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: "teaching hardware reverse engineering educational guidelines and practical insights"
  Abstract: Since underlying hardware components form the basis of trust in virtually any computing system, security failures in hardware pose a devastating threat to our daily lives. Hardware reverse engineering is commonly employed by security engineers in order to identify security vulnerabilities, to detect IP violations, or to conduct very-large-scale integration (VLSI) failure analysis. Even though industry and the scientific community demand experts with expertise in hardware reverse engineering, there is a lack of educational offerings, and existing training is almost entirely unstructured and on the job. To the best of our knowledge, we have developed the first course to systematically teach students hardware reverse engineering based on insights from the fields of educational research, cognitive science, and hardware security. The contribution of our work is threefold: (1) we propose underlying educational guidelines for practice-oriented courses which teach hardware reverse engineering; (2) we develop such a lab course with a special focus on gate-level netlist reverse engineering and provide the required tools to support it; (3) we conduct an educational evaluation of our pilot course. Based on our results, we provide valuable insights on the structure and content necessary to design and teach future courses on hardware reverse engineering.

Connected through hyperedge HE-1 (induced by source paper "highway to hal open sourcing the first extendable gate level netlist reverse engineering framework"):
  with members:
    - "insights into the mind of a trojan designer the challenge to integrate a trojan into the bitstream"
    - "towards cognitive obfuscation impeding hardware reverse engineering based on psychological insights"
    - "a look at the dark side of hardware reverse engineering a case study"
    - "hardware reverse engineering overview and open challenges"

Connected through hyperedge HE-2 (induced by source paper "towards cognitive obfuscation impeding hardware reverse engineering based on psychological insights"):
  with members:
    - "a look at the dark side of hardware reverse engineering a case study"
    - "hardware reverse engineering overview and open challenges"

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)