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**庆南情报大学毕业证**
**韩国庆南情报大学**
**GraduateDiploma**
**QingnanUniversity of Intelligence, South Korea**
**学位授予：**理学学士
**DegreeConferred:** Bachelor of Science
**授予日期：**2024年4月28日
**Dateof Conferral:** April 28, 2024
**校长：**XXX
**President:**XXX
**教务长：**XXX
**Registrar:**XXX
**毕业生姓名：**[YourName]
**Graduate'sName:** [Your Name]
**学号：**XXXXXXXXXX
**StudentID:** XXXXXXXXXXX
**本科专业：**计算机科学与技术
**UndergraduateMajor:** Computer Science and Technology
**毕业论文题目：**人工智能在网络安全中的应用
**ThesisTitle:** Application of Artificial Intelligence in Network Security
**毕业论文导师：**XXX
**ThesisAdvisor:** XXX
**庆南情报大学证书编号：**XXXXXXXXXX
**QingnanUniversity of Intelligence Certificate Number:** XXXXXXXXXXX
**备注：**该证书乃经过韩国庆南情报大学授权颁发，证明其持有人已完成本校要求的学业，并被授予理学学士学位。
**Note:**This diploma is conferred by Qingnan University of Intelligence,South Korea, certifying that the holder has fulfilled therequirements of the institution and has been awarded the degree ofBachelor of Science.
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**论文摘要**
在本篇毕业论文中，我们研究了人工智能在网络安全中的应用。随着信息技术的迅速发展，网络安全问题日益严重，传统的安全防护手段已经不能满足对抗复杂网络攻击的需求。本文主要探讨了如何利用人工智能技术来加强网络安全防护，提高网络安全防御能力。我们分析了机器学习、深度学习等人工智能技术在网络安全中的应用现状，并结合实际案例展示了其在网络入侵检测、恶意代码识别、异常流量检测等方面的效果与应用。
本文首先介绍了网络安全面临的挑战和传统安全防护手段存在的局限性，随后详细介绍了人工智能在网络安全中的应用技术。我们深入探讨了基于机器学习的入侵检测系统、基于深度学习的恶意代码识别方法以及基于异常检测的网络流量分析技术。通过实验与对比分析，我们验证了这些技术在提高网络安全防御能力方面的有效性和优势，并提出了进一步改进的方向和思路。
最后，本文总结了人工智能在网络安全中的应用现状和发展趋势，指出了未来研究的方向和挑战。我们希望本文的研究成果能够为网络安全领域的相关研究和实践提供参考，促进人工智能技术在网络安全中的广泛应用与发展。
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**Abstract**
Inthis thesis, we investigate the application of artificialintelligence in network security. With the rapid development ofinformation technology, network security issues are becomingincreasingly severe, and traditional security measures are no longersufficient to combat complex cyber-attacks. This paper mainlyexplores how to use artificial intelligence technology to enhancenetwork security defenses and improve network security capabilities.We analyze the current applications of artificial intelligencetechnologies such as machine learning, deep learning, etc., innetwork security, and demonstrate their effectiveness andapplications in network intrusion detection, malicious codeidentification, anomaly traffic detection, and other aspects throughpractical cases.
Thispaper first introduces the challenges faced by network security andthe limitations of traditional security measures, and then detailsthe application of artificial intelligence in network security. Wedelve into machine learning-based intrusion detection systems, deeplearning-based malicious code identification methods, and anomalydetection-based network traffic analysis techniques. Throughexperiments and comparative analysis, we verify the effectiveness andadvantages of these technologies in improving network securitydefenses and propose directions and ideas for further improvement.
Finally,this paper summarizes the current application status and developmenttrends of artificial intelligence in network security, and points outthe direction and challenges for future research. We hope that theresearch results of this paper can provide references for relevantresearch and practices in the field of network security, and promotethe widespread application and development of artificial intelligencetechnology in network security.
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