Results for “iot-edge”

Design and implement network segmentation for industrial control systems using the Purdue Enterprise Reference Architecture model, separating OT and IT networks into hierarchical security zones with strict traffic control.

Conduct comprehensive security assessments of Operational Technology (OT) networks including SCADA systems, DCS architectures, and industrial control system communication paths, addressing the Purdue Reference Model layers and identifying IT/OT convergence risks.

Design and deploy IEC 62443-compliant conduit architecture for secure OT remote access, including jump servers, MFA gateways, session recording, and approval-based workflows for vendor and engineer access to industrial control systems.

Design and implement network segmentation in Operational Technology environments using VLANs, industrial firewalls, data diodes, and software-defined networking, following the Purdue Model and IEC 62443 standards.

Design and implement security zones and conduits for industrial automation and control systems per IEC 62443-3-2, including zone partitioning, firewall configuration, and validation through traffic analysis and penetration testing.

Measures the trade-off between computation time and energy consumption in mobile edge computing by computing a weighted sum of the two objectives, given system configuration parameters and per-user task characteristics.

Deploys anomaly detection for industrial control environments using machine learning models trained on OT network baselines, physics-based process models, and behavioral analysis of industrial protocol communications.

AIDefence security layer with prompt injection blocking, input validation, sandboxed execution, output sanitization, and STRIDE threat modeling.

AI 原生的潜在客户情报和外联流水线。用 agent 驱动的信号评分、共同关系人排名、暖场路径发现、来源语音建模和多渠道外联（邮件、LinkedIn、X），替代 Apollo、Clay 和 ZoomInfo。在用户想找到、评估并联系高价值联系人时使用。

Aggregate and rank signals from multiple edge-finding skills into a prioritized conviction dashboard with weighted scoring, deduplication, and contradiction detection.

Reconciles project documentation, agent memory, and rule files against the actual codebase after a development session, ensuring accuracy and consistency across all knowledge layers.