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# 2022 Forrester Wave™：企业防火墙 -- 我们荣获领导者称号

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威胁呈指数级增长，而且没有减缓的迹象。根据我们的 [2022 年 Unit 42 网络威胁趋势研究报告](https://start.paloaltonetworks.com/unit-42-network-threat-trends-report-2022.html)，从 2020 年到 2021 年，攻击数量增加了 15%，达到历史最高水平，是新冠导致远程办公人数增加之前的三倍。与此同时，由于企业安全日益复杂、数字化转型加速以及技术娴熟的网络安全人才短缺，导致检测和阻止规避型攻击者更加具有挑战性。[Forrester WaveTM：企业防火墙，2022 年第 4 季度报告](https://start.paloaltonetworks.com/leader-in-forrester-wave.html)指出，"根据 Forrester 的 2022 年安全调查，74% 的受访者称自己的企业在过去 12 个月中至少经历过一次潜在入侵或破坏。这一比例高于 2021 年的 63%。"现在，企业比以往任何时候都更需要值得信赖的安全合作伙伴------能为其提供高性能的解决方案，满足现代企业的需求，并且能够赶上网络威胁攻击者的脚步。

\***"Palo Alto Networks 长期以来被称为新一代防火墙 (NGFW) 的发明者，在网络安全领域的多个标准中实现真正的创新。"**--\*2022 年 Forrester Wave 报告

今天，我们很荣幸在[Forrester Wave：企业防火墙，2022 年第 4 季度报告](https://start.paloaltonetworks.com/leader-in-forrester-wave.html)中荣获领导者称号。Palo Alto Networks 在战略和现有产品类别中都获得了最高分。在报告中，Forrester 根据一组预定义的标准对供应商进行了评估，如产品前景、路线图执行、效果、零信任环境、性能、可用性和合作伙伴生态系统。Forrester 的分析和认可有助于安全和风险专业人士了解他们可通过企业防火墙供应商获得的价值。并且，让专业人士有信心做出重要的网络安全选择，从而带来持久的业务影响。[获取 2022 年 Forrester Wave 报告。](https://start.paloaltonetworks.com/leader-in-forrester-wave.html)

我们在网络安全领域持续占据领导地位，不断创新，并因此而获得了 Forrester 的认可，在战略和现有产品类别中都获得了最高分。[PAN-OS 10.2 Nebula](https://www.paloaltonetworks.com/network-security/whats-new-in-nebula) 是行业领先的网络安全操作系统的最新版本，通过将人工智能 (AI)、机器学习 (ML) 和史上首个内联深度学习相结合，帮助企业先发制敌，防御规避型威胁。借助 Nebula，Palo Alto Networks 的客户可先发制敌，防御当今最复杂的攻击。以下是 Palo Alto Networks 擅长的关键领域：

\***"公司的网络安全愿景中融入了人工智能和零信任原则。二者的执行都令人印象深刻。"**--\*2022 年 Forrester Wave 报告

**零信任** ：Palo Alto Networks 机器学习支持的新一代防火墙 (NGFW) 提供以最低访问权限、持续信任验证和持续安全检查原则为基础的基本零信任组件。我们的新一代防火墙通过原生集成 [User-ID、App-ID 和 Device-ID](https://www.paloaltonetworks.com/network-security/pan-os) 提供真正的零信任安全性，帮助安全团队识别用户、应用和设备，然后根据用户身份和情境信息不断验证其可信度。我们的[云交付安全服务](https://www.paloaltonetworks.com/network-security/security-subscriptions)可持续检查所有事务，以确保企业免受威胁，并且在不影响性能的情况下保护所有敏感数据。

