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 context aware framework for detecting sensor based threats on smart devices"
  Abstract: Sensors (e.g., light, gyroscope, accelerometer) and sensing-enabled applications on a smart device make the applications more user-friendly and efficient. However, the current permission-based sensor management systems of smart devices only focus on certain sensors and any App can get access to other sensors by just accessing the generic sensor Application Programming Interface (API). In this way, attackers can exploit these sensors in numerous ways: they can extract or leak users' sensitive information, transfer malware, or record or steal sensitive information from other nearby devices. In this paper, we propose 6thSense, a context-aware intrusion detection system which enhances the security of smart devices by observing changes in sensor data for different tasks of users and creating a contextual model to distinguish benign and malicious behavior of sensors. 6thSense utilizes three different Machine Learning-based detection mechanisms (i.e., Markov Chain, Naive Bayes, and LMT). We implemented 6thSense on several sensor-rich Android-based smart devices (i.e., smart watch and smartphone) and collected data from typical daily activities of 100 real users. Furthermore, we evaluated the performance of 6thSense against three sensor-based threats: (1) a malicious App that can be triggered via a sensor, (2) a malicious App that can leak information via a sensor, and (3) a malicious App that can steal data using sensors. Our extensive evaluations show that the 6thSense framework is an effective and practical approach to defeat growing sensor-based threats with an accuracy above 96% without compromising the normal functionality of the device. Moreover, our framework reveals minimal overhead.

Connected through hyperedge HE-1 (induced by source paper "real time analysis of privacy un aware iot applications"):
  with members:
    - "aegis a context aware security framework for smart home systems"
    - "program analysis of commodity iot applications for security and privacy challenges and opportunities"
    - "soteria automated iot safety and security analysis"
    - "peek a boo i see your smart home activities even encrypted"
    - "sensitive information tracking in commodity iot"
    - "a survey on sensor based threats to internet of things iot devices and applications"
    - "advertising in the iot era vision and challenges"
    - "iotdots a digital forensics framework for smart environments"

Connected through hyperedge HE-2 (induced by source paper "multi user multi device aware access control system for smart home"):
  with members:
    - "a system level behavioral detection framework for compromised cps devices smart grid case"
    - "healthguard a machine learning based security framework for smart healthcare systems"
    - "aegis a context aware security framework for smart home systems"
    - "soteria automated iot safety and security analysis"
    - "peek a boo i see your smart home activities even encrypted"
    - "sensitive information tracking in commodity iot"
    - "advertising in the iot era vision and challenges"
    - "iotdots a digital forensics framework for smart environments"

Connected through hyperedge HE-3 (induced by source paper "computer systems have 99 problems let s not make machine learning another one"):
  with members:
    - "atmpa attacking machine learning based malware visualization detection methods via adversarial examples"
    - "copycat practical adversarial attacks on visualization based malware detection"
    - "robust physical world attacks on deep learning models"
    - "mxnet a flexible and efficient machine learning library for heterogeneous distributed systems"
    - "malicious behavior detection using windows audit logs"
    - "a survey on deep packet inspection for intrusion detection systems"

Connected through hyperedge HE-4 (induced by source paper "aegis a context aware security framework for smart home systems"):
  with members:
    - "cross app interference threats in smart homes categorization detection and handling"
    - "peek a boo i see your smart home activities even encrypted"
    - "sensitive information tracking in commodity iot"
    - "iotdots a digital forensics framework for smart environments"
    - "6thsense a context aware sensor based attack detector for smart devices"
    - "context aware computing for the internet of things a survey"

Connected through hyperedge HE-5 (induced by source paper "healthguard a machine learning based security framework for smart healthcare systems"):
  with members:
    - "6thsense a context aware sensor based attack detector for smart devices"

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)