NDSS 2025 - Explanation As A Watermark

SESSION Session 3D: AI Safety

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Authors, Creators & Presenters: Shuo Shao (Zhejiang University), Yiming Li (Zhejiang University), Hongwei Yao (Zhejiang University), Yiling He (Zhejiang University), Zhan Qin (Zhejiang University), Kui Ren (Zhejiang University)
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PAPER Explanation as a Watermark: Towards Harmless and Multi-bit Model Ownership Verification via Watermarking Feature Attribution Ownership verification is currently the most critical and widely adopted post-hoc method to safeguard model copyright. In general, model owners exploit it to identify whether a given suspicious third-party model is stolen from them by examining whether it has particular properties 'inherited' from their released models. Currently, backdoor-based model watermarks are the primary and cutting-edge methods to implant such properties in the released models. However, backdoor-based methods have two fatal drawbacks, including harmfulness and ambiguity. The former indicates that they introduce maliciously controllable misclassification behaviors ( backdoor) to the watermarked released models. The latter denotes that malicious users can easily pass the verification by finding other misclassified samples, leading to ownership ambiguity.

In this paper, we argue that both limitations stem from the 'zero-bit' nature of existing watermarking schemes, where they exploit the status (misclassified) of predictions for verification. Motivated by this understanding, we design a new watermarking paradigm "Explanation as a Watermark (EaaW)", that implants verification behaviors into the explanation of feature attribution instead of model predictions. Specifically, EaaW embeds a 'multi-bit' watermark into the feature attribution explanation of specific trigger samples without changing the original prediction. We correspondingly design the watermark embedding and extraction algorithms inspired by explainable artificial intelligence. In particular, our approach can be used for different tasks (image classification and text generation). Extensive experiments verify the effectiveness and harmlessness of our EaaW and its resistance to potential attacks.

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ABOUT NDSS
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.

NDSS 2025 - THEMIS: Regulating Textual Inversion For Personalized Concept Censorship

SESSION Session 3D: Al Safety

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Authors, Creators & Presenters: Yutong Wu (Nanyang Technological University), Jie Zhang (Centre for Frontier AI Research, Agency for Science, Technology and Research (A*STAR), Singapore), Florian Kerschbaum (University of Waterloo), Tianwei Zhang (Nanyang Technological University)
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PAPER THEMIS: Regulating Textual Inversion for Personalized Concept Censorship

Personalization has become a crucial demand in the Generative AI technology. As the pre-trained generative model (e.g., stable diffusion) has fixed and limited capability, it is desirable for users to customize the model to generate output with new or specific concepts. Fine-tuning the pre-trained model is not a promising solution, due to its high requirements of computation resources and data. Instead, the emerging personalization approaches make it feasible to augment the generative model in a lightweight manner. However, this also induces severe threats if such advanced techniques are misused by malicious users, such as spreading fake news or defaming individual reputations. Thus, it is necessary to regulate personalization models (i.e., achieve concept censorship) for their development and advancement. In this paper, we focus on the regulation of a popular personalization technique dubbed textbf{Textual Inversion (TI)}, which can customize Text-to-Image (T2I) generative models with excellent performance. TI crafts the word embedding that contains detailed information about a specific object. Users can easily add the word embedding to their local T2I model, like the public Stable Diffusion (SD) model, to generate personalized images. The advent of TI has brought about a new business model, evidenced by the public platforms for sharing and selling word embeddings (e.g., Civitai [1]). Unfortunately, such platforms also allow malicious users to misuse the word embeddings to generate unsafe content, causing damages to the concept owners. We propose THEMIS to achieve the personalized concept censorship. Its key idea is to leverage the backdoor technique for good by injecting positive backdoors into the TI embeddings. Briefly, the concept owner selects some sensitive words as triggers during the training of TI, which will be censored for normal use. In the subsequent generation stage, if a malicious user combines the sensitive words with the personalized embeddings as final prompts, the T2I model will output a pre-defined target image rather than images including the desired malicious content. To demonstrate the effectiveness of THEMIS, we conduct extensive experiments on the TI embeddings with Latent Diffusion and Stable Diffusion, two prevailing open-sourced T2I models. The results demonstrate that THEMIS is capable of preventing Textual Inversion from cooperating with sensitive words meanwhile guaranteeing its pristine utility. Furthermore, THEMIS is general to different uses of sensitive words, including different locations, synonyms, and combinations of sensitive words. It can also resist different types of potential and adaptive attacks. Ablation studies are also conducted to verify our design.