**人工智能和机器学习** ：虽然基于签名的检测方法对于防止已知威胁来说仍然至关重要，但目前需要一种新的方法来保护企业抵御使用规避型技术的攻击。只有 Palo Alto Networks 新一代防火墙通过[内联深度学习](https://www.paloaltonetworks.com/blog/2022/02/inline-deep-learning/)提供机器学习支持的保护措施，通过行业首创的实时保护来阻止第一感染源，抵御零日威胁和高度规避的威胁。我们一流的[高级威胁防御](https://www.paloaltonetworks.com/network-security/advanced-threat-prevention)、[高级 URL 过滤](https://www.paloaltonetworks.com/network-security/advanced-url-filtering)和 [DNS 安全](https://www.paloaltonetworks.com/network-security/dns-security)以及其他云交付的安全服务能够在规避型攻击危及企业资产之前主动阻止。

\***"Palo Alto Networks 的 AIOps 可轻松将策略转化为最佳实践...Palo Alto Networks 的全新策略创建向导使用 AIOps 持续提供任意变更的最佳实践推荐，有效为用户提供实时防护措施。与竞争对手相比，这种方法有多好，怎么说都不为过。"**--\*2022 年 Forrester Wave 报告

**AIOps** ：我们的 [AIOps for NGFW](https://www.paloaltonetworks.com/network-security/aiops-for-ngfw) 旨在主动改善安全态势和健康状况，正如 Forrester 报告中所说："轻松将策略转化为最佳实践"。报告还指出："Palo Alto Networks 的全新策略创建向导使用 AIOps 持续提供任意变更的最佳实践推荐，有效为用户提供实时防护措施。与竞争对手相比，这种方法有多好，怎么说都不为过。"

AIOps 使用机器学习来分析来自新一代防火墙的遥测数据，从而智能预测防火墙的运行状况、性能和容量问题，可防止高达 51% 的防火墙中断问题。1AIOps for NGFW 在影响业务之前解释、预测和解决这些问题，重新定义了防火墙运营体验。

**性能** ：Palo Alto Networks 机器学习支持的新一代防火墙旨在实现最高性能。我们的[单通道并行处理架构 (SP3)](https://stage.paloaltonetworks.com/resources/whitepapers/single-pass-parallel-processing-architecture)添加了前所未有的功能和技术创新，但同时也能实现高吞吐量。 单通道架构可在单通道中对所有威胁和内容执行联网、策略查找、应用和解码以及签名匹配。这大大减少了在一台安全设备中执行多种功能所产生的处理开销。此外，随着时间的推移以及安全性的提高，此架构还能实现可预测的一致性能。

\***"公司的 TLS 解密技术在这个竞争激烈的领域中名列前茅。"**--\*2022 年 Forrester Wave 报告

**解密** ：如今，超过 85% 的企业流量都已加密，70% 以上的恶意软件使用加密技术来逃避安全防御。检查加密流量以抵御威胁具有前所未有的重要性。我们机器学习支持的新一代防火墙内联解密 TLS/SSL 流量，包括 TLS 1.3/HTTP/2 等现代协议。Palo Alto Networks 通过完全了解加密连接，[可以轻松部署解密技术。](https://www.paloaltonetworks.com/blog/2020/08/network-advances-in-decryption/)客户可以利用各种机制（如 URL 分类）来确定解密内容的优先级，以便随着时间的推移进行解密并保护隐私。借助我们的[第四代机器学习支持的新一代防火墙](https://www.paloaltonetworks.com/network-security/next-generation-firewall-hardware)，Palo Alto Networks 的客户可以阻止隐藏在加密流量背后的威胁，最终防御和解密性能提高了 5 倍。

### **下载 Forrester Wave：企业防火墙，2022 年第 4 季度**

Palo Alto Networks 将持续巩固领导地位，凭借强大的安全创新和产品战略来帮助实时满足关键客户的需求。此外，我们始终致力于以最佳投资回报率提供无与伦比的客户体验，这提高了我们提供高性能网络安全解决方案的能力，这些解决方案可满足现代企业即时检测和抵御高度规避性威胁的需求。

我们邀请您免费下载完整报告[Forrester Wave：企业防火墙，2022 年第 4 季度](https://start.paloaltonetworks.com/leader-in-forrester-wave.html)，亲自了解我们如何"在网络安全领域的多个标准中实现真正的创新"。

* 基于重点客户支持案例分析的 Palo Alto Networks 工程研究。

*** ** * ** ***

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