anonymity in zcash"
    - "towards blockchain driven secure and transparent audit logs"
    - "end to end analysis of in browser cryptojacking"
    - "linbft linear communication byzantine fault tolerance for public blockchains"
    - "a survey on security and privacy issues of bitcoin"

Connected through hyperedge HE-5 (induced by source paper "empirically analyzing ethereum s gas mechanism"):
  with members:
    - "an empirical study of speculative concurrency in ethereum smart contracts"
    - "decentralization in bitcoin and ethereum networks"
    - "an efficient framework for optimistic concurrent execution of smart contracts"
    - "chainspace a sharded smart contracts platform"
    - "adding concurrency to smart contracts"
    - "an empirical analysis of smart contracts platforms applications and design patterns"
    - "new kids on the block an analysis of modern blockchains"
    - "optimal selfish mining strategies in bitcoin"

Connected through hyperedge HE-6 (induced by source paper "blockchain mutability challenges and proposed solutions"):
  with members:
    - "redactable blockchain in the permissionless setting"
    - "mof bc a memory optimized and flexible blockchain for large scale networks"
    - "blockchains consensus protocols in the wild"
    - "when the cookie meets the blockchain privacy risks of web payments via cryptocurrencies"
    - "an empirical analysis of smart contracts platforms applications and design patterns"
    - "enigma decentralized computation platform with guaranteed privacy"
    - "deanonymisation of clients in bitcoin p2p network"

Connected through hyperedge HE-7 (induced by source paper "cascading machine learning to attack bitcoin anonymity"):
  with members:
    - "characterizing entities in the bitcoin blockchain"
    - "data mining for detecting bitcoin ponzi schemes"
    - "anomaly detection in bitcoin network using unsupervised learning methods"
    - "deanonymisation of clients in bitcoin p2p network"
    - "traveling the silk road a measurement analysis of a large anonymous online marketplace"

Connected through hyperedge HE-8 (induced by source paper "bitcoinheist topological data analysis for ransomware detection on the bitcoin blockchain"):
  with members:
    - "ransomware payments in the bitcoin ecosystem"
    - "obfuscation in bitcoin techniques and politics"
    - "xgboost a scalable tree boosting system"

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)