Enhancing Security Infrastructure with AI: A Case Study of EV Group

• 应用基础设施与中间件 - 事件驱动型应用
• 平台即服务 (PaaS) - 设备管理平台

• 设备与机械
• 国家安全与国防

• 自主运输系统
• 篡改检测

随着 EV Group 的数字基础设施变得越来越复杂，该团队试图通过超越其现有安全工具所依赖的基于日志的分析来提高其安全地位。他们基于日志的 SIEM 技术很好地概述了数字资产，但在网络流量层缺乏数据包级别的洞察力意味着安全事件没有得到足够快的识别和控制。

主要目的是最小化事件发生和被确认之间的时间。

电动汽车集团

EV Group是半导体、MEMS、化合物半导体、功率器件和纳米技术器件制造的大批量生产设备和工艺解决方案的领先供应商。它支持由全球客户和合作伙伴组成的复杂网络，在全球拥有 1100 多名员工。‍

因此，该团队将 Darktrace 与其他工具并排进行了测试，决定使用 Darktrace 的自学习 AI 主要是因为其检测的准确性。

Darktrace 揭示了该组织的数字资产，揭示了该团队以前没有意识到的许多问题。该技术帮助安全团队在清理他们的数字基础设施和确保长期更强大的安全方面更具战略性。

• The implementation of Darktrace's Self-Learning AI has significantly improved EV Group's security infrastructure. The AI technology provides packet-level insight and accurate detections, enabling the security team to recognize and control security incidents more quickly. The technology also reveals configuration errors that could represent potential backdoors into the digital estate, helping the team to strategically clean up their infrastructure. The addition of Autonomous Response to the security stack ensures round-the-clock security, taking targeted and proportionate action against threats whenever they occur. The team's confidence in the technology is so high that they assess every anomaly surfaced by Darktrace, ensuring a clean dashboard at the end of every day.

• Reduced time to response for security incidents
• 24/7 operational security with Autonomous Response
• Daily anomaly checks to ensure a clean Darktrace dashboard