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智能边缘人工智能:威胁架构、攻击面和现实世界风险.pdf

上传人: 竿*** 编号:982091 2025-11-29 28页 3.04MB

1、#SECTORCA BlackHatEventsAgentic Edge AI:Threat Architecture,Attack Surfaces&Real-World RiskNumaan HuqSenior Threat Researcher,Trend Micro#SECTORCA BlackHatEventsWho am I?#SECTORCA BlackHatEventsAgentic AI is a software architecture that aims to solve complex tasks through autonomous agents.Each agen

2、t is typically designed to perform a specific set of functions within a particular domain and can leverage tools,such as a web client,to interact with the outside world.These tools enable agents to gather information,act upon their environment,and communicate with other systems.While these agents ar

3、e not necessarily AI-driven,they normally leverage AI,in which case they are referred to as AI agents.Agents are managed by an orchestrator the reasoning engine responsible for identifying goals,formulating a plan,and coordinating the agents workflow to achieve such goals.Agents,in turn,serve as the

4、 fundamental units that perform actions within the agentic systemWhat is Agentic AI?#SECTORCA BlackHatEventsAgentic Edge AI is an edge first architecture where a local agentic orchestrator runs compact models to perceive,reason,plan,and act in real time on-device,and can stay operational even if off

5、line,while also using the cloud to augment analytics,learning,and fleet coordination.What is Agentic Edge AI?#SECTORCA BlackHatEventsImportancePerception-Reasoning-Actuation Loop Core FunctionsPerforms sensing,cognition,learning,and action capabilities locally on edge devices.Goal-Directed AutonomyS

6、ystems can independently pursue goals without external control,enhancing adaptability and efficiency.Real-Time Decision-MakingDecisions are made instantly based on current data,enabling rapid responses to changing conditions.On-Device ProcessingData is processed locally on the device,improving speed

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根据报告的内容,全文主要内容概括如下: 1. **Agentic Edge AI 简介**:这是一种边缘计算架构,通过自主代理在设备上实时感知、推理、规划和执行任务,即使离线也能运作,同时利用云服务增强分析、学习和车队协调。 2. **核心功能**: - 目标导向:基于高级目标运作。 - 环境感知:理解其环境和用户上下文。 - 多步推理:规划和分解复杂任务。 - 行动驱动:通过可用工具执行任务。 - 自我改进:从经验中学习以改进。 3. **Agentic Edge AI 架构**:包括感知层、边缘认知层、云认知层、学习层和行动层。 4. **AI 发展**:从早期机器学习到神经网络,再到Transformer和多模态模型,AI技术不断进步,推动了Agentic AI的出现。 5. **应用领域**:智能家居机器人、自动驾驶车辆、先进可穿戴设备、智能安全系统、工业物联网和机器人、国防与航空航天。 6. **安全挑战**:Agentic Edge AI的分布式性质、多样化的传感器集成和自主决策带来的风险。 7. **威胁场景**:包括传感器欺骗、模型中毒、通信拦截、拒绝服务攻击等。 8. **缓解策略**:在开发流程的各个阶段实施安全措施,包括虚拟环境、合成数据、训练与验证、部署与现场等。
"边缘AI如何改变未来?" "智能设备面临哪些新威胁?" "自主决策AI的安全挑战有哪些?"
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