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 "on incentive compatible role based reward distribution in algorand"):
  Abstract: Algorand is a recent, open-source public or permissionless blockchain system that employs a novel proof-of-stake byzantine consensus protocol to efficiently scale the distributed transaction agreement problem to billions of users. In addition to being more democratic and energy-efficient, compared to popular protocols such as Bitcoin, Algorand also touts a much high transaction throughput. This paper is the first attempt in the literature to study and address this problem. By carefully modeling the participation costs and rewards received within a strategic interaction scenario, we first empirically show that even a small number of nodes defecting to participate in the protocol tasks due to insufficiency of the available incentives can result in the Algorand network failing to compute and add new blocks of transactions. We further show that this effect can be formalized by means of a mathematical model of interaction in Algorand given its participation costs and the current (or planned) reward distribution/sharing approach envisioned by the Algorand Foundation. Specifically, on analyzing this game model we observed that mutual cooperation under the currently proposed reward sharing approach is not a Nash equilibrium. This is a significant result which could threaten the success of an otherwise robust distributed consensus mechanism. We propose a novel reward sharing approach for Algorand and formally show that it is incentive-compatible, i.e., it can guarantee cooperation within a group of selfish Algorand users. Extensive numerical and Algorand simulation results further confirm our analytical findings. Moreover, these results show that for a given distribution of stakes in the network, our reward sharing approach can guarantee cooperation with a significantly smaller reward per round.

Includes members:
  Member "be selfish and avoid dilemmas fork after withholding faw attacks on bitcoin":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "exploring the attack surface of blockchain a systematic overview")
  Member "blockchain mining games":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on the feasibility of sybil attacks in shard based permissionless blockchains")
  Member "algorand the efficient and democratic ledger":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "consistency of proof of stake blockchains with concurrent honest slot leaders")
  Member "bitcoin ng a scalable blockchain protocol":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "surface a practical blockchain consensus algorithm for real world networks")
  Member "on subversive miner strategies and block withholding attack in bitcoin digital currency":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "exploring the attack surface of blockchain a systematic overview")
  Member "the miner s dilemma":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "surface a practical blockchain consensus algorithm for real world networks")
  Member "analysis of bitcoin pooled mining reward systems":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "cryptomining makes noise a machine learning approach for cryptojacking detection")

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)