NDSS 2025 – Tweezers
好的,我现在需要帮用户总结一篇文章的内容,控制在100个字以内,并且不需要特定的开头。首先,我得仔细阅读用户提供的文章内容,找出关键信息。 文章主要介绍了一个名为Tweezers的框架,用于通过事件属性为中心的推文嵌入来检测安全事件。Twitter作为传播网络安全威胁情报的重要平台,但面临大量噪音和语义理解的挑战。现有的方法要么基于关键词过滤,效果不佳;要么忽视事件覆盖的全面性。研究者提出了一种新的嵌入方法,提高了检测的准确性和覆盖率,并开发了Tweezers框架,检测到两倍于现有基线的事件。此外,他们还展示了两个应用:安全事件趋势分析和识别有信息量的安全用户。 接下来,我需要将这些信息浓缩到100字以内。重点包括:Tweezers框架、基于推文嵌入检测安全事件、解决Twitter上的挑战、提高准确性和覆盖率、检测到更多事件以及两个应用。 最后,确保语言简洁明了,直接描述内容,不使用“文章总结”等开头。 </think> 研究者提出了一种基于事件属性的推文嵌入方法和框架Tweezers,用于从Twitter中高效检测网络安全事件。该方法通过语义理解提高检测精度和覆盖范围,并开发了两个应用以支持安全趋势分析和用户识别。 2026-1-21 20:0:0 Author: securityboulevard.com(查看原文) 阅读量:0 收藏

Session 9D: Github + OSN Security

Authors, Creators & Presenters: Jian Cui (Indiana University), Hanna Kim (KAIST), Eugene Jang (S2W Inc.), Dayeon Yim (S2W Inc.), Kicheol Kim (S2W Inc.), Yongjae Lee (S2W Inc.), Jin-Woo Chung (S2W Inc.), Seungwon Shin (KAIST), Xiaojing Liao (Indiana University)
PAPER
Tweezers: A Framework For Security Event Detection Via Event Attribution-Centric Tweet Embedding
Twitter is recognized as a crucial platform for the dissemination and gathering of Cyber Threat Intelligence (CTI). Its capability to provide real-time, actionable intelligence makes it a indispensable tool for detecting security events, helping security professionals cope with ever-growing threats. However, the large volume of tweets and inherent noises of human-crafted tweets pose significant challenges in accurately identifying security events. While many studies tried to filter out event-related tweets based on keywords, they are not effective due to their limitation in understanding the semantics of tweets. Another challenge in security event detection from Twitter is the comprehensive coverage of security events. Previous studies emphasized the importance of early detection of security events, but they overlooked the importance of event coverage. To cope with these challenges, in our study, we introduce a novel event attribution-centric tweet embedding method to enable the high precision and coverage of events. Our experiment result shows that the proposed method outperforms existing text and graph-based tweet embedding methods in identifying security events. Leveraging this novel embedding approach, we have developed and implemented a framework, Tweezers, that is applicable to security event detection from Twitter for CTI gathering. This framework has demonstrated its effectiveness, detecting twice as many events compared to established baselines. Additionally, we have showcased two applications, built on Tweezers for the integration and inspection of security events, i.e., security event trend analysis and informative security user identification.
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The Network and Distributed System Security Symposium (NDSS) fosters information exchange among researchers and practitioners of network and distributed system security. The target audience includes those interested in practical aspects of network and distributed system security, with a focus on actual system design and implementation. A major goal is to encourage and enable the Internet community to apply, deploy, and advance the state of available security technologies.

Our thanks to the Network and Distributed System Security (NDSS) Symposium for publishing their Creators, Authors and Presenter’s superb NDSS Symposium 2025 Conference content on the Organizations’ YouTube Channel.

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*** This is a Security Bloggers Network syndicated blog from Infosecurity.US authored by Marc Handelman. Read the original post at: https://www.youtube-nocookie.com/embed/bLBiCjw_IcM?si=bsH-7q6hEQIbC97m


文章来源: https://securityboulevard.com/2026/01/ndss-2025-tweezers/
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