Tootfinder

Web 3.0 Requires Data Integrity
New integrity-focused standards are necessary to enable the trusted AI services of tomorrow.
🔐 https://cacm.acm.org/opinion/web-3-0-requires-data-integrity/

The Secure Overview and Analysis OF 3GPP MAC CE
Jin Cao, Yuanyuan Yang, Ruhui Ma, Sheng Li, Hui Li
https://arxiv.org/abs/2506.09502 https://

The Secure Overview and Analysis OF 3GPP MAC CE
To more effectively control and allocate network resources, MAC CE has been introduced into the network protocol, which is a type of control signaling located in the MAC layer. Since MAC CE lacks encryption and integrity protection mechanisms provided by PDCP, the control signaling carried by MAC CE is vulnerable to interception or tampering by attackers during resource scheduling and allocation. Currently, the 3GPP has analyzed the security risks of Layer 1/Layer 2 Triggered Mobility (LTM), wh…

IntenTest: Stress Testing for Intent Integrity in API-Calling LLM Agents
Shiwei Feng, Xiangzhe Xu, Xuan Chen, Kaiyuan Zhang, Syed Yusuf Ahmed, Zian Su, Mingwei Zheng, Xiangyu Zhang
https://arxiv.org/abs/2506.07524

IntenTest: Stress Testing for Intent Integrity in API-Calling LLM Agents
LLM agents are increasingly deployed to automate real-world tasks by invoking APIs through natural language instructions. While powerful, they often suffer from misinterpretation of user intent, leading to the agent's actions that diverge from the user's intended goal, especially as external toolkits evolve. Traditional software testing assumes structured inputs and thus falls short in handling the ambiguity of natural language. We introduce IntenTest, an API-centric stress testing framework th…

Linking Data Citation to Repository Visibility: An Empirical Study
Fakhri Momeni, Janete Saldanha Bach, Brigitte Mathiak, Peter Mutschke
https://arxiv.org/abs/2506.09530

Linking Data Citation to Repository Visibility: An Empirical Study
In today's data-driven research landscape, dataset visibility and accessibility play a crucial role in advancing scientific knowledge. At the same time, data citation is essential for maintaining academic integrity, acknowledging contributions, validating research outcomes, and fostering scientific reproducibility. As a critical link, it connects scholarly publications with the datasets that drive scientific progress. This study investigates whether repository visibility influences data citatio…

#Wasserstoff gilt als Hoffnungsträger für die #Dekarbonisierung, doch beim Transport durch bestehende #Erdgasleitungen gibt es

Pipelines for hydrogen transport: A review of integrity and safety challenges
The European Commission highlights hydrogen as an important energy carrier and chemical feedstock that could help decarbonise sectors otherwise deemed hard-to-abate. Europe’s existing natural gas grid is seen as a promising asset to repurpose for the transportation of hydrogen. This technical report provides a literature review of hydrogen's impact on pipeline materials, particularly steel and polymers. Hydrogen is known to reduce the ductility, fracture toughness, and the fatigue crack growt…

Just finished another round of my ongoing "fix the general lack of good signal integrity and high speed digital info on wikipedia" effort.
Today's focus was making some examples for the article on emphasis https://en.wikipedia.org/wiki/Emphasis_(telecommu…

Emphasis (telecommunications) - Wikipedia

The volume paradox: inferior fronto-occipital fasciculus integrity and connectivity in early blindness https://www.sciencedirect.com/science/article/abs/pii/S0278262625000582 "Neuroimaging of early blindness show paradoxical findings of brain volu…

This https://arxiv.org/abs/2502.07732 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCY_…

When Incentives Backfire, Data Stops Being Human
Progress in AI has relied on human-generated data, from annotator marketplaces to the wider Internet. However, the widespread use of large language models now threatens the quality and integrity of human-generated data on these very platforms. We argue that this issue goes beyond the immediate challenge of filtering AI-generated content -- it reveals deeper flaws in how data collection systems are designed. Existing systems often prioritize speed, scale, and efficiency at the cost of intrinsic …

FDA tells drugmakers to redo studies over data integrity issue
(*CRO misconduct issue)
https://www.statnews.com/pharmalot/2025/04/04/fda-research-cro-raptim-india-data/

FDA tells drugmakers to redo studies run by a contract research firm due to data integrity issues
Citing "objectionable conditions," the agency said there were problems with the way Raptim Research tested medicines in India.

