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 based combination pufs for device authentication in embedded systems"
  Abstract: Embedded systems play a crucial role in fueling the growth of the Internet-of-Things (IoT) in application domains such as healthcare, home automation, transportation, etc. However, their increasingly network-connected nature, coupled with their ability to access potentially sensitive/confidential information, has given rise to many security and privacy concerns. An additional challenge is the growing number of counterfeit components in these devices, resulting in serious reliability and financial implications. Physically Unclonable Functions (PUFs) are a promising security primitive to help address these concerns. Memory-based PUFs are particularly attractive as they require minimal or no additional hardware for their operation. However, current memory-based PUFs utilize only a single memory technology for constructing the PUF, which has several disadvantages including making them vulnerable to security attacks. In this paper, we propose the design of a new memory-based combination PUF that intelligently combines two memory technologies, SRAM and DRAM, to overcome these shortcomings. The proposed combination PUF exhibits high entropy, supports a large number of challenge-response pairs, and is intrinsically reconfigurable. We have implemented the proposed combination PUF using a Terasic TR4-230 FPGA board and several off-the-shelf SRAMs and DRAMs. Experimental results demonstrate substantial improvements over current memory-based PUFs including the ability to resist various attacks. Extensive authentication tests across a wide temperature range (20 - 60 deg. Celsius) and accelerated aging (12 months) demonstrate the robustness of the proposed design, which achieves a 100% true-positive rate and 0% false-positive rate for authentication across these parameter ranges.

Connected through hyperedge HE-1 (induced by source paper "dataplant in dram security mechanisms for low cost devices"):
  with members:
    - "intrinsic rowhammer pufs leveraging the rowhammer effect for improved security"
    - "ensuring high quality randomness in cryptographic key generation"
    - "internet of things iot a vision architectural elements and future directions"
    - "security through amnesia a software based solution to the cold boot attack on disk encryption"

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)