会议信息
RAID 2025: International Symposium on Research in Attacks, Intrusions and Defenses
https://raid2025.github.io/
截稿日期:
2025-04-17
通知日期:
2025-07-09
会议日期:
2025-10-19
会议地点:
Gold Coast, Australia
届数:
28
CCF: b   CORE: a   QUALIS: a2   浏览: 43383   关注: 103   参加: 8

征稿
Since its inception in 1997, the International Symposium on Research in Attacks, Intrusions and Defenses (RAID) has established itself as a venue where leading researchers and practitioners from academia, industry, and the government are given the opportunity to present novel research in a unique venue to an engaged and lively community.

The conference is known for the quality and thoroughness of the reviews of the papers submitted, the desire to build a bridge between research carried out in different communities, and the emphasis given on the need for sound experimental methods and measurement to improve the state of the art in cybersecurity.

We are soliciting research papers on topics covering all well-motivated computer security problems. We care about techniques that identify new real-world threats, techniques to prevent them, to detect them, to mitigate them or to assess their prevalence and their consequences. Measurement papers are encouraged, as well as papers offering public access to new tools or datasets, or experience papers that clearly articulate important lessons learned

Specific topics of interest to RAID include, but are not limited to:

    Cloud security
    Cybercrime and underground economies
    Cyber-physical systems security and threats against critical infrastructures
    Denial-of-Service attacks and defenses
    Digital forensics
    Hardware security
    Intrusion detection and prevention
    IoT security
    Machine learning for security
    Malware and unwanted software
    Mobile security and privacy
    Network security
    Program analysis and reverse engineering
    Security education and training
    Security measurement studies
    Security of machine learning systems
    Software security
    Systems security
    Statistical and adversarial learning for computer security
    Usable security and privacy
    Vulnerability analysis and exploitation techniques
    Web security and privacy

Papers will be judged on novelty, significance, correctness, and clarity. We expect all papers to provide enough detail to enable the reproducibility of their experimental results. We encourage authors to make both the tools and data publicly available.

More information is available at https://raid2025.github.io/. 
最后更新 Dou Sun 在 2025-01-27
录取率
时间提交数录取数录取率(%)
20221393525.2%
20211383223.2%
20201213125.6%
20191663722.3%
20181453322.8%
20171052120%
2016842125%
20151192823.5%
20141132219.5%
2013952223.2%
2012841821.4%
2011872023%
20101042423.1%
2009591728.8%
2008802025%
20071001818%
2006931617.2%
2005831720.5%
20041181411.9%
2003441329.5%
2002641625%
2001551221.8%
2000261453.8%
1998523567.3%
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