Authenticated Private Set Intersection: A Merkle Tree-Based Approach for Enhancing Data Integrity
Zixian Gong, Zhiyong Zheng, Zhe Hu, Kun Tian, Yi Zhang, Zhedanov Oleksiy, Fengxia Liu
https://arxiv.org/abs/2506.04647

Authenticated Private Set Intersection: A Merkle Tree-Based Approach for Enhancing Data Integrity
Private Set Intersection (PSI) enables secure computation of set intersections while preserving participant privacy, standard PSI existing protocols remain vulnerable to data integrity attacks allowing malicious participants to extract additional intersection information or mislead other parties. In this paper, we propose the definition of data integrity in PSI and construct two authenticated PSI schemes by integrating Merkle Trees with state-of-the-art two-party volePSI and multi-party mPSI pr…

This https://arxiv.org/abs/2506.01173 has been replaced.
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SIFBench: An Extensive Benchmark for Fatigue Analysis
Fatigue-induced crack growth is a leading cause of structural failure across critical industries such as aerospace, civil engineering, automotive, and energy. Accurate prediction of stress intensity factors (SIFs) -- the key parameters governing crack propagation in linear elastic fracture mechanics -- is essential for assessing fatigue life and ensuring structural integrity. While machine learning (ML) has shown great promise in SIF prediction, its advancement has been severely limited by the …

Internal docs show Meta plans to use AI to automate up to 90% of its privacy and integrity risk assessments, including in sensitive areas like violent content (NPR)
https://www.npr.org/2025/05/31/nx-s1-5407870/meta-ai-facebook-instagram-risks…

And on integrity and swamps:
https://bsky.app/profile/corybooker.com/post/3lqnryx2syk2f

And on integrity and swamps:
https://bsky.app/profile/corybooker.com/post/3lqnryx2syk2f

#npr is a victim of the #trump administration
If you value independent journalism, support them pls🙏🏼
Origineel bericht: https://

Q&A with Lesley Stahl on the pressures at CBS News and 60 Minutes, Trump's lawsuit and likely settlement, Shari Redstone, Bill Owens stepping down, and more (David Remnick/New Yorker)
https://www.newyorker.com/podcas…

Trump’s Playbook to Cripple “60 Minutes” and the Press
On The New Yorker Radio Hour, the “60 Minutes” correspondent reflects on the loss of journalistic integrity that a settlement of the President’s twenty-billion-dollar lawsuit would likely entail.

This https://arxiv.org/abs/2505.15173 has been replaced.
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AvatarShield: Visual Reinforcement Learning for Human-Centric Video Forgery Detection
The rapid advancement of Artificial Intelligence Generated Content (AIGC) technologies, particularly in video generation, has led to unprecedented creative capabilities but also increased threats to information integrity, identity security, and public trust. Existing detection methods, while effective in general scenarios, lack robust solutions for human-centric videos, which pose greater risks due to their realism and potential for legal and ethical misuse. Moreover, current detection approach…

This https://arxiv.org/abs/2502.05221 has been replaced.
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Blackout DIFUSCO
This study explores the integration of Blackout Diffusion into the DIFUSCO framework for combinatorial optimization, specifically targeting the Traveling Salesman Problem (TSP). Inspired by the success of discrete-time diffusion models (D3PM) in maintaining structural integrity, we extend the paradigm to a continuous-time framework, leveraging the unique properties of Blackout Diffusion. Continuous-time modeling introduces smoother transitions and refined control, hypothesizing enhanced solutio…

This https://arxiv.org/abs/2503.18236 has been replaced.
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Research impact evaluation based on effective authorship contribution sensitivity: h-leadership index
The evaluation of a researcher's performance has traditionally relied on various bibliometric measures, with the h-index being one of the most prominent. However, the h-index only accounts for the number of citations received in a publication and does not account for other factors such as the number of authors or their specific contributions in collaborative works. Therefore, the h-index has been placed on scrutiny as it has motivated academic integrity issues where non-contributing authors get…