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ABOUT NDSS
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.
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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.

NDSS 2025 - A Key-Driven Framework For Identity-Preserving Face Anonymization

SESSION Session 3D: Al Safety

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Authors, Creators & Presenters: Miaomiao Wang (Shanghai University), Guang Hua (Singapore Institute of Technology), Sheng Li (Fudan University), Guorui Feng (Shanghai University)
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PAPER A Key-Driven Framework for Identity-Preserving Face Anonymization

Virtual faces are crucial content in the metaverse. Recently, attempts have been made to generate virtual faces for privacy protection. Nevertheless, these virtual faces either permanently remove the identifiable information or map the original identity into a virtual one, which loses the original identity forever. In this study, we first attempt to address the conflict between privacy and identifiability in virtual faces, where a key-driven face anonymization and authentication recognition (KFAAR) framework is proposed. Concretely, the KFAAR framework consists of a head posture-preserving virtual face generation (HPVFG) module and a key-controllable virtual face authentication (KVFA) module. The HPVFG module uses a user key to project the latent vector of the original face into a virtual one. Then it maps the virtual vectors to obtain an extended encoding, based on which the virtual face is generated. By simultaneously adding a head posture and facial expression correction module, the virtual face has the same head posture and facial expression as the original face. During the authentication, we propose a KVFA module to directly recognize the virtual faces using the correct user key, which can obtain the original identity without exposing the original face image. We also propose a multi-task learning objective to train HPVFG and KVFA. Extensive experiments demonstrate the advantages of the proposed HPVFG and KVFA modules, which effectively achieve both facial anonymity and identifiability.

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ABOUT NDSS
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.

NDSS 2025 - Hitchhiking Vaccine: Enhancing Botnet Remediation With Remote Code Deployment Reuse

SESSION Session 3C: Mobile Security

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Authors, Creators & Presenters: Runze Zhang (Georgia Institute of Technology), Mingxuan Yao (Georgia Institute of Technology), Haichuan Xu (Georgia Institute of Technology), Omar Alrawi (Georgia Institute of Technology), Jeman Park (Kyung Hee University), Brendan Saltaformaggio (Georgia Institute of Technology)
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PAPER Hitchhiking Vaccine: Enhancing Botnet Remediation With Remote Code Deployment Reuse For decades, law enforcement and commercial entities have attempted botnet takedowns with mixed success. These efforts, relying on DNS sink-holing or seizing C&C infrastructure, require months of preparation and often omit the cleanup of left-over infected machines. This allows botnet operators to push updates to the bots and re-establish their control. In this paper, we expand the goal of malware takedowns to include the covert and timely removal of frontend bots from infected devices. Specifically, this work proposes seizing the malware's built-in update mechanism to distribute crafted remediation payloads. Our research aims to enable this necessary but challenging remediation step after obtaining legal permission. We developed ECHO, an automated malware forensics pipeline that extracts payload deployment routines and generates remediation payloads to disable or remove the frontend bots on infected devices. Our study of 702 Android malware shows that 523 malware can be remediated via ECHO's takedown approach, ranging from covertly warning users about malware infection to uninstalling the malware.

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ABOUT NDSS
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.
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Our thanks to the **[Network and Distributed System Security (NDSS) Symposium][1]** for publishing their Creators, Authors and Presenter’s superb **[NDSS Symposium 2025 Conference][2]** content on the **[organization’s’][1]** **[YouTube][3]** channel.

