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 sink driven approach to detecting exposed component vulnerabilities in android apps"
  Abstract: Android apps could expose their components for cooperating with other apps. This convenience, however, makes apps susceptible to the exposed component vulnerability (ECV), in which a dangerous API (commonly known as sink) inside its component can be triggered by other (malicious) apps. In the prior works, detecting these ECVs use a set of sinks pertaining to the ECVs under detection. In this paper, we argue that a more comprehensive and effective approach should start by a systematic selection and classification of vulnerability-specific sinks (VSinks). The set of VSinks is much larger than those used in the previous works. Based on these VSinks, our sink-driven approach can detect different kinds of ECVs in an app in two steps. First, VSinks and their categories are identified through a typical forward reachability analysis. Second, based on each VSink's category, a corresponding detection method is used to identify the ECV via a customized backward dataflow analysis. We also design a semi-auto guided analysis and validation capability for system-only broadcast checking to remove some false positives. We implement our sink-driven approach in a tool called ECVDetector and evaluate it with the top 1K Android apps. Using ECVDetector we successfully identify a total of 49 vulnerable apps across all four ECV categories we have defined. To our knowledge, most of them are previously undisclosed, such as the very popular Go SMS Pro and Clean Master. Moreover, the performance of ECVDetector is high, requiring only 9.257 seconds on average to process each component.

Connected through hyperedge HE-1 (induced by source paper "scalable online vetting of android apps for measuring declared sdk versions and their consistency with api calls"):
  with members:
    - "sclib a practical and lightweight defense against component hijacking in android applications"
    - "discovering flaws in security focused static analysis tools for android using systematic mutation"
    - "mopeye opportunistic monitoring of per app mobile network performance"
    - "measuring the declared sdk versions and their consistency with api calls in android apps"
    - "mamadroid detecting android malware by building markov chains of behavioral models"
    - "indirect file leaks in mobile applications"
    - "analyzing android browser apps for file vulnerabilities"

Connected through hyperedge HE-2 (induced by source paper "sclib a practical and lightweight defense against component hijacking in android applications"):
  with members:
    - "measuring the declared sdk versions and their consistency with api calls in android apps"
    - "indirect file leaks in mobile applications"
    - "analyzing android browser apps for file vulnerabilities"
    - "quire lightweight provenance for smart phone operating systems"

Connected through hyperedge HE-3 (induced by source paper "measuring the declared sdk versions and their consistency with api calls in android apps"):
  with members:
    - "mopeye monitoring per app network performance with zero measurement traffic"
    - "indirect file leaks in mobile applications"
    - "analyzing android browser apps for file vulnerabilities"

Connected through hyperedge HE-4 (induced by source paper "cross platform analysis of indirect file leaks in android and ios applications"):
  with members:
    - "indirect file leaks in mobile applications"
    - "analyzing android browser apps for file vulnerabilities"
    - "quire lightweight provenance for smart phone operating systems"

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)