Session 10A: Confidential Computing 2

Authors, Creators & Presenters: Qihang Zhou (Institute of Information Engineering, Chinese Academy of Sciences), Wenzhuo Cao (Institute of Information Engineering, Chinese Academy of Sciences; School of Cyberspace Security, University of Chinese Academy of Sciences), Xiaoqi Jia (Institute of Information Engineering, Chinese Academy of Sciences), Peng Liu (The Pennsylvania State University, USA), Shengzhi Zhang (Department of Computer Science, Metropolitan College, Boston University, USA), Jiayun Chen (Institute of Information Engineering, Chinese Academy of Sciences; School of Cyberspace Security, University of Chinese Academy of Sciences), Shaowen Xu (Institute of Information Engineering, Chinese Academy of Sciences; School of Cyberspace Security, University of Chinese Academy of Sciences), Zhenyu Song (Institute of Information Engineering, Chinese Academy of Science)

PAPER
RContainer: A Secure Container Architecture through Extending ARM CCA Hardware Primitives

Containers have become widely adopted in cloud platforms due to their efficient deployment and high resource utilization. However, their weak isolation has always posed a significant security concern. In this paper, we propose RContainer, a novel secure container architecture that protects containers from untrusted operating systems and enforces strong isolation among containers by extending ARM Confidential Computing Architecture (CCA) hardware primitives. RContainer introduces a small, trusted mini-OS that runs alongside the deprivileged OS, responsible for monitoring the control flow between the operating system and containers. Additionally, RContainer uses shim-style isolation, creating an isolated physical address space called con-shim for each container at the kernel layer through the Granule Protection Check mechanism. We have implemented RContainer on ARMv9-A Fixed Virtual Platform and ARMv8 hardware SoC for security analysis and performance evaluation. Experimental results demonstrate that RContainer can significantly enhance container security with a modest performance overhead and a minimal Trusted Computing Base (TCB).

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.

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Session 10A: Confidential Computing 2

Authors, Creators & Presenters: Byeongwook Kim (Seoul National University), Jaewon Hur (Seoul National University), Adil Ahmad (Arizona State University), Byoungyoung Lee (Seoul National University)

PAPER
Secure Data Analytics in Apache Spark with Fine-grained Policy Enforcement and Isolated Execution

Cloud based Spark platform is a tempting approach for sharing data, as it allows data users to easily analyze the data while the owners to efficiently share the large volume of data. However, the absence of a robust policy enforcement mechanism on Spark hinders the data owners from sharing their data due to the risk of private data breach. In this respect, we found that malicious data users and cloud managers can easily leak the data by constructing a policy violating physical plan, compromising the Spark libraries, or even compromising the Spark cluster itself. Nonetheless, current approaches fail to securely and generally enforce the policies on Spark, as they do not check the policies on physical plan level, and they do not protect the integrity of data analysis pipeline. This paper presents Laputa, a secure policy enforcement framework on Spark. Specifically, Laputa designs a pattern matching based policy checking on the physical plans, which is generally applicable to Spark applications with more fine-grained policies. Then, Laputa compartmentalizes Spark applications based on confidential computing, by which the entire data analysis pipeline is protected from the malicious data users and cloud managers. Meanwhile, Laputa preserves the usability as the data users can run their Spark applications on Laputa with minimal modification. We implemented Laputa, and evaluated its security and performance aspects on TPC-H, Big Data benchmarks, and real world applications using ML models. The evaluation results demonstrated that Laputa correctly blocks malicious Spark applications while imposing moderate performance overheads.

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.

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Hiring the right minds and skill sets in marketing in today’s age is vital to laying the right foundations for any company, let alone a crypto company.

Session 10A: Confidential Computing 2

Authors, Creators & Presenters: Weili Wang (Southern University of Science and Technology), Honghan Ji (ByteDance Inc.), Peixuan He (ByteDance Inc.), Yao Zhang (ByteDance Inc.), Ye Wu (ByteDance Inc.), Yinqian Zhang (Southern University of Science and Technology)

PAPER
WAVEN: WebAssembly Memory Virtualization for Enclaves

The advancement of trusted execution environments (TEEs) has enabled the confidential computing paradigm and created new application scenarios for WebAssembly (Wasm). "Wasm+TEE" designs achieve in-enclave multi-tenancy with strong isolation, facilitating concurrent execution of untrusted code instances from multiple users. However, the linear memory model of Wasm lacks efficient cross-module data sharing and fine-grained memory access control, significantly restricting its applications in certain confidential computing scenarios where secure data sharing is essential (e.g., confidential stateful FaaS and data marketplaces). In this paper, we propose WAVEN (WebAssembly Memory Virtualization for ENclaves), a novel WebAssembly memory virtualization scheme, to enable memory sharing among Wasm modules and page-level access control. We implement WAVEN atop WAMR, a popular Wasm runtime for TEEs, and empirically demonstrate its efficiency and effectiveness. To the best of our knowledge, our work represents the first approach that enables cross-module memory sharing with fine-grained memory access control in Wasm.

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.

