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2024 Practical Issues: Using Artificial Intelligence to Combat Social Engineering Emails

編輯群2024-10-23

Industry: AI Application Services

Industry Pain Points:

  • As hacker techniques evolve, the complexity of social engineering attacks increases. Attackers often exploit human weaknesses through disguised emails, links, or attachments, luring users into clicking or responding inadvertently, thereby stealing confidential information. These attack methods not only increase the risk of corporate data leakage but also intensify the challenges of protection mechanisms. Reliance on traditional security tools alone is no longer effective. Therefore, enterprises need to adopt more advanced technologies and risk control measures to address such increasingly complex threats.

Benefits of Introducing AI:

  • Through precise data analysis and pattern recognition, AI systems can quickly detect potential abnormal behaviors and proactively prevent attacks before they occur. This technology can automatically adjust protection strategies according to emerging attack methods, thus significantly reducing risk. Moreover, the system is highly adaptable, able to adjust to ever-changing cybersecurity threats, providing more accurate protection and ensuring timely prevention of various cybersecurity attacks, enhancing the speed and accuracy of overall protection.
  • Additionally, this technology can serve as a powerful tool to prevent security vulnerabilities. Through rule setting and learning mechanisms, the system can gradually enhance its defensive capabilities. As the system operates over time, it automatically learns and analyzes new social engineering methods. Based on these learning outcomes, the system can establish a more robust detection model, thereby more effectively identifying and intercepting unlawful attacks. This continuous learning mode enables the system to constantly adapt to new attack strategies, providing a stable and robust support for the company's cybersecurity frontline, further reducing the likelihood of risks and ensuring long-term stability of corporate cybersecurity.

Common AI Technologies:

  • Bayesian classifiers, Support Vector Machines, Logistic Regression.
  • Deep learning, frameworks such as:、。BERT、TextRNN。

「Translated content is generated by ChatGPT and is for reference only. Translation date：2024-11-15」