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: "bobtail a proof of work target that minimizes blockchain mining variance draft"
  Abstract: Blockchain systems are designed to produce blocks at a constant average rate. The most popular systems currently employ a Proof of Work (PoW) algorithm as a means of creating these blocks. Bitcoin produces, on average, one block every 10 minutes. An unfortunate limitation of all deployed PoW blockchain systems is that the time between blocks has high variance. For example, 5% of the time, Bitcoin's inter-block time is at least 40 minutes. This variance impedes the consistent flow of validated transactions through the system. We propose an alternative process for PoW-based block discovery that results in an inter-block time with significantly lower variance. Our algorithm, called Bobtail, generalizes the current algorithm by comparing the mean of the k lowest order statistics to a target. We show that the variance of inter-block times decreases as k increases. If our approach were applied to Bitcoin, about 80% of blocks would be found within 7 to 12 minutes, and nearly every block would be found within 5 to 18 minutes; the average inter-block time would remain at 10 minutes. Further, we show that low-variance mining significantly thwarts doublespend and selfish mining attacks. For Bitcoin and Ethereum currently (k=1), an attacker with 40% of the mining power will succeed with 30% probability when the merchant sets up an embargo of 8 blocks; however, when k>=20, the probability of success falls to less than 1%. Similarly, for Bitcoin and Ethereum currently, a selfish miner with 40% of the mining power will claim about 66% of blocks; however, when k>=5, the same miner will find that selfish mining is less successful than honest mining. The cost of our approach is a larger block header.

Connected through hyperedge HE-1 (induced by source paper "hotpow finality from proof of work quorums"):
  with members:
    - "all that glitters is not bitcoin unveiling the centralized nature of the btc ip network"
    - "squirrl automating attack discovery on blockchain incentive mechanisms with deep reinforcement learning"
    - "the consensus number of a cryptocurrency"
    - "txprobe discovering bitcoin s network topology using orphan transactions"
    - "consensus in the age of blockchains"
    - "hijacking bitcoin routing attacks on cryptocurrencies"
    - "blockchain mining games"
    - "enhancing bitcoin security and performance with strong consistency via collective signing"

Connected through hyperedge HE-2 (induced by source paper "bonded mining difficulty adjustment by miner commitment"):
  with members:
    - "bitcoin vs bitcoin cash coexistence or downfall of bitcoin cash"
    - "estimation of miner hash rates and consensus on blockchains draft"
    - "enhancing bitcoin security and performance with strong consistency via collective signing"
    - "bitcoin meets strong consistency"
    - "cryptocurrencies without proof of work"
    - "majority is not enough bitcoin mining is vulnerable"

Connected through hyperedge HE-3 (induced by source paper "an axiomatic approach to block rewards"):
  with members:
    - "blockchain mining games"
    - "optimal selfish mining strategies in bitcoin"
    - "majority is not enough bitcoin mining is vulnerable"

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)