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: "quantitative information flow for scheduler dependent systems"
  Abstract: Quantitative information flow analyses measure how much information on secrets is leaked by publicly observable outputs. One area of interest is to quantify and estimate the information leakage of composed systems. Prior work has focused on running disjoint component systems in parallel and reasoning about the leakage compositionally, but has not explored how the component systems are run in parallel or how the leakage of composed systems can be minimised. In this paper we consider the manner in which parallel systems can be combined or scheduled. This considers the effects of scheduling channels where resources may be shared, or whether the outputs may be incrementally observed. We also generalise the attacker's capability, of observing outputs of the system, to consider attackers who may be imperfect in their observations, e.g. when outputs may be confused with one another, or when assessing the time taken for an output to appear. Our main contribution is to present how scheduling and observation effect information leakage properties. In particular, that scheduling can hide some leaked information from perfect observers, while some scheduling may reveal secret information that is hidden to imperfect observers. In addition we present an algorithm to construct a scheduler that minimises the min-entropy leakage and min-capacity in the presence of any observer.

Connected through hyperedge HE-1 (induced by source paper "quantitative aspects of programming languages and systems over the past 2 4 years and beyond"):
  with members:
    - "paws a tool for the analysis of weighted systems"
    - "divide and conquer variable set separation in hybrid systems reachability analysis"
    - "logical characterization of trace metrics"
    - "design and optimisation of the flyfast front end for attribute based coordination"
    - "language based abstractions for dynamical systems"
    - "limit your consumption finding bounds in average energy games"
    - "mela modelling in ecology with location attributes"
    - "logical characterization of bisimulation metrics"

Connected through hyperedge HE-2 (induced by source paper "hybrid statistical estimation of mutual information and its application to information flow"):
  with members:
    - "what s the over under probabilistic bounds on information leakage"
    - "a game theoretic approach to information flow control via protocol composition"
    - "information leakage games"
    - "on the compositionality of quantitative information flow"
    - "speeding up smt based quantitative program analysis"
    - "a scalable approximate model counter"
    - "quantitative information flow as safety and liveness hyperproperties"

Connected through hyperedge HE-3 (induced by source paper "quantifying information flow in interactive systems"):
  with members:
    - "widths of regular and context free languages"
    - "quantitative information flow under generic leakage functions and adaptive adversaries"

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)