沙特阿拉伯与美国的比较:网络安全的预防与处理

Sonia Ibrahim, Nada Alkenani, Banan Alghamdi, Amal Alfgeeh, Salwa alghamdl, Yusra Alzhrani, Amani Almuntashiri, Rawan S. Alghamdi, Abeer. Y. Salawi, Wejdan A Alghamdi, Mohammed I. Alghamdi
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引用次数: 0

摘要

网络安全实践主要涉及防止对连接到互联网的软件、硬件、服务器数据和其他资产的外部威胁。组织遵循许多网络安全实践来保护他们的系统和数据库免受恶意网络行为者的攻击。网络犯罪分子使用不同的技术,如鱼叉式网络钓鱼、网络钓鱼、密码攻击、拒绝服务、勒索软件等,对个人、组织和政府造成伤害,并从他们那里窃取重要信息。我们分析了如何使用深度学习算法来应对网络攻击。深度神经网络或深度学习由机器学习过程组成,以支持网络解决复杂问题并从未管理的数据中学习。此外,我们还分析了美国和沙特阿拉伯为合作应对网络威胁而实施的一些网络安全法律和实践。我们注意到,两国在应对网络威胁方面都做得很好,但两国需要付出更多努力,为处理网络安全敏感数据的公共部门专业人员提供培训和支持。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparison between Saudi Arabia and USA: Prevention and Dealing with Cyber Security
Cyber security practices mainly involve the prevention of external threats to software, hardware, server data, and other assets which are connected to the internet. Organizations follow a lot of cyber security practices to protect their systems and databases from malicious cyber actors. Cybercriminals use different techniques like spear-phishing, phishing, password attack, denial of service, ransomware, etc. to cause harm to people, organizations, and governments and steal important information from them. We analyzed the use of deep learning algorithms to deal with cyber-attacks. Deep neural networks or deep learning consist of machine learning procedures to support the network to fix complex issues and learn from unmanaged data. In addition, we also analyzed some of the cyber security laws and practices implemented in the US and Saudi Arabia to work collaboratively against cyber threats. It is observed that both countries are doing well against cyberthreats, but they need to work even more to provide training and support to professionals in the public sector who handle sensitive data about cyber security.
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CiteScore
1.70
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