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: "a first step towards understanding real world attacks on iot devices"
  Abstract: With the rapid growth of Internet of Things (IoT) devices, it is imperative to proactively understand the real-world cybersecurity threats posed to them. This paper describes our initial efforts towards building a honeypot ecosystem as a means to gathering and analyzing real attack data against IoT devices. A primary condition for a honeypot to yield useful insights is to let attackers believe they are real systems used by humans and organizations. IoT devices pose unique challenges in this respect, due to the large variety of device types and the physical-connectedness nature. We thus create a multiphased approach in building a honeypot ecosystem, where researchers can gradually increase a low-interaction honeypot's sophistication in emulating an IoT device by observing real-world attackers' behaviors. We deployed honeypots both on-premise and in the cloud, with associated analysis and vetting infrastructures to ensure these honeypots cannot be easily identified as such and appear to be real systems. In doing so we were able to attract increasingly sophisticated attack data. We present the design of this honeypot ecosystem and our observation on the attack data so far. Our data shows that real-world attackers are explicitly going after IoT devices, and some captured activities seem to involve direct human interaction (as opposed to scripted automatic activities). We also build a low interaction honeypot for IoT cameras, called Honeycamera, that present to attackers seemingly real videos. This is our first step towards building a more comprehensive honeypot ecosystem that will allow researchers to gain concrete understanding of what attackers are going after on IoT devices, so as to more proactively protect them.

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)