NDSS 2025 - Detecting And Interpreting Inconsistencies In App Behaviors

SESSION Session 3C: Mobile Security

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Authors, Creators & Presenters: Chang Yue (Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China), Kai Chen (Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China), Zhixiu Guo (Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China), Jun Dai, Xiaoyan Sun (Department of Computer Science, Worcester Polytechnic Institute), Yi Yang (Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China)
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PAPER What's Done Is Not What's Claimed: Detecting and Interpreting Inconsistencies in App Behaviors The widespread use of mobile apps meets user needs but also raises security concerns. Current security analysis methods often fall short in addressing user concerns as they do not parse app behavior from the user's standpoint, leading to users not fully understanding the risks within the apps and unknowingly exposing themselves to privacy breaches. On one hand, their analysis and results are usually presented at the code level, which may not be comprehensible to users. On the other hand, they neglect to account for the users' perceptions of the app behavior. In this paper, we aim to extract user-related behaviors from apps and explain them to users in a comprehensible natural language form, enabling users to perceive the gap between their expectations and the app's actual behavior, and assess the risks within the inconsistencies independently. Through experiments, our tool InconPreter is shown to effectively extract inconsistent behaviors from apps and provide accurate and reasonable explanations. InconPreter achieves an inconsistency identification precision of 94.89% on our labeled dataset, and a risk analysis accuracy of 94.56% on widely used Android malware datasets. When applied to real-world (wild) apps, InconPreter identifies 1,664 risky inconsistent behaviors from 413 apps out of 10,878 apps crawled from Google Play, including the leakage of location, SMS, and contact information, as well as unauthorized audio recording, etc., potentially affecting millions of users. Moreover, InconPreter can detect some behaviors that are not identified by previous tools, such as unauthorized location disclosure in various scenarios (e.g. taking photos, chatting, and enabling mobile hotspots, etc.). We conduct a thorough analysis of the discovered behaviors to deepen the understanding of inconsistent behaviors, thereby helping users better manage their privacy and providing insights for privacy design in further app development.

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ABOUT NDSS
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.
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Our thanks to the **[Network and Distributed System Security (NDSS) Symposium][1]** for publishing their Creators, Authors and Presenter’s superb **[NDSS Symposium 2025 Conference][2]** content on the **[organization’s’][1]** **[YouTube][3]** channel.

NDSS 2025 - Understanding Miniapp Malware: Identification, Dissection, And Characterization

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SESSION Session 3C: Mobile Security

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Authors, Creators & Presenters: Yuqing Yang (The Ohio State University), Yue Zhang (Drexel University), Zhiqiang Lin (The Ohio State University)
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PAPER Understanding Miniapp Malware: Identification, Dissection, and Characterization Super apps, serving as centralized platforms that manage user information and integrate third-party miniapps, have revolutionized mobile computing but also introduced significant security risks from malicious miniapps. Despite the mandatory miniapp vetting enforced to the built-in miniapp store, the threat of evolving miniapp malware persists, engaging in a continual cat-and-mouse game with platform security measures. However, compared with traditional paradigms such as mobile and web computing, there has been a lack of miniapp malware dataset available for the community to explore, hindering the generation of crucial insights and the development of robust detection techniques. In response to this, this paper addresses the scarcely explored territory of malicious miniapp analysis, dedicating over three year to identifying, dissecting, and examining the risks posed by these miniapps, resulting in the first miniapp malware dataset now available to aid future studies to enhance the security of super app ecosystems. To build the dataset, our primary focus has been on the WeChat platform, the largest super app, hosting millions of miniapps and serving a billion users. Over an extensive period, we collected over 4.5 million miniapps, identifying a subset (19, 905) as malicious through a rigorous cross-check process: 1) applying static signatures derived from real-world cases, and 2) confirming that the miniapps were delisted and removed from the market by the platform. With these identified samples, we proceed to characterize them, focusing on their lifecycle including propagation, activation, as well as payload execution. Additionally, we analyzed the collected malware samples using real-world cases to demonstrate their practical security impact. Our findings reveal that these malware frequently target user privacy, leverage social network sharing capabilities to disseminate unauthorized services, and manipulate the advertisement-based revenue model to illicitly generate profits. These actions result in significant privacy and financial harm to both users and the platform.

