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: "new attacks and defenses for randomized caches"
  Abstract: The last level cache is vulnerable to timing based side channel attacks because it is shared by the attacker and the victim processes even if they are located on different cores. These timing attacks evict the victim cache lines using small conflict groups(SCG), and monitor the cache to observe when the victim uses these cache lines again. A conflict group is a collection of cache lines which will evict the target cache line. Randomization is often used by defenses to prevent creation of SCGs. #R##N#We introduce new attacks to demonstrate that the current randomization schemes require an extremely high refresh rate to be secure, on average a 15\% performance overhead, and upto 50\% in the worst case. Next, we propose a new randomization strategy using an indirection table, which mitigates this issue. Addresses of cache lines are encrypted and used to lookup the indirection table entry. Each indirection table entry stores a mapping to a randomly chosen cache set. The cache line is placed into this randomly chosen set. The encryption key changes upto 50x faster than CEASER's default rate, by using evictions to trigger the re-randomization. Instead of moving cache lines, this mechanism re-randomizes one iTable entry at a time, whenever the cache lines corresponding to the iTable entry are naturally evicted. Thus, the miss rate is not much worse than the baseline. #R##N#We quantitatively show that our scheme does almost as well as a fully associative cache to defend against these attacks. We also demonstrate new attacks that target the iTable by oversubscribing its entries, and quantitatively show that our scheme is resilient against new attacks for trillions of years. We estimate low area ( < 7\%) and power overhead compared to a baseline inclusive last-level cache. Lastly, we evaluate a low performance overhead (<4%) using the SPECrate 2017 and PARSEC 3.0 benchmarks.

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)