human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "tbt targeted neural network attack with bit trojan"):
  Abstract: Security of modern Deep Neural Networks (DNNs) is under severe scrutiny as the deployment of these models become widespread in many intelligence-based applications. Most recently, DNNs are attacked through Trojan which can effectively infect the model during the training phase and get activated only through specific input patterns (i.e, trigger) during inference. However, in this work, for the first time, we propose a novel Targeted Bit Trojan(TBT), which eliminates the need for model re-training to insert the targeted Trojan. Our algorithm efficiently generates a trigger specifically designed to locate certain vulnerable bits of DNN weights stored in main memory (i.e., DRAM). The objective is that once the attacker flips these vulnerable bits, the network still operates with normal inference accuracy. However, when the attacker activates the trigger embedded with input images, the network classifies all the inputs to a certain target class. We demonstrate that flipping only several vulnerable bits founded by our method, using available bit-flip techniques (i.e, row-hammer), can transform a fully functional DNN model into a Trojan infected model. We perform extensive experiments of CIFAR-10, SVHN and ImageNet datasets on both VGG-16 and Resnet-18 architectures. Our proposed TBT could classify 93% of the test images to a target class with as little as 82 bit-flips out of 88 million weight bits on Resnet-18 for CIFAR10 dataset.

Includes members:
  Member "terminal brain damage exposing the graceless degradation in deep neural networks under hardware fault attacks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "sniff reverse engineering of neural networks with fault attacks")
  Member "bit flip attack crushing neural network with progressive bit search":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "functional error correction for robust neural networks")
  Member "detecting backdoor attacks on deep neural networks by activation clustering":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "vulnerabilities of connectionist ai applications evaluation and defence")
  Member "fine pruning defending against backdooring attacks on deep neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "entangled watermarks as a defense against model extraction")
  Member "hu fu hardware and software collaborative attack framework against neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "februus input purification defense against trojan attacks on deep neural network systems")
  Member "potrojan powerful neural level trojan designs in deep learning models":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "backdoor attacks against transfer learning with pre trained deep learning models")
  Member "hardware trojan attacks on neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "sentinet detecting localized universal attacks against deep learning systems")
  Member "enhancing robustness of machine learning systems via data transformations":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "adversarial perturbations prevail in the y channel of the ycbcr color space")

Question: Please tell me which class the source paper 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)