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ABOUT NDSS
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.
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Our thanks to the **[Network and Distributed System Security (NDSS) Symposium][1]** for publishing their Creators, Authors and Presenter’s superb **[NDSS Symposium 2025 Conference][2]** content on the **[organization’s’][1]** **[YouTube][3]** channel.

NDSS 2025 - The Skeleton Keys: A Large Scale Analysis Of Credential Leakage In Mini-Apps

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SESSION Session 3C: Mobile Security

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Authors, Creators & Presenters: Yizhe Shi (Fudan University), Zhemin Yang (Fudan University), Kangwei Zhong (Fudan University), Guangliang Yang (Fudan University), Yifan Yang (Fudan University), Xiaohan Zhang (Fudan University), Min Yang (Fudan University)

PAPER The Skeleton Keys: A Large Scale Analysis of Credential Leakage in Mini-apps In recent years, the app-in-app paradigm, involving super-app and mini-app, has been becoming increasingly popular in the mobile ecosystem. Super-app platforms offer mini-app servers access to a suite of powerful and sensitive services, including payment processing and mini-app analytics. This access empowers mini-app servers to enhance their offerings with robust and practical functionalities and better serve their mini-apps. To safeguard these essential services, a credential-based authentication system has been implemented, facilitating secure access between super-app platforms and mini-app servers. However, the design and workflow of the crucial credential mechanism still remain unclear. More importantly, its security has not been comprehensively understood or explored to date. In this paper, we conduct the first systematic study of the credential system in the app-in-app paradigm and draw the security landscape of credential leakage risks. Consequently, our study shows that 21 popular super-app platforms delegate sensitive services to mini-app servers with seven types of credentials. Unfortunately, these credentials may suffer from leakage threats caused by malicious mini-app users, posing serious security threats to both super-app platforms and mini-app servers. Then, we design and implement a novel credential security verification tool, called KeyMagnet, that can effectively assess the security implications of credential leakage. To tackle unstructured and dynamically retrieved credentials in the app-in-app paradigm, KeyMagnet extracts and understands the semantics of credential-use in mini-apps and verifies their security. Last, by applying KeyMagnet on 413,775 real-world mini-apps of 6 super-app platforms, 84,491 credential leaks are detected, spanning over 54,728 mini-apps. We confirm credential leakage can cause serious security hazards, such as hijacking the accounts of all mini-app users and stealing users' sensitive data. In response, we have engaged in responsible vulnerability disclosure with the corresponding developers and are actively helping them resolve these issues. At the time of writing, 89 reported issues have been assigned with CVE IDs.

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ABOUT NDSS
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.
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Our thanks to the **[Network and Distributed System Security (NDSS) Symposium][1]** for publishing their Creators, Authors and Presenter’s superb **[NDSS Symposium 2025 Conference][2]** content on the **[organization’s’][1]** **[YouTube][3]** channel.

NDSS 2025 - EvoCrawl: Exploring Web Application Code And State Using Evolutionary Search