Evaluating the Contextual Integrity of False Positives in Algorithmic Travel Surveillance
Alina Wernick, Alan Medlar, Sofia S\"oderholm, Dorota G{\l}owacka
https://arxiv.org/abs/2506.00218

Evaluating the Contextual Integrity of False Positives in Algorithmic Travel Surveillance
International air travel is highly surveilled. While surveillance is deemed necessary for law enforcement to prevent and detect terrorism and other serious crimes, even the most accurate algorithmic mass surveillance systems produce high numbers of false positives. Despite the potential impact of false positives on the fundamental rights of millions of passengers, algorithmic travel surveillance is lawful in the EU. However, as the system's processing practices and accuracy are kept secret by l…

In the digital age, misinformation spreads rapidly, making it increasingly difficult to ensure the integrity of information. AI presents new opportunities to support fact-checking and news classification. Join Giovanna Monti and Lucian Precup as they share insights from their work developing an AI-driven platform integrating search capabilities, an intelligent assistant and a RAG system.
Learn more:

SIL Allocation for Mitigation Safety Functions
Hamid Jahanian
https://arxiv.org/abs/2506.02309 https://arxiv.org/pdf/2506.02309

SIL Allocation for Mitigation Safety Functions
SIL (Safety Integrity Level) allocation plays a pivotal role in evaluating the significance of Safety Functions (SFs) within high-risk industries. The outcomes of a SIL allocation study determine the design specifications necessary to uphold the Probability of Failure on Demand (PFD) below permissible limits, thus managing risk effectively. While extensive research has focused on SIL allocation for preventive SFs, there is a noticeable gap in attention towards mitigation SFs. To address this ga…

Texas GOP lawmakers introduce bills to display Ten Commandments, read Bible in schools
Considering that these texts constitute the foundational elements of all religions derived from Judaism, should they not be displayed in their original Hebrew to preserve their authenticity and integrity? https://ground.news/article/texas-gop-lawmakers-introduce-bills-to-display-ten-commandments-read-bible-in-schools_e0334e

Well, at least it is a different result! #UbuntuStudio shouldn't be so hard. None of the USB write methods complain about my media, but shouldn't the start-disk writer offer SOME sort of integrity check?

This https://arxiv.org/abs/2503.00600 has been replaced.
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Semantic Integrity Constraints: Declarative Guardrails for AI-Augmented Data Processing Systems
AI-augmented data processing systems (DPSs) integrate large language models (LLMs) into query pipelines, allowing powerful semantic operations on structured and unstructured data. However, the reliability (a.k.a. trust) of these systems is fundamentally challenged by the potential for LLMs to produce errors, limiting their adoption in critical domains. To help address this reliability bottleneck, we introduce semantic integrity constraints (SICs) -- a declarative abstraction for specifying and …

Graph Contrastive Learning for Optimizing Sparse Data in Recommender Systems with LightGCL
Aravinda Jatavallabha, Prabhanjan Bharadwaj, Ashish Chander
https://arxiv.org/abs/2506.00048

Graph Contrastive Learning for Optimizing Sparse Data in Recommender Systems with LightGCL
Graph Neural Networks (GNNs) are powerful tools for recommendation systems, but they often struggle under data sparsity and noise. To address these issues, we implemented LightGCL, a graph contrastive learning model that uses Singular Value Decomposition (SVD) for robust graph augmentation, preserving semantic integrity without relying on stochastic or heuristic perturbations. LightGCL enables structural refinement and captures global collaborative signals, achieving significant gains over stat…

The Guide to #Hashing I Wish I Had When I Started
https://banjocode.com/post/cs/hashing

This https://arxiv.org/abs/2503.00271 has been replaced.
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Why Johnny Signs with Next-Generation Tools: A Usability Case Study of Sigstore
Software signing is the most robust method for ensuring the integrity and authenticity of components in a software supply chain. However, traditional signing tools place key management and signer identification burdens on practitioners, leading to both security vulnerabilities and usability challenges. Next-generation signing tools such as Sigstore have automated some of these concerns, but little is known about their usability and adoption dynamics. This knowledge gap hampers the integration o…

