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: "triad nvm persistent security for integrity protected and encrypted non volatile memories nvms"
  Abstract: Emerging Non-Volatile Memories (NVMs) are promising contenders for building future memory systems. On the other side, unlike DRAM systems, NVMs can retain data even after power loss and thus enlarge the attack surface. While data encryption and integrity verification have been proposed earlier for DRAM systems, protecting and recovering secure memories becomes more challenging with persistent memory. Specifically, security metadata, e.g., encryption counters and Merkle Tree data, should be securely persisted and recovered across system reboots and during recovery from crashes. Not persisting updates to security metadata can lead to data inconsistency, in addition to serious security vulnerabilities. #R##N#In this paper, we pioneer a new direction that explores persistency of both Merkle Tree and encryption counters to enable secure recovery of data-verifiable and encrypted memory systems. To this end, we coin a new concept that we call Persistent-Security. We discuss the requirements for such persistently secure systems, propose novel optimizations, and evaluate the impact of the proposed relaxation schemes and optimizations on performance, resilience and recovery time. To the best of our knowledge, our paper is the first to discuss the persistence of security metadata in integrity-protected NVM systems and provide corresponding optimizations. We define a set of relaxation schemes that bring trade-offs between performance and recovery time for large capacity NVM systems. Our results show that our proposed design, Triad-NVM, can improve the throughput by an average of ~2x (relative to strict persistence). Moreover, Triad-NVM maintains a recovery time of less than 4 seconds for an 8TB NVM system (30.6 seconds for 64TB), which is ~3648x faster than a system without security metadata persistence.

Connected through hyperedge HE-1 (induced by source paper "streamlining integrity tree updates for secure persistent non volatile memory"):
  with members:
    - "pangolin a fault tolerant persistent memory programming library"
    - "let the cloud watch over your iot file systems"
    - "the parallel persistent memory model"

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.DC(Distributed, Parallel, and Cluster Computing)