Enhancing Mobile Healthcare App Security: A Case Study on Eko Health and Data Theorem

技术

分析与建模 - 机器学习
网络安全和隐私 - 应用安全

适用行业

国家安全与国防
电信

用例

篡改检测
时间敏感网络

服务

云规划/设计/实施服务
系统集成

挑战

Eko Health 需要一种“始终在线”的解决方案来防止应用程序安全数据泄露。他们正在寻找一种易于集成、快速提供结果且不断创新的解决方案。他们还希望减少开发人员的返工并领先于威胁。

关于客户

Eko Health 开发经 FDA 批准的人工智能心音和心电图传感器，用于心脏病监测。它们使临床医生能够提供最好的心脏护理。 Eko 的设备和移动应用程序可帮助记录、回放、直播和共享患者的身体声音和心电图。他们是护理第一线的医疗服务提供者和科学家的忠实合作伙伴。

解决方案

Eko Health 与 Data Theorem 合作制定了他们的移动安全策略。他们对应用程序安全堆栈采用整体方法，并使用 Data Theorem 的 ASM 和全堆栈平台来保护 Web、移动、API 和云应用程序中的敏感、机密和受监管的数据。他们将 Data Theorem 的安全代码和自动修复脚本集成到 DevSecOps 管道中，以实现持续的安全覆盖。

运营影响

Data Theorem's solution has provided Eko Health with a 'zero approach' to security issues, requiring that all customers have zero P1 security issues, App Store/Google Play blockers, and 3rd Party SDK/ OSS issues. This allows Eko to know about any showstoppers in its pre-production environment, but also knowledge about “zero-days” in the wild on production apps. Furthermore, Data Theorem’s ability to scan 3rd party SDK & Open Source libraries has allowed Eko to shed light on an attack surface that would otherwise be a blind spot. Data Theorem was the only company evaluated that also offers “Secure Code” directly to developers to help fix identified security issues. This enables Data Theorem's customers to streamline the amount of time and resources required to fix an issue, and continuously monitor, scan, and fix mobile application security - at scale - with a solution that has a negligible impact on speed and performance.

数量效益

Data Theorem scans for critical (P1) security issues on a daily basis
Data Theorem's solution ensures security coverage 24/7/365
Data Theorem's Secure Code and Auto-Remediation scripts are leveraged via various platforms, providing actionable security results