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ICAISG 2026: International Conference on Artificial Intelligence Security and Governance

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ICAISG
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투고 마감일:
2026-09-15 Extended
통보일:
2026-10-15
개최일:
2026-11-20
개최지:
Hangzhou, China
개최 횟수:
2
주최측:
조회: 1280   팔로우: 0   참가: 0

회반 지수 (CP-I)

40.8 / 100
전체 5,687개 중 4,853위 · 상위 86%

보안·프라이버시 분야 361개 중 310위 인공지능·기계학습 분야 741개 중 620위

학술적 인정 (35%) 데이터 없음 — 중립 기준값 50점으로 계산 —
투고 선별성 (20%) 데이터 없음 — 중립 기준값 50점으로 계산 —
개최 횟수 (20%)
30
커뮤니티 관심도 (10%)
21
공개 자료 충실도 (15%)
35

사용한 입력: 확인되는 개최 횟수: 2 · 지난 24개월 동안 이 페이지를 연 연구자: 16명

공개 자료에서 빠진 항목: 역대 게재율 (+4.5) · 역대 회차 (+3.0) · 최우수 논문 기록 (+2.3)
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신뢰도 45% — 점수 중 중립 기준값이 아니라 실제 관측된 데이터에 근거한 비율. 이 점수는 어떻게 계산되나 · 전체 순위 보기 · 알고리즘 버전 1.1 · 산출일 2026-09-27

논문 모집

ICAISG 2026 ( International Conference on Artificial Intelligence Security and Governance) is an academic conference held in Hangzhou, China on 2026-11-20. The paper submission deadline is 2026-09-15 (extended). Acceptance notifications are sent on 2026-10-15.

Papers in the main technical program must describe high-quality, original research. Topics of interest include all aspects of artificial intelligence and software engineering including, but not limited to Track 1: Content Generation and Tampering Content Detection ▪ Media Manipulation Detection and Localization ▪ Deepfake Forgery Detection and Mitigation ▪ Authenticity Assessment of AI-Generated Media (Images, Videos, Audio, Text) ▪ Approximate Reasoning Track 2: Traceability and Provenance Analysis of Synthetic Content ▪ Source Device Attribution of Synthetic Media ▪ Generative Model Attribution (GANs, Diffusion Models) ▪ Identity Provenance in AI-Generated Content Track 3: Security of Large Language Models ▪ Adversarial Attacks and Defense Strategies for LLMs ▪ Jailbreaking Attacks and Prompt Injection Mitigation ▪ Security Risks in Knowledge Distillation Pipelines ▪ Monitoring Malicious Adaptation of Open-Source LLMs ▪ Detection and Mitigation of Hallucinations in LLMs ▪ Content Integrity Assurance in Multimodal LLMs Track 4: Data Privacy Protection ▪ Privacy Leakage in Federated Learning Systems ▪ Privacy-Preserving Data Anonymization Techniques ▪ Secure Multi-Party Computation Frameworks ▪ Ethical Implications of Synthetic Data Generation ▪ Countermeasures Against AI-Driven Data Reconstruction Track 5: AI-Driven Cybersecurity ▪ AI-Powered Threat Detection and Incident Response ▪ Automated Vulnerability Discovery and Exploitation ▪ AI in Offensive and Defensive Network Operations ▪ Collaborative Threat Intelligence Sharing via AI ▪ Quantum Computing Threats to AI Security Protocols Track 6: Automated Adversarial Testing and Validation ▪ Generation and Application of Adversarial Examples ▪ AI-Based Attack Simulation and Penetration Testing ▪ Automated Verification of AI System Robustness Track 7: Security of AI-Enabled IoT Systems ▪ Privacy and Integrity of IoT Data Streams ▪ Defense Mechanisms for AI-Enhanced IoT Networks Track 8: Biometric Security and AI ▪ Privacy-Preserving Biometric Data Management ▪ Anti-Spoofing Techniques for Biometric Systems ▪ AI-Augmented Biometric Authentication Track 9: Ethical AI and Regulatory Compliance ▪ Accountability in AI Decision-Making Processes ▪ Bias Detection and Fairness in Algorithmic Systems ▪ Legal and Compliance Frameworks for AI Deployment ▪ Inclusive Algorithm Design for Diverse Populations ▪ Moral Responsibility in Autonomous Decision Systems Track 10: Emerging Trends in AI Security ▪ Security Challenges of Cutting-Edge AI Technologies ▪ Novel Defense Paradigms for Future AI Systems ▪ Strategic Roadmap for Long-Term AI Security Track 11: Explainable and Transparent AI ▪ Standardization of Black-Box Model Interpretability ▪ High-Stakes Applications of Transparent AI (e.g., Legal, Financial) ▪ Quantifying User Trust in AI-Driven Decisions ▪ Balancing Explainability and Model Efficiency ▪ Cross-Cultural Adaptation of Explainability Tools Track 12: Adversarial Robustness in AI Systems ▪ Generation and Detection of Adversarial Perturbations ▪ Impact Analysis of Adversarial Attacks on AI Models ▪ Enhancing System Robustness and Fault Tolerance ▪ Threat Modeling for GAN-Enabled AI Systems ▪ Real-World Adversarial Attack Scenarios ▪ Game-Theoretic Approaches to Defense Mechanisms ▪ Vulnerability Assessment of Multimodal AI Models Track 13: Public Engagement and AI Literacy ▪ Global Educational Frameworks for AI Security ▪ Digital Platforms for Civic Participation in AI Governance
최종 수정: Dunn Carl ()

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AA*92.5STOCACM Symposium on Theory of Computing2026-11-022027-06-06
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관련 저널

CCF정식 명칭영향력 지수출판사ISSN
International Journal of Electronic GovernanceInderscience1742-7509
AIEEE Transactions on Multimedia9.7IEEE1520-9210
CKnowledge-Based Systems7.2Elsevier0950-7051
BSoftware & Systems Modeling3.2Springer1619-1366
AIEEE Transactions on Computers3.8IEEE0018-9340
CFuture Generation Computer Systems5.9Elsevier0167-739X
CNeurocomputing6.5Elsevier0925-2312
CPattern Recognition Letters3.9Elsevier0167-8655
BPattern Recognition7.6Elsevier0031-3203
IEEE Access3.6IEEE2169-3536

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