This https://arxiv.org/abs/2405.00295 has been replaced.
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Proof of Sampling: A Nash Equilibrium-Based Verification Protocol for Decentralized Systems
This paper introduces the Proof of Sampling (PoSP) protocol, a Nash Equilibrium-based verification mechanism, and its application to decentralized machine learning inference through spML. Our protocol has a pure strategy Nash Equilibrium, compelling rational participants to act honestly. It economically disincentivizes dishonest behavior, making it costly for participants to compromise the network's integrity. In our spML protocol, we apply PoSP to decentralized inference for AI applications vi…

TIL that the family coat of arms used as a logo by Donald Trump is just some *other* family's arms.
> The Trump Organization made only one change: replacing the word "Integrity" with the word "Trump"
https://www.bbc.co.uk/news/world-us-canada-40097665

Right to bear arms? Trump accused of plagiarising family crest
Donald Trump has been criticised for using another man's coat of arms, but what are the rules?

Contextualized Automatic Speech Recognition with Dynamic Vocabulary Prediction and Activation
Zhennan Lin, Kaixun Huang, Wei Ren, Linju Yang, Lei Xie
https://arxiv.org/abs/2505.23077

Contextualized Automatic Speech Recognition with Dynamic Vocabulary Prediction and Activation
Deep biasing improves automatic speech recognition (ASR) performance by incorporating contextual phrases. However, most existing methods enhance subwords in a contextual phrase as independent units, potentially compromising contextual phrase integrity, leading to accuracy reduction. In this paper, we propose an encoder-based phrase-level contextualized ASR method that leverages dynamic vocabulary prediction and activation. We introduce architectural optimizations and integrate a bias loss to ex…

Where's the Line? A Classroom Activity on Ethical and Constructive Use of Generative AI in Physics
Zosia Krusberg
https://arxiv.org/abs/2506.00229 http…

Where's the Line? A Classroom Activity on Ethical and Constructive Use of Generative AI in Physics
Generative AI tools like ChatGPT are rapidly reshaping how students and instructors engage with course material-and how they think about academic integrity. This paper presents a classroom activity designed to help physics students critically examine the ethical and educational implications of using AI in coursework. Through a structured sequence of case analysis, discussion, and optional policy drafting, students develop the metacognitive, ethical, and collaborative skills needed to navigate e…

A highly sensitive SF$_6$-based leak test system for JUNO 3-inch PMT underwater electronics boxes
Ziliang Chu, Diru Wu, Miao He, Jilei Xu, Xiaoping Jing, Jian Wang
https://arxiv.org/abs/2505.24142

A highly sensitive SF$_6$-based leak test system for JUNO 3-inch PMT underwater electronics boxes
A total of 25600 3-inch photomultiplier tubes (PMTs), along with their corresponding frontend electronics, have been installed at the Jiangmen Underground Neutrino Observatory (JUNO). These electronics are housed in 200 stainless steel boxes that operate underwater. To verify the sealing integrity of the underwater boxes following integration, we developed an SF$_6$-based leak test system, opting against the typical helium-based system due to helium's ability to penetrate the PMT glass. After a…

Ramachandra Guha: Ignored by the ‘national’ media, a disaster is unfolding in Great Nicobar
https://scroll.in/article/1081027/ramachandra-guha-ignored-by-the-national-media-a-disaster-is-unfolding-in-great-n…

PoCGen: Generating Proof-of-Concept Exploits for Vulnerabilities in Npm Packages
Deniz Simsek, Aryaz Eghbali, Michael Pradel
https://arxiv.org/abs/2506.04962

PoCGen: Generating Proof-of-Concept Exploits for Vulnerabilities in Npm Packages
Security vulnerabilities in software packages are a significant concern for developers and users alike. Patching these vulnerabilities in a timely manner is crucial to restoring the integrity and security of software systems. However, previous work has shown that vulnerability reports often lack proof-of-concept (PoC) exploits, which are essential for fixing the vulnerability, testing patches, and avoiding regressions. Creating a PoC exploit is challenging because vulnerability reports are info…

