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: "an algorithm to find optimal attack paths in nondeterministic scenarios"
  Abstract: As penetration testing frameworks have evolved and have become more complex, the problem of controlling automatically the pentesting tool has become an important question. This can be naturally addressed as an attack planning problem. Previous approaches to this problem were based on modeling the actions and assets in the PDDL language, and using off-the-shelf AI tools to generate attack plans. These approaches however are limited. In particular, the planning is classical (the actions are deterministic) and thus not able to handle the uncertainty involved in this form of attack planning. We herein contribute a planning model that does capture the uncertainty about the results of the actions, which is modeled as a probability of success of each action. We present efficient planning algorithms, specifically designed for this problem, that achieve industrial-scale runtime performance (able to solve scenarios with several hundred hosts and exploits). These algorithms take into account the probability of success of the actions and their expected cost (for example in terms of execution time, or network traffic generated). We thus show that probabilistic attack planning can be solved efficiently for the scenarios that arise when assessing the security of large networks. Two "primitives" are presented, which are used as building blocks in a framework separating the overall problem into two levels of abstraction. We also present the experimental results obtained with our implementation, and conclude with some ideas for further work.

Connected through hyperedge HE-1 (induced by source paper "autonomous intelligent cyber defense agent aica reference architecture release 2 0"):
  with members:
    - "initial reference architecture of an intelligent autonomous agent for cyber defense"
    - "toward intelligent autonomous agents for cyber defense report of the 2017 workshop by the north atlantic treaty organization nato research group ist 152 rtg"
    - "deep models under the gan information leakage from collaborative deep learning"
    - "pomdps make better hackers accounting for uncertainty in penetration testing"
    - "playing atari with deep reinforcement learning"
    - "stackelberg vs nash in security games an extended investigation of interchangeability equivalence and uniqueness"

Connected through hyperedge HE-2 (induced by source paper "towards automated network mitigation analysis extended"):
  with members:
    - "pomdps make better hackers accounting for uncertainty in penetration testing"
    - "attack planning in the real world"
    - "stackelberg vs nash in security games an extended investigation of interchangeability equivalence and uniqueness"
    - "on line planning and scheduling an application to controlling modular printers"
    - "the fast downward planning system"
    - "the ff planning system fast plan generation through heuristic search"
    - "the computational complexity of probabilistic planning"

Connected through hyperedge HE-3 (induced by source paper "pomdps make better hackers accounting for uncertainty in penetration testing"):
  with members:
    - "penetration testing pomdp solving"
    - "attack planning in the real world"
    - "policy contingent abstraction for robust robot control"
    - "the metric ff planning system translating ignoring delete lists to numeric state variables"

Connected through hyperedge HE-4 (induced by source paper "les pomdp font de meilleurs hackers tenir compte de l incertitude dans les tests de penetration"):
  with members:
    - "penetration testing pomdp solving"
    - "attack planning in the real world"
    - "policy contingent abstraction for robust robot control"
    - "the metric ff planning system translating ignoring delete lists to numeric state variables"

Connected through hyperedge HE-5 (induced by source paper "penetration testing pomdp solving"):
  with members:
    - "attack planning in the real world"
    - "deterministic pomdps revisited"

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)