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 "sok a comprehensive reexamination of phishing research from the security perspective"):
  Abstract: Phishing and spear-phishing are typical examples of masquerade attacks since trust is built up through impersonation for the attack to succeed. Given the prevalence of these attacks, considerable research has been conducted on these problems along multiple dimensions. We reexamine the existing research on phishing and spear-phishing from the perspective of the unique needs of the security domain, which we call security challenges: real-time detection, active attacker, dataset quality and base-rate fallacy. We explain these challenges and then survey the existing phishing/spear phishing solutions in their light. This viewpoint consolidates the literature and illuminates several opportunities for improving existing solutions. We organize the existing literature based on detection techniques for different attack vectors (e.g., URLs, websites, emails) along with studies on user awareness. For detection techniques, we examine properties of the dataset, feature extraction, detection algorithms used, and performance evaluation metrics. This work can help guide the development of more effective defenses for phishing, spear-phishing, and email masquerade attacks of the future, as well as provide a framework for a thorough evaluation and comparison.

Includes members:
  Member "deltaphish detecting phishing webpages in compromised websites":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "whitenet phishing website detection by visual whitelists")
  Member "defending against phishing attacks taxonomy of methods current issues and future directions":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "manipulation of perceived politeness in a web based email discourse through a malicious browser extension")
  Member "malicious url detection using machine learning a survey":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "ten ai stepping stones for cybersecurity")
  Member "an intelligent classification model for phishing email detection":
    also connected through other hyperedges:
      (none)
  Member "do users focus on the correct cues to differentiate between phishing and genuine emails":
    also connected through other hyperedges:
      (none)
  Member "know your phish novel techniques for detecting phishing sites and their targets":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "safekeeper protecting web passwords using trusted execution environments")
  Member "bit ly malicious deep dive into short url based e crime detection":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "malicious url detection using machine learning a survey")
  Member "an evasion and counter evasion study in malicious websites detection":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "taking care of the discretization problem a black box adversarial image attack in discrete integer domain")

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)