SESSION Session 3C: Mobile Security

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Authors, Creators & Presenters: Xiangyu Guo (University of Toronto), Akshay Kawlay (University of Toronto), Eric Liu (University of Toronto), David Lie (University of Toronto)
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PAPER EvoCrawl: Exploring Web Application Code and State using Evolutionary Search As more critical services move onto the web, it has become increasingly important to detect and address vulnerabilities in web applications. These vulnerabilities only occur under specific conditions: when 1) the vulnerable code is executed and 2) the web application is in the required state. If the application is not in the required state, then even if the vulnerable code is executed, the vulnerability may not be triggered. Previous work naively explores the application state by filling every field and triggering every JavaScript event before submitting HTML forms. However, this simplistic approach can fail to satisfy constraints between the web page elements, as well as input format constraints. To address this, we present EvoCrawl, a web crawler that uses evolutionary search to efficiently find different sequences of web interactions. EvoCrawl finds sequences that can successfully submit inputs to web applications and thus explore more code and server-side states than previous approaches. To assess the benefits of EvoCrawl we evaluate it against three state-of-the-art vulnerability scanners on ten web applications. We find that EvoCrawl achieves better code coverage due to its ability to execute code that can only be executed when the application is in a particular state. On average, EvoCrawl achieves a 59% increase in code coverage and successfully submits HTML forms 5x more frequently than the next best tool. By integrating IDOR and XSS vulnerability scanners, we used EvoCrawl to find eight zero-day IDOR and XSS vulnerabilities in WordPress, HotCRP, Kanboard, ImpressCMS, and GitLab.

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ABOUT NDSS
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.
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Our thanks to the **[Network and Distributed System Security (NDSS) Symposium][1]** for publishing their Creators, Authors and Presenter’s superb **[NDSS Symposium 2025 Conference][2]** content on the **[organization’s’][1]** **[YouTube][3]** channel.

NDSS 2025 - Detecting IMSI-Catchers By Characterizing Identity Exposing Messages In Cellular Traffic

SESSION Session 3B: Wireless, Cellular & Satellite Security

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Authors, Creators & Presenters: Jiska Classen (Hasso Plattner Institute, University of Potsdam), Alexander Heinrich (TU Darmstadt, Germany), Fabian Portner (TU Darmstadt, Germany), Felix Rohrbach (TU Darmstadt, Germany), Matthias Hollick (TU Darmstadt, Germany)
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PAPER
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Starshields for iOS: Navigating the Security Cosmos in Satellite Communication
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Apple has integrated satellite communication into their latest iPhones, enabling emergency communication, road- side assistance, location sharing with friends, iMessage, and SMS. This technology allows communication when other wireless services are unavailable. However, the use of satellites poses restrictions on bandwidth and delay, making it difficult to use modern communication protocols with their security and privacy guarantees. To overcome these challenges, Apple designed and implemented a proprietary satellite communication protocol to address these limitations. We are the first to successfully reverse-engineer this protocol and analyze its security and privacy properties. In addition, we develop a simulation-based testbed for testing emergency services without causing emergency calls. Our tests reveal protocol and infrastructure design issues. For example, compact protocol messages come at the cost of missing integrity protection and require an internet-based setup phase. We further demonstrate various restriction bypasses, such as misusing location sharing to send arbitrary text messages on old iOS versions, and sending iMessages over satellite from region-locked countries. These bypasses allow us to overcome censorship and operator control of text messaging services.
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ABOUT NDSS
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.
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Our thanks to the **[Network and Distributed System Security (NDSS) Symposium][1]** for publishing their Creators, Authors and Presenter’s superb **[NDSS Symposium 2025 Conference][2]** content on the **[organization’s’][1]** **[YouTube][3]** channel.

NDSS 2025 - Spatial-Domain Wireless Jamming With Reconfigurable Intelligent Surfaces

