会议信息

TrustCom 2025: International Conference on Trust, Security and Privacy in Computing and Communications

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TrustCom
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截稿日期:
2025-08-01
通知日期:
2025-10-01
会议日期:
2025-11-14
会议地点:
Guiyang, China
届数:
24
CCF: C   ICORE: B   浏览: 6801321   关注: 335   参加: 127

会伴指数 (CP-I)

65.9 / 100
全站第 415 名 / 共 5,682 个会议 · 前 8%

安全与隐私 第 35 / 360 网络与通信 第 52 / 864

学术认可 (35%)
72
投稿选择性 (20%) 无数据 —— 按中性基准 50 分计入 —
会议传承 (20%)
87
社区关注 (10%)
81
资料公开度 (15%)
35

用到的输入: 收录等级：CCF C, ICORE B · 有据可查的届次：24 · 在会伴关注它的研究者：335 人 · 过去 24 个月打开过本页的研究者：31 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 80% —— 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 2026-09-20

征稿

TrustCom 2025 (International Conference on Trust, Security and Privacy in Computing and Communications) is a CCF C / ICORE B conference held in Guiyang, China on 2025-11-14. The paper submission deadline is 2025-08-01. Acceptance notifications are sent on 2025-10-01.

As computer systems, communication networks and artificial intelligence (AI) undergo rapid development, accompanied by increasing complexity, the expectations of users for trust, security, and privacy have grown considerably. This presents a significant challenge, as traditional security technologies and measures may struggle to meet the evolving demands within open, dynamic, heterogeneous, mobile, wireless, and distributed computing environments. Consequently, the imperative is to construct systems and networks that enable users to access more comprehensive services while concurrently upholding trust, security, and privacy. In response to this challenge, trusted computing and communications have emerged as pivotal and innovative technologies, capturing the heightened interest of researchers. These advancements offer promising solutions to address the intricate demands of contemporary computing landscapes. The IEEE TrustCom-2025 (24th IEEE International Conference on Trust, Security and Privacy in Computing and Communications) is a forum for presenting leading works on trusted computing, communications, networking and machine learning, with regard to trust, security, privacy, reliability, dependability, survivability, availability, and fault tolerance aspects of computer systems and networks, as well as AI. The 24th IEEE TrustCom continues the tradition of successful IEEE TrustCom conferences held from 2002 to 2024 across Asia, Europe, Australia, and America. It will feature sessions of regular presentations, workshops, tutorials and keynote speeches. TrustCom-2025 will be hosted in Guiyang, China. Guiyang is the capital of Guizhou province of the People's Republic of China. Guiyang is the capital city of Guizhou Province, located in southwestern China. It is known for its cool climate, mountainous landscape, and rich cultural heritage, awarded the title of “National Forest City”. Prospective authors are invited to submit their papers to TrustCom-2025. Accepted papers will be submitted for possible inclusion into IEEE Xplore subject to meeting IEEE Xplore's scope and quality requirements. The authors of selected best papers will be invited post conference to extend their contributions for special issues of prestigious journals to be planned in conjunction with the conference. Topics Track 1: Trust Track • Trust semantics, metrics and models • Trusted computing platform • Trusted network computing • Trusted operating systems • Trusted software and applications • Trust in social networks • Trust in e-commerce and e-government • Trust in mobile and wireless communications • Risk and reputation management • Survivable computer systems/networks • Trust in 5G networks • Miscellaneous trust issues in Cyber Security • System reverse engineering • Watermarking and security • Cryptanalysis and security solutions Track 2: Security Track • Network and cyber security • Computer security • Database security • Web applications security • Security policy, model and architecture • Security in social networks • Security in parallel and distributed systems • Security in mobile and wireless communications • Security in cloud/pervasive computing • Authentication, authorization and accounting • Security of 5G Networks • Miscellaneous security issues • Steganography and steganalysis • Security-aware facial recognition Track3: Privacy Track • Privacy in web-based applications and services • Privacy in database systems • Privacy in parallel and distributed systems • Privacy in cloud/pervasive computing • Privacy in mobile and wireless communications • Privacy in e-commerce and e-government • Privacy in network deployment and management • Privacy and trust • Privacy and security • Privacy and anonymity • Privacy preservation in 5G • Miscellaneous privacy issues • Privacy-preserving biometrics Track 4: Forensics and Analytics Track • Anti-forensics and analytics • Big data forensics • CCTV forensics • Cloud forensics • Computational forensics • Cyber-physical system forensics • Datamining for forensics • Fingerprint forensics • Image forensics • Malware forensics • Mobile app forensics (e.g. Skype, WeChat and Facebook) • Mobile device forensics • Multimedia forensics • Network forensics Track 5: Emerging Tech Track • Emerging hardware security • Emerging security problems and solutions in edge/fog computing • Emerging paradigms of deep learning in security • Emerging applications of reinforcement learning for securing networks • Emerging secure mechanisms for service delivery models • Emerging quantum safe cryptography for 5G • Emerging techniques in intelligent transportation systems • Emerging network attacks & anomalies detection and prevention • Emerging approaches to cybersecurity • Emerging techniques in identity management • Emerging approaches of smart contract and distributed ledger • Emerging blockchain techniques Track 6: AI Trust Track • Robustness and safety of machine learning • Attacks on AI models • Non-discrimination and fairness of AI • Transparency and explainability of AI • Auditability and accountability of AI • Privacy preservation of AI • Data truth discovery • Trust framework for AI model generation and usage • Trusted computing platform for big data learning • Adversarial learning • Trustworthy data fusion
由 Dou Sun 最后更新于

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