人工智能正以其先进的工具和广泛的可及性改变着许多行业。然而，人工智能的进步也带来了网络安全风险，因为网络犯罪分子可以滥用这些技术。美国和英国等政府以及微软和OpenAI等主要人工智能公司正在制定政策和策略来解决这些安全问题。本研究考察了这些措施，包括“布莱切利宣言”和拜登总统的行政命令，并探讨了人工智能如何增强信息系统抵御新的网络威胁的弹性。

🧑‍💻 **人工智能和机器学习系统的弹性增强**：人工智能自 1956 年由明斯基和麦卡锡首次提出以来，已从理论概念发展成为医疗保健、金融、自动驾驶和网络安全等领域的必不可少应用。尽管取得了进展，但人工智能和机器学习系统在数据质量、稳健性和安全性方面仍然存在不足，这会影响其有效性。本研究调查了增强人工智能和机器学习系统抵御各种风险（包括对抗性攻击和数据中断）的弹性方法。它着眼于政府政策和企业策略，以确保这些技术的可靠性和可信度。

🌐 **AI 和网络安全中的信息弹性**：信息弹性是指系统在中断或攻击期间保持其运行、完整性和性能的能力。NIST 定义了这一概念，突出了系统在具有挑战性的条件下运行并有效恢复的能力。在人工智能和机器学习的背景下，弹性对于管理数据质量和安全问题以及适应不断变化的条件至关重要。网络安全是信息弹性的关键，因为它保护网络、数据和端点安全。人工智能和机器学习通过自动化威胁检测、预测风险以及启用自适应安全措施来提高弹性。

🤝 **全球网络安全倡议与合作**：为了应对日益严重的网络攻击威胁，各国政府、跨国公司和国际组织已制定政策和指南，以创建一个安全且有弹性的信息环境。联合国支持负责任地使用人工智能技术，认识到其在实现可持续发展目标方面发挥的作用。美国的一项全面的网络安全战略旨在通过联邦机构与私营部门之间的合作来保护国家利益和关键基础设施。印度正在制定关于人工智能伦理使用的法规，而中国的网络安全法强调数据保护和互联网安全。像“布莱切利宣言”这样的倡议强调了全球合作在管理人工智能风险方面的重要性，促进了最大限度地利用人工智能的优势，同时减轻潜在威胁的统一方法。

🏢 **企业对网络安全的贡献**：企业也在推进网络安全工作。微软创建了一个网络安全政策框架，并与政府和其他利益相关者建立合作伙伴关系，以解决全球网络安全问题。苹果的安全措施（如安全隔离区和端到端加密）反映了其对用户隐私的承诺。OpenAI 利用加密和严格的访问控制来保护敏感信息，并通过协作倡议支持网络安全。这些努力强调了公共部门和私营部门之间需要协调一致，以加强全球网络安全并建立健壮的信息基础设施。

Balancing Innovation and Threats in AI and Cybersecurity:

AI is transforming many sectors with its advanced tools and broad accessibility. However, the advancement of AI also introduces cybersecurity risks, as cybercriminals can misuse these technologies. Governments, including the US and UK, and major AI firms like Microsoft and OpenAI, are working on policies and strategies to address these security concerns. The study examines these measures, including “The Bletchley Declaration” and President Biden’s Executive Order, and explores how AI can bolster the resilience of information systems against new cyber threats.

Strengthening Resilience in AI and ML Systems:

First coined by Minsky and McCarthy in 1956, AI has grown from theoretical ideas to essential applications in healthcare, finance, autonomous driving, and cybersecurity. Despite their progress, AI and ML systems need help with data quality, robustness, and security, which can impact their effectiveness. This study investigates methods to enhance the resilience of AI and ML systems against various risks, including adversarial attacks and data disruptions. It looks into government policies and corporate strategies to ensure these technologies’ reliability and trustworthiness.

The Evolution and Impact of AI and Machine Learning:

Since their emergence in the mid-20th century, AI and its subset, ML, have made significant strides driven by algorithm advancements, computing power, and data availability. These play a critical role in various sectors, leveraging their capacity to analyze large volumes of data, extract insights, and make autonomous decisions. AI and ML are transforming industries like healthcare, finance, and cybersecurity by improving efficiency, boosting productivity, and facilitating better decision-making, making them essential modern technology components.

Boosting Information Resilience in AI and Cybersecurity:

Information resilience refers to a system’s ability to maintain its operation, integrity, and performance during disruptions or attacks. Defined by NIST, this concept highlights a system’s ability to function under challenging conditions and recover effectively. In the context of AI and ML, resilience is vital for managing data quality and security issues and adapting to changing conditions. Cybersecurity is key to information resilience, as it safeguards network, data, and endpoint security. AI and ML contribute to resilience by automating threat detection, forecasting risks, and enabling adaptive security measures.

Global Cybersecurity Initiatives and Collaboration:

Various governments, multinational companies, and international organizations have established policies and guidelines to create a secure and resilient information environment to address the rising threat of cyberattacks. The UN supports the responsible use of AI technologies, recognizing their role in achieving Sustainable Development Goals. A comprehensive cybersecurity strategy in the US aims to protect national interests and critical infrastructure through collaboration between federal agencies and the private sector. India is developing regulations on ethical AI use, while China’s cybersecurity laws emphasize data protection and internet security. Initiatives like the Bletchley Declaration highlight the importance of global cooperation in managing AI risks, promoting a unified approach to maximizing AI’s benefits while mitigating potential threats.

Corporate Contributions to Cybersecurity:

Corporations are also advancing cybersecurity efforts. Microsoft has created a cybersecurity policy framework with partnerships with governments and other stakeholders to tackle global cybersecurity issues. Apple’s security measures, such as Secure Enclave and end-to-end encryption, reflect its commitment to user privacy. OpenAI utilizes encryption and strict access controls to protect sensitive information and supports cybersecurity through collaborative initiatives. These efforts underscore the need for a coordinated approach between public and private sectors to enhance global cybersecurity and build a robust information infrastructure.

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