SESSION Session 3B: Wireless, Cellular & Satellite Security

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Authors, Creators & Presenters: Philipp Mackensen (Ruhr University Bochum), Paul Staat (Max Planck Institute for Security and Privacy), Stefan Roth (Ruhr University Bochum), Aydin Sezgin (Ruhr University Bochum), Christof Paar (Max Planck Institute for Security and Privacy), Veelasha Moonsamy (Ruhr University Bochum)
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PAPER
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Spatial-Domain Wireless Jamming with Reconfigurable Intelligent Surfaces
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Wireless communication infrastructure is a cornerstone of modern digital society, yet it remains vulnerable to the persistent threat of wireless jamming. Attackers can easily create radio interference to overshadow legitimate signals, leading to denial of service. The broadcast nature of radio signal propagation makes such attacks possible in the first place, but at the same time poses a challenge for the attacker: The jamming signal does not only reach the victim device but also other neighboring devices, preventing precise attack targeting. In this work, we solve this challenge by leveraging the emerging RIS technology, for the first time, for precise delivery of jamming signals. In particular, we propose a novel approach that allows for environment-adaptive spatial control of wireless jamming signals, granting a new degree of freedom to perform jamming attacks. We explore this novel method with extensive experimentation and demonstrate that our approach can disable the wireless communication of one or multiple victim devices while leaving neighboring devices unaffected. Notably, our method extends to challenging scenarios where wireless devices are very close to each other: We demonstrate complete denial-of-service of a Wi-Fi device while a second device located at a distance as close as 5 mm remains unaffected, sustaining wireless communication at a data rate of 25 Mbit/s. Lastly, we conclude by proposing potential countermeasures to thwart RIS-based spatial domain wireless jamming attacks.
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ABOUT NDSS
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][1]** for publishing their Creators, Authors and Presenter’s superb **[NDSS Symposium 2025 Conference][2]** content on the **[organization’s’][1]** **[YouTube][3]** channel.

NDSS 2025 - Detecting IMSI-Catchers By Characterizing Identity Exposing Messages In Cellular Traffic

SESSION Session 3B: Wireless, Cellular & Satellite Security

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Authors, Creators & Presenters: Tyler Tucker (University of Florida), Nathaniel Bennett (University of Florida), Martin Kotuliak (ETH Zurich), Simon Erni (ETH Zurich), Srdjan Capkun (ETH Zuerich), Kevin Butler (University of Florida), Patrick Traynor (University of Florida)
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PAPER
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Detecting IMSI-Catchers By Characterizing Identity Exposing Messages In Cellular Traffic
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IMSI-Catchers allow parties other than cellular network providers to covertly track mobile device users. While the research community has developed many tools to combat this problem, current solutions focus on correlated behavior and are therefore subject to substantial false classifications. In this paper, we present a standards-driven methodology that focuses on the messages an IMSI-Catcher textit(must) use to cause mobile devices to provide their permanent identifiers. That is, our approach focuses on causal attributes rather than correlated ones. We systematically analyze message flows that would lead to IMSI exposure (most of which have not been previously considered in the research community), and identify 53 messages an IMSI-Catcher can use for its attack. We then perform a measurement study on two continents to characterize the ratio in which connections use these messages in normal operations.
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ABOUT NDSS
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][1]** for publishing their Creators, Authors and Presenter’s superb **[NDSS Symposium 2025 Conference][2]** content on the **[organization’s’][1]** **[YouTube][3]** channel.

NDSS 2025 - Time-Varying Bottleneck Links In LEO Satellite Networks

SESSION Session 3B: Wireless, Cellular & Satellite Security

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Authors, Creators & Presenters: Yangtao Deng (Tsinghua University), Qian Wu (Tsinghua University), Zeqi Lai (Tsinghua University), Chenwei Gu (Tsinghua University), Hewu Li (Tsinghua University), Yuanjie Li (Tsinghua University), Jun Liu (Tsinghua University)
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PAPER
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Time-varying Bottleneck Links in LEO Satellite Networks: Identification, Exploits, and Countermeasures In this paper, we perform a multifaceted study on the security risk involved by the unique time-varying bottleneck links in emerging Low-Earth Orbit (LEO) satellite networks (LSNs). We carry out our study in three steps. First, we profile the spatial and temporal characteristics of bottleneck links and how they might be exploited for bottleneck identification. Thus, the bottleneck links imposes a new risk of link flooding attack (LFA) on LSNs. Second, we propose SKYFALL, a new LFA risk analyzer that enables satellite network operators to simulate various LFA behaviors and comprehensively analyze the consequences on LSN services. Concretely, SKYFALL's analysis based on real-world information of operational LSNs demonstrates that the throughput of legal background traffic could be reduced by a factor of 3.4 if an attacker can manipulate a number of compromised user terminals to continuously congest the bottleneck links. Based on our analysis, we finally discuss the limitations of traditional LFA countermeasures and propose new mitigation strategies for LSNs.
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ABOUT NDSS
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][1]** for publishing their Creators, Authors and Presenter’s superb **[NDSS Symposium 2025 Conference][2]** content on the **[organization’s’][1]** **[YouTube][3]** channel.

