会议信息

AI-SIIS 2026: IEEE International Conference on AI and Security for Industrial IoT Systems

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截稿日期:
2026-02-15
通知日期:
2026-04-25
会议日期:
2026-09-24
会议地点:
Hyderabad, India
浏览: 3549   关注: 1   参加: 0
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会伴指数 (CP-I)

44.2 / 100
全站第 3,153 名 / 共 5,694 个会议 · 前 56%

安全与隐私 第 194 / 362 网络与通信 第 487 / 865

证据有限：这个会议不在 CCF / ICORE / QUALIS 任何一份榜单里，也没有录用率数据，因此分数的大部分回落到了中性基准。
学术认可 (35%) 无数据 —— 按中性基准 50 分计入 —
投稿选择性 (20%) 无数据 —— 按中性基准 50 分计入 —
会议传承 (20%) 无数据 —— 按中性基准 50 分计入 —
社区关注 (10%)
15
资料公开度 (15%)
35

用到的输入: 在会伴关注它的研究者：1 人 · 过去 24 个月打开过本页的研究者：2 人

公开资料里还缺: 历年录用率 (+4.5) · 历届信息 (+3.0) · 最佳论文记录 (+2.3)
主办方认领本会议后，可直接在这一页补上；分数每晚重算。如何提升这个分数

置信度 25% —— 分数中有多大比例来自实际观测到的数据，而不是中性基准。 这个分数是怎么算出来的 · 查看完整榜单 · 算法版本 1.1 · 算于 2026-10-07

征稿

AI-SIIS 2026 (IEEE International Conference on AI and Security for Industrial IoT Systems) is an academic conference held in Hyderabad, India on 2026-09-24. The paper submission deadline is 2026-02-15. Acceptance notifications are sent on 2026-04-25.

AI-SIIS 2026 focuses on industrial and upcoming frontier technologies, applications of electronics, controls, communications, instrumentation and computational intelligence. The objectives of the conference are to provide high quality research and professional interactions for the advancement of science, technology, and fellowship. Papers with new research results are encouraged for submission. Technical Topics (but not limited to) Track 1: AI-Based Security and Intelligence for Industrial IoT AI-based threat detection and mitigation for Industrial IoT (IIoT) Machine learning for anomaly detection in industrial networks Federated and distributed learning for industrial cybersecurity Fault-tolerant AI architectures for industrial automation Intrusion detection and prevention in smart factories Deep learning for malware classification in IIoT environments Blockchain for secure IIoT data sharing and identity management Track 2: AI for Smart Healthcare and Medical IoT Deep learning for disease diagnosis and early detection AI-enabled predictive healthcare analytics and patient monitoring Federated learning for clinical data sharing and privacy preservation Explainable AI (XAI) for medical decision-making Reinforcement learning in personalized treatment planning AI-driven biomedical signal and image analysis Digital twins and AI modeling for healthcare systems AI for remote monitoring and telemedicine applications Track 3: Secure and Ethical AI Systems for Industry and Society Ethics-by-design frameworks for AI in industrial automation AI control mechanisms and failsafe architectures Explainability and interpretability for critical decision systems AI accountability and auditability models Managing algorithmic bias in industrial and social contexts Standards and benchmarks for ethical and safe AI Track 4: Human–Machine Collaboration and Cognitive AI Systems AI-driven human-machine collaboration in industrial environments Cognitive AI systems for decision support and control Adaptive interfaces for human-in-the-loop systems Trust, transparency, and human factors in AI-enabled operations Track 5: Smart and Intelligent Sensor Applications AI and machine learning for sensor data processing Sensor fusion and signal conditioning Self-calibrating and self-healing sensors Smart camera systems Industrial IoT and predictive maintenance sensors
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