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 "towards secure blockchain enabled internet of vehicles optimizing consensus management using reputation and contract theory"):
  Abstract: In Internet of Vehicles (IoV), data sharing among vehicles is essential to improve driving safety and enhance vehicular services. To ensure data sharing security and traceability, highefficiency Delegated Proof-of-Stake consensus scheme as a hard security solution is utilized to establish blockchain-enabled IoV (BIoV). However, as miners are selected from miner candidates by stake-based voting, it is difficult to defend against voting collusion between the candidates and compromised high-stake vehicles, which introduces serious security challenges to the BIoV. To address such challenges, we propose a soft security enhancement solution including two stages: (i) miner selection and (ii) block verification. In the first stage, a reputation-based voting scheme for the blockchain is proposed to ensure secure miner selection. This scheme evaluates candidates' reputation by using both historical interactions and recommended opinions from other vehicles. The candidates with high reputation are selected to be active miners and standby miners. In the second stage, to prevent internal collusion among the active miners, a newly generated block is further verified and audited by the standby miners. To incentivize the standby miners to participate in block verification, we formulate interactions between the active miners and the standby miners by using contract theory, which takes block verification security and delay into consideration. Numerical results based on a real-world dataset indicate that our schemes are secure and efficient for data sharing in BIoV.

Includes members:
  Member "a survey on consensus mechanisms and mining strategy management in blockchain networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "blockchain consensus algorithms a survey")
  Member "speedychain a framework for decoupling data from blockchain for smart cities":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "dmap a distributed blockchain based framework for online mapping in smart city")
  Member "review of blockchain technology and its expectations case of the energy sector":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "blockchain applications in power systems a bibliometric analysis")
  Member "incentive mechanism design for wireless energy harvesting based internet of things":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "joint power splitting and relay selection in energy harvesting communications for iot networks")
  Member "intelligent vehicle trust point reward based intelligent vehicle communication using blockchain":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "onionchain towards balancing privacy and traceability of blockchain based applications")
  Member "evolutionary game for mining pool selection in blockchain networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a survey on consensus mechanisms and mining strategy management in blockchain networks")
  Member "blockchain based intelligent vehicle data sharing framework":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "onionchain towards balancing privacy and traceability of blockchain based applications")
  Member "decentralized computation offloading game for mobile cloud computing":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "context aware distribution of fog applications using deep reinforcement learning")

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)