NDSS 2025 - Magmaw: Modality-Agnostic Adversarial Attacks

SESSION Session 3B: Wireless, Cellular & Satellite Security

Authors, Creators & Presenters: Jung-Woo Chang (University of California, San Diego), Ke Sun (University of California, San Diego), Nasimeh Heydaribeni (University of California, San Diego), Seira Hidano (KDDI Research, Inc.), Xinyu Zhang (University of California, San Diego), Farinaz Koushanfar (University of California, San Diego)
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PAPER
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Magmaw: Modality-Agnostic Adversarial Attacks on Machine Learning-Based Wireless Communication Systems
Machine Learning (ML) has been instrumental in enabling joint transceiver optimization by merging all physical layer blocks of the end-to-end wireless communication systems. Although there have been a number of adversarial attacks on ML-based wireless systems, the existing methods do not provide a comprehensive view including multi-modality of the source data, common physical layer protocols, and wireless domain constraints. This paper proposes Magmaw, a novel wireless attack methodology capable of generating universal adversarial perturbations for any multimodal signal transmitted over a wireless channel. We further introduce new objectives for adversarial attacks on downstream applications. We adopt the widely used defenses to verify the resilience of Magmaw. For proof-of-concept evaluation, we build a real-time wireless attack platform using a software-defined radio system. Experimental results demonstrate that Magmaw causes significant performance degradation even in the presence of strong defense mechanisms. Furthermore, we validate the performance of Magmaw in two case studies: encrypted communication channel and channel modality-based ML model. Our code is available at [https://github.com/juc023/Magmaw].
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ABOUT NDSS
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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.
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Our thanks to the **[Network and Distributed System Security (NDSS) Symposium][1]** for publishing their Creators, Authors and Presenter’s superb **[NDSS Symposium 2025 Conference][2]** content on the **[organization’s’][1]** **[YouTube][3]** channel.

NDSS 2025 - MineShark: Cryptomining Traffic Detection At Scale

SESSION Session 3A: Network Security 1

Authors, Creators & Presenters: Shaoke Xi (Zhejiang University), Tianyi Fu (Zhejiang University), Kai Bu (Zhejiang University), Chunling Yang (Zhejiang University), Zhihua Chang (Zhejiang University), Wenzhi Chen (Zhejiang University), Zhou Ma (Zhejiang University), Chongjie Chen (HANG ZHOU CITY BRAIN CO., LTD), Yongsheng Shen (HANG ZHOU CITY BRAIN CO., LTD), Kui Ren (Zhejiang University)
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PAPER
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MineShark: Cryptomining Traffic Detection at Scale The rapid growth of cryptojacking and the increase in regulatory bans on cryptomining have prompted organizations to enhance detection ability within their networks. Traditional methods, including rule-based detection and deep packet inspection, fall short in timely and comprehensively identifying new and encrypted mining threats. In contrast, learning-based techniques show promise by identifying content-agnostic traffic patterns, adapting to a wide range of cryptomining configurations. However, existing learning-based systems often lack scalability in real-world detection, primarily due to challenges with unlabeled, imbalanced, and high-speed traffic inputs. To address these issues, we introduce MineShark, a system that identifies robust patterns of mining traffic to distinguish between vast quantities of benign traffic and automates the confirmation of model outcomes through active probing to prevent an overload of model alarms. As model inference labels are progressively confirmed, MineShark conducts self-improving updates to enhance model accuracy. MineShark is capable of line-rate detection at various traffic volume scales with the allocation of different amounts of CPU and GPU resources. In a 10 Gbps campus network deployment lasting ten months, MineShark detected cryptomining connections toward 105 mining pools ahead of concurrently deployed commercial systems, 17.6% of which were encrypted. It automatically filtered over 99.3% of false alarms and achieved an average packet processing throughput of 1.3 Mpps, meeting the line-rate demands of a 10 Gbps network, with a negligible loss rate of 0.2%. We publicize MineShark for broader use.
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ABOUT NDSS
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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.
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Our thanks to the **[Network and Distributed System Security (NDSS) Symposium][1]** for publishing their Creators, Authors and Presenter’s superb **[NDSS Symposium 2025 Conference][2]** content on the **[organization’s’][1]** **[YouTube][3]** channel.

