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: "sustained space complexity"
  Abstract: Memory-hard functions (MHF) are functions whose evaluation cost is dominated by memory cost. MHFs are egalitarian, in the sense that evaluating them on dedicated hardware (like FPGAs or ASICs) is not much cheaper than on off-the-shelf hardware (like x86 CPUs). MHFs have interesting cryptographic applications, most notably to password hashing and securing blockchains. #R##N#Alwen and Serbinenko [STOC'15] define the cumulative memory complexity (cmc) of a function as the sum (over all time-steps) of the amount of memory required to compute the function. They advocate that a good MHF must have high cmc. Unlike previous notions, cmc takes into account that dedicated hardware might exploit amortization and parallelism. Still, cmc has been critizised as insufficient, as it fails to capture possible time-memory trade-offs, as memory cost doesn't scale linearly, functions with the same cmc could still have very different actual hardware cost. #R##N#In this work we address this problem, and introduce the notion of sustained-memory complexity, which requires that any algorithm evaluating the function must use a large amount of memory for many steps. We construct functions (in the parallel random oracle model) whose sustained-memory complexity is almost optimal: our function can be evaluated using $n$ steps and $O(n/\log(n))$ memory, in each step making one query to the (fixed-input length) random oracle, while any algorithm that can make arbitrary many parallel queries to the random oracle, still needs $\Omega(n/\log(n))$ memory for $\Omega(n)$ steps. #R##N#Our main technical contribution is the construction is a family of DAGs on $n$ nodes with constant indegree with high "sustained-space complexity", meaning that any parallel black-pebbling strategy requires $\Omega(n/\log(n))$ pebbles for at least $\Omega(n)$ steps.

Connected through hyperedge HE-1 (induced by source paper "on locally decodable codes in resource bounded channels"):
  with members:
    - "relaxed locally correctable codes in computationally bounded channels"
    - "high rate locally correctable and locally testable codes with sub polynomial query complexity"
    - "optimal rate code constructions for computationally simple channels"

Connected through hyperedge HE-2 (induced by source paper "approximating cumulative pebbling cost is unique games hard"):
  with members:
    - "on the computational complexity of minimal cumulative cost graph pebbling"
    - "pebble games proof complexity and time space trade offs"

Connected through hyperedge HE-3 (induced by source paper "the gap game"):
  with members:
    - "be selfish and avoid dilemmas fork after withholding faw attacks on bitcoin"
    - "redesigning bitcoin s fee market"
    - "solida a blockchain protocol based on reconfigurable byzantine consensus"
    - "optimal selfish mining strategies in bitcoin"
    - "bitcoin ng a scalable blockchain protocol"
    - "the miner s dilemma"
    - "majority is not enough bitcoin mining is vulnerable"
    - "on bitcoin and red balloons"

Connected through hyperedge HE-4 (induced by source paper "relaxed locally correctable codes in computationally bounded channels"):
  with members:
    - "optimal hashing based time space trade offs for approximate near neighbors"
    - "high rate locally correctable and locally testable codes with sub polynomial query complexity"
    - "optimal rate code constructions for computationally simple channels"
    - "some applications of coding theory in computational complexity"

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)