This https://arxiv.org/abs/2506.03507 has been replaced.
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Software Bill of Materials in Software Supply Chain Security A Systematic Literature Review
Software Bill of Materials (SBOMs) are increasingly regarded as essential tools for securing software supply chains (SSCs), yet their real-world use and adoption barriers remain poorly understood. This systematic literature review synthesizes evidence from 40 peer-reviewed studies to evaluate how SBOMs are currently used to bolster SSC security. We identify five primary application areas: vulnerability management, transparency, component assessment, risk assessment, and SSC integrity. Despite c…

Generative AI for Multiple Choice STEM Assessments
Christina Perdikoulias, Chad Vance, Stephen M. Watt
https://arxiv.org/abs/2506.02094 https://

Generative AI for Multiple Choice STEM Assessments
Artificial intelligence technology enables a range of enhancements in computer-aided instruction, from accelerating the creation of teaching materials to customizing learning paths based on learner outcomes. However, ensuring the mathematical accuracy and semantic integrity of generative AI output remains a significant challenge, particularly in STEM disciplines. In this study, we explore the use of generative AI in which "hallucinations" -- typically viewed as undesirable inaccuracies -- can i…

This https://arxiv.org/abs/2504.16571 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

LaSDVS : A Post-Quantum Secure Compact Strong-Designated Verifier Signature
Digital signatures are fundamental cryptographic primitives that ensure the authenticity and integrity of digital communication. However, in scenarios involving sensitive interactions -- such as e-voting or e-cash -- there is a growing need for more controlled signing mechanisms. Strong-Designated Verifier Signature (SDVS) offers such control by allowing the signer to specify and restrict the verifier of a signature. The existing state-of-the-art SDVS are mostly based on number-theoretic hardne…

Software Bill of Materials in Software Supply Chain Security A Systematic Literature Review
Eric O'Donoghue, Yvette Hastings, Ernesto Ortiz, A. Redempta Manzi Muneza
https://arxiv.org/abs/2506.03507

Software Bill of Materials in Software Supply Chain Security A Systematic Literature Review
Software Bill of Materials (SBOMs) are increasingly regarded as essential tools for securing software supply chains (SSCs), yet their real-world use and adoption barriers remain poorly understood. This systematic literature review synthesizes evidence from 40 peer-reviewed studies to evaluate how SBOMs are currently used to bolster SSC security. We identify five primary application areas: vulnerability management, transparency, component assessment, risk assessment, and SSC integrity. Despite c…

SIFBench: An Extensive Benchmark for Fatigue Analysis
Tushar Gautam, Robert M. Kirby, Jacob Hochhalter, Shandian Zhe
https://arxiv.org/abs/2506.01173 https…

SIFBench: An Extensive Benchmark for Fatigue Analysis
Fatigue-induced crack growth is a leading cause of structural failure across critical industries such as aerospace, civil engineering, automotive, and energy. Accurate prediction of stress intensity factors (SIFs) -- the key parameters governing crack propagation in linear elastic fracture mechanics -- is essential for assessing fatigue life and ensuring structural integrity. While machine learning (ML) has shown great promise in SIF prediction, its advancement has been severely limited by the …

This https://arxiv.org/abs/2505.02198 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCY_…

Student Perspectives on the Benefits and Risks of AI in Education
The use of chatbots equipped with artificial intelligence (AI) in educational settings has increased in recent years, showing potential to support teaching and learning. However, the adoption of these technologies has raised concerns about their impact on academic integrity, students' ability to problem-solve independently, and potential underlying biases. To better understand students' perspectives and experiences with these tools, a survey was conducted at a large public university in the Uni…

Ten Simple Rules for Catalyzing Collaborations and Building Bridges between Research Software Engineers and Software Engineering Researchers
Nasir U. Eisty, Jeffrey C. Carver, Johanna Cohoon, Ian A. Cosden, Carole Goble, Samuel Grayson
https://arxiv.org/abs/2506.03012

Ten Simple Rules for Catalyzing Collaborations and Building Bridges between Research Software Engineers and Software Engineering Researchers
In the evolving landscape of scientific and scholarly research, effective collaboration between Research Software Engineers (RSEs) and Software Engineering Researchers (SERs) is pivotal for advancing innovation and ensuring the integrity of computational methodologies. This paper presents ten strategic guidelines aimed at fostering productive partnerships between these two distinct yet complementary communities. The guidelines emphasize the importance of recognizing and respecting the cultural …

