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 "iotdots a digital forensics framework for smart environments"):
  Abstract: IoT devices and sensors have been utilized in a cooperative manner to enable the concept of a smart environment. In these smart settings, abundant data is generated as a result of the interactions between devices and users' day-to-day activities. Such data contain valuable forensic information about events and actions occurring inside the smart environment and, if analyzed, may help hold those violating security policies accountable. In this paper, we introduce IoTDots, a novel digital forensic framework for a smart environment such as smart homes and smart offices. IoTDots has two main components: IoTDots-Modifier and IoTDots-Analyzer. At compile time, IoTDots-Modifier performs the source code analysis of smart apps, detects forensically-relevant information, and automatically insert tracing logs. Then, at runtime, the logs are stored into a IoTDots database. Later, in the event of a forensic investigation, the IoTDots-Analyzer applies data processing and machine learning techniques to extract valuable and usable forensic information from the devices' activity. In order to test the performance of IoTDots, we tested IoTDots in a realistic smart office environment with a total of 22 devices and sensors. The evaluation results show that IoTDots can achieve, on average, over 98% of accuracy on detecting user activities and over 96% accuracy on detecting the behavior of users, devices, and apps in a smart environment. Finally, IoTDots performance yields no overhead to the smart devices and very minimal overhead to the cloud server.

Includes members:
  Member "sensitive information tracking in commodity iot":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "real time analysis of privacy un aware iot applications")
  Member "advertising in the iot era vision and challenges":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "architectural software patterns for the development of iot smart applications")
  Member "digital forensic investigation of cloud storage services":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "greening cloud enabled big data storage forensics syncany as a case study")
  Member "digital forensic approaches for amazon alexa ecosystem":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "smart home personal assistants a security and privacy review")

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)