NDSS 2025 - The Discriminative Power Of Cross-layer RTTs In Fingerprinting Proxy Traffic

SESSION Session 3A: Network Security 1

Authors, Creators & Presenters: Diwen Xue (University of Michigan), Robert Stanley (University of Michigan), Piyush Kumar (University of Michigan), Roya Ensafi (University of Michigan)
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PAPER
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The Discriminative Power of Cross-layer RTTs in Fingerprinting Proxy Traffic The escalating global trend of Internet censorship has necessitated an increased adoption of proxy tools, especially obfuscated circumvention proxies. These proxies serve a fundamental need for access and connectivity among millions in heavily censored regions. However, as the use of proxies expands, so do censors' dedicated efforts to detect and disrupt such circumvention traffic to enforce their information control policies. In this paper, we bring out the presence of an inherent fingerprint for detecting obfuscated proxy traffic. The fingerprint is created by the misalignment of transport- and application-layer sessions in proxy routing, which is reflected in the discrepancy in Round Trip Times (RTTs) across network layers. Importantly, being protocol-agnostic, the fingerprint enables an adversary to effectively target multiple proxy protocols simultaneously. We conduct an extensive evaluation using both controlled testbeds and real-world traffic, collected from a partner ISP, to assess the fingerprint's potential for exploitation by censors. In addition to being of interest on its own, our timing-based fingerprinting vulnerability highlights the deficiencies in existing obfuscation approaches. We hope our study brings the attention of the circumvention community to packet timing as an area of concern and leads to the development of more sustainable countermeasures.
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ABOUT NDSS
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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][1]** for publishing their Creators, Authors and Presenter’s superb **[NDSS Symposium 2025 Conference][2]** content on the **[organization’s’][1]** **[YouTube][3]** channel.

NDSS 2025 - Heimdall: Towards Risk-Aware Network Management Outsourcing

SESSION Session 3A: Network Security 1

Authors, Creators & Presenters: Yuejie Wang (Peking University), Qiutong Men (New York University), Yongting Chen (New York University Shanghai), Jiajin Liu (New York University Shanghai), Gengyu Chen (Carnegie Mellon University), Ying Zhang (Meta), Guyue Liu (Peking University), Vyas Sekar (Carnegie Mellon University)

PAPER PAPER Heimdall: Towards Risk-Aware Network Management Outsourcing

Enterprises are increasingly outsourcing network management (e.g., troubleshooting routing issues) to reduce cost and improve efficiency, either by hiring third-party contractors or by outsourcing to third-party vendors. Unfortunately, recent events have shown that this outsourcing model has become a new source of network incidents in customer networks. In this work, we argue that a risk-aware outsourcing approach is needed that enables customers to measure and assess risk transparently and make informed decisions to minimize harm. We first concretely define the notion of risk in the context of outsourced network management and then present an end-to-end framework, called Heimdall, which enables enterprises to assess, monitor, and respond to risk. Heimdall automatically builds a dependency graph to accurately assess the risk of an outsourced task, and uses a fine-grained reference monitor to monitor and mitigate potential risks during operation. Our expert validation results show that Heimdall effectively controls risk for outsourced network operations, resolving 92% of practical issues at the minimal risk level while incurring only a marginal timing overhead of approximately 7%.

ABOUT NDSS 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 organization’s’ YouTube channel.