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: "memory dos attacks in multi tenant clouds severity and mitigation"
  Abstract: Memory DoS attacks are Denial of Service (or Degradation of Service) attacks caused by contention for hardware memory resources. In cloud computing, these availability breaches are serious security threats that occur despite the strong memory isolation techniques for Virtual Machines (VMs), enforced by the software virtualization layer. The underlying hardware memory layers are still shared by the VMs and can be exploited by a clever attacker in a hostile VM co-located on the same server as the victim VM. While memory contention has been studied in past work, the severity of contention on different levels of the memory hierarchy has not been systematically studied, as we do in this paper. We identify design vulnerabilities and show how memory DoS attacks can be constructed. We also show how a malicious cloud customer can mount low-cost attacks, using just a few co-located hostile VMs to cause severe performance degradation for a distributed application, Hadoop, consisting of multiple victim VMs, and 38X delay in response time for an E-commerce website. We show a new defense system for these memory DoS attacks, using a statistical metric based on performance counter measurements. We implement a full prototype of this defense architecture on the OpenStack cloud system.

Connected through hyperedge HE-1 (induced by source paper "undermining user privacy on mobile devices using ai"):
  with members:
    - "deepcloak adversarial crafting as a defensive measure to cloak processes"
    - "theory and practice of finding eviction sets"
    - "loophole timing attacks on shared event loops in chrome"
    - "perfweb how to violate web privacy with hardware performance events"
    - "autolock why cache attacks on arm are harder than you think"
    - "flush flush a fast and stealthy cache attack"
    - "tensorflow a system for large scale machine learning"
    - "flush flush a fast and stealthy cache attack"

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)