Decentralized COVID-19 Health System Leveraging Blockchain
Lingsheng Chen, Shipeng Ye, Xiaoqi Li
https://arxiv.org/abs/2506.02674 https://

Decentralized COVID-19 Health System Leveraging Blockchain
With the development of the Internet, the amount of data generated by the medical industry each year has grown exponentially. The Electronic Health Record (EHR) manages the electronic data generated during the user's treatment process. Typically, an EHR data manager belongs to a medical institution. This traditional centralized data management model has many unreasonable or inconvenient aspects, such as difficulties in data sharing, and it is hard to verify the authenticity and integrity of the…

Generative Knowledge Production Pipeline Driven by Academic Influencers
Katalin Feher, Marton Demeter
https://arxiv.org/abs/2505.24681 https://

Generative Knowledge Production Pipeline Driven by Academic Influencers
Generative AI transforms knowledge production, validation, and dissemination, raising academic integrity and credibility concerns. This study examines 53 academic influencer videos that reached 5.3 million viewers to identify an emerging, structured, implementation-ready pipeline balancing originality, ethical compliance, and human-AI collaboration despite the disruptive impacts. Findings highlight generative AI's potential to automate publication workflows and democratize participation in know…

This https://arxiv.org/abs/2405.17492 has been replaced.
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StatWhy: Formal Verification Tool for Statistical Hypothesis Testing Programs
Statistical methods have been widely misused and misinterpreted in various scientific fields, raising significant concerns about the integrity of scientific research. To mitigate this problem, we propose a tool-assisted method for formally specifying and automatically verifying the correctness of statistical programs. In this method, programmers are required to annotate the source code of the statistical programs with the requirements for these methods. Through this annotation, they are reminde…

This https://arxiv.org/abs/2505.23821 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

SpeechVerifier: Robust Acoustic Fingerprint against Tampering Attacks via Watermarking
With the surge of social media, maliciously tampered public speeches, especially those from influential figures, have seriously affected social stability and public trust. Existing speech tampering detection methods remain insufficient: they either rely on external reference data or fail to be both sensitive to attacks and robust to benign operations, such as compression and resampling. To tackle these challenges, we introduce SpeechVerifer to proactively verify speech integrity using only the …

This https://arxiv.org/abs/2505.06448 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDL_…

Gaming the Metrics? Bibliometric Anomalies and the Integrity Crisis in Global University Rankings
Global university rankings have transformed how certain institutions define success, often elevating metrics over meaning. This study examines universities with rapid research growth suggestive of metric-driven behaviors. Among the 1,000 most publishing institutions, 98 showed extreme output increases between 2018-2019 and 2023-2024. Of these, eighteen were selected for exhibiting sharp declines in first and corresponding authorship. Compared to national, regional, and international norms, thes…

This https://arxiv.org/abs/2411.16746 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

LoBAM: LoRA-Based Backdoor Attack on Model Merging
Model merging is an emerging technique that integrates multiple models fine-tuned on different tasks to create a versatile model that excels in multiple domains. This scheme, in the meantime, may open up backdoor attack opportunities where one single malicious model can jeopardize the integrity of the merged model. Existing works try to demonstrate the risk of such attacks by assuming substantial computational resources, focusing on cases where the attacker can fully fine-tune the pre-trained m…

SpeechVerifier: Robust Acoustic Fingerprint against Tampering Attacks via Watermarking
Lingfeng Yao (University of Houston), Chenpei Huang (University of Houston), Shengyao Wang (Waseda University), Junpei Xue (Waseda University), Hanqing Guo (University of Hawaii at M\=anoa), Jiang Liu (Waseda University), Xun Chen (Independent Researcher), Miao Pan (University of Houston)

SpeechVerifier: Robust Acoustic Fingerprint against Tampering Attacks via Watermarking
With the surge of social media, maliciously tampered public speeches, especially those from influential figures, have seriously affected social stability and public trust. Existing speech tampering detection methods remain insufficient: they either rely on external reference data or fail to be both sensitive to attacks and robust to benign operations, such as compression and resampling. To tackle these challenges, we introduce SpeechVerifer to proactively verify speech integrity using only the …