AI models are no longer locked in the cloud—they live in your pocket, powering mobile apps for fitness, finance, healthcare, and beyond. But with this power comes new risk: adversarial attacks, model theft, privacy leaks, and silent failures that undermine user trust.
Secure Mobile AI Models Against Attacks
您将学到什么
Explain the fundamentals of deploying AI models on mobile applications, including their unique performance, privacy, and security considerations.
Analyze threats to mobile AI models like reverse engineering, adversarial attacks, and privacy leaks and their effect on reliability and trust.
Design a layered defense strategy for securing mobile AI applications by integrating encryption, obfuscation, and continuous telemetry monitoring.
您将获得的技能
要了解的详细信息
可分享的证书
添加到您的领英档案
作业
1 项作业
授课语言：英语（English）
最近已更新！
December 2025
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积累特定领域的专业知识
本课程是 AI Security: Security in the Age of Artificial Intelligence 专项课程 专项课程的一部分
在注册此课程时，您还会同时注册此专项课程。
- 向行业专家学习新概念
- 获得对主题或工具的基础理解
- 通过实践项目培养工作相关技能
- 获得可共享的职业证书
该课程共有3个模块
This module introduces learners to the unique nature of AI models running on mobile devices and why security cannot be bolted on later. Through an AI-guided dialogue, short lessons, and a design-focused lab, learners see how early choices in packaging and deployment set the stage for resilience or vulnerability. In this module, the emphasis is that security is not a barrier to innovation, it is the enabler of sustainable mobile AI applications.
涵盖的内容
4个视频2篇阅读材料1次同伴评审
In this module, learners will dive deeply into the adversarial landscape, exploring how reverse engineering, data inference, and adversarial inputs compromise mobile AI systems. The AI coach uses a real-world scenario to show how curiosity can become an attack, while lessons and labs reveal the tangible risks of model theft and privacy leaks. Forwards the understanding that researching threats is not paranoia but the prerequisite for defending trust and intellectual property, the essential elements of a secure, and mobile, AI.
涵盖的内容
3个视频1篇阅读材料1次同伴评审
This module shifts from analysis to action, equipping learners with strategies to harden models and continuously monitor them in production. Guided by an AI dialogue on stealthy breaches, learners see how OpenTelemetry and layered defenses provide visibility and resilience in the field. Overall, learners discover securing mobile AI is not a one-time act, but a continuous practice of observing, adapting, and improving.
涵盖的内容
4个视频1篇阅读材料1个作业2次同伴评审
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