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Session 9D: Github + OSN Security

Authors, Creators & Presenters: Jan-Ulrich Holtgrave (CISPA Helmholtz Center for Information Security), Kay Friedrich (CISPA Helmholtz Center for Information Security), Fabian Fischer (CISPA Helmholtz Center for Information Security), Nicolas Huaman (Leibniz University Hannover), Niklas Busch (CISPA Helmholtz Center for Information Security), Jan H. Klemmer (CISPA Helmholtz Center for Information Security), Marcel Fourné (Paderborn University), Oliver Wiese (CISPA Helmholtz Center for Information Security), Dominik Wermke (North Carolina State University), Sascha Fahl (CISPA Helmholtz Center for Information Security)

PAPER
Attributing Open-Source Contributions is Critical but Difficult: A Systematic Analysis of GitHub Practices and Their Impact on Software Supply Chain Security

Critical open-source projects form the basis of many large software systems. They provide trusted and extensible implementations of important functionality for cryptography, compatibility, and security. Verifying commit authorship authenticity in open-source projects is essential and challenging. Git users can freely configure author details such as names and email addresses. Platforms like GitHub use such information to generate profile links to user accounts. We demonstrate three attack scenarios malicious actors can use to manipulate projects and profiles on GitHub to appear trustworthy. We designed a mixed-research study to assess the effect on critical open-source software projects and evaluated countermeasures. First, we conducted a large-scale measurement among 50,328 critical open-source projects on GitHub and demonstrated that contribution workflows can be abused in 85.9% of the projects. We identified 573,043 email addresses that a malicious actor can claim to hijack historic contributions and improve the trustworthiness of their accounts. When looking at commit signing as a countermeasure, we found that the majority of users (95.4%) never signed a commit, and for the majority of projects (72.1%), no commit was ever signed. In contrast, only 2.0% of the users signed all their commits, and for 0.2% of the projects all commits were signed. Commit signing is not associated with projects' programming languages, topics, or other security measures. Second, we analyzed online security advice to explore the awareness of contributor spoofing and identify recommended countermeasures. Most documents exhibit awareness of the simple spoofing technique via Git commits but no awareness of problems with GitHub's handling of email addresses.

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.

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An anonymous reader quotes a report from Ars Technica: It's no secret that students worldwide use AI chatbots to do their homework and avoid learning things. On the flip side, students can also use AI as a tool to beef up their knowledge and plan for the future with flashcards or study guides. Google hopes its latest Gemini feature will help with the latter. The company has announced that Gemini can now create free SAT practice tests and coach students to help them get higher scores. As a standardized test, the content of the SAT follows a predictable pattern. So there's no need to use a lengthy, personalized prompt to get Gemini going. Just say something like, "I want to take a practice SAT test," and the chatbot will generate one complete with clickable buttons, graphs, and score analysis. Of course, generative AI can go off the rails and provide incorrect information, which is a problem when you're trying to learn things. However, Google says it has worked with education firms like The Princeton Review to ensure the AI-generated tests resemble what students will see in the real deal. The interface for Gemini's practice tests includes scoring and the ability to review previous answers. If you are unclear on why a particular answer is right or wrong, the questions have an "Explain answer" button right at the bottom. After you finish the practice exam, the custom interface (which looks a bit like Gemini's Canvas coding tool) can help you follow up on areas that need improvement. Google says support for the SAT is just the start, "with more tests coming in the future."

Read more of this story at Slashdot.

It's no secret that students worldwide use AI chatbots to do their homework and avoid learning things. On the flip side, students can also use AI as a tool to beef up their knowledge and plan for the future with flashcards or study guides. Google hopes its latest Gemini feature will help with the latter. The company has announced that Gemini can now create free SAT practice tests and coach students to help them get higher scores.

As a standardized test, the content of the SAT follows a predictable pattern. So there's no need to use a lengthy, personalized prompt to get Gemini going. Just say something like, "I want to take a practice SAT test," and the chatbot will generate one complete with clickable buttons, graphs, and score analysis.

Of course, generative AI can go off the rails and provide incorrect information, which is a problem when you're trying to learn things. However, Google says it has worked with education firms like The Princeton Review to ensure the AI-generated tests resemble what students will see in the real deal.

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Session 9D: Github + OSN Security

Authors, Creators & Presenters: Aditya Sirish A Yelgundhalli (New York University), Patrick Zielinski (New York University), Reza Curtmola (New Jersey Institute of Technology), Justin Cappos (New York University)

PAPER
Rethinking Trust In Forge-Based Git Security

Git is the most popular version control system today, with Git forges such as GitHub, GitLab, and Bitbucket used to add functionality. Significantly, these forges are used to enforce security controls. However, due to the lack of an open protocol for ensuring a repository's integrity, forges cannot prove themselves to be trustworthy, and have to carry the responsibility of being non-verifiable trusted third parties in modern software supply chains. In this paper, we present gittuf, a system that decentralizes Git security and enables every user to contribute to collectively enforcing the repository's security. First, gittuf enables distributing of policy declaration and management responsibilities among more parties such that no single user is trusted entirely or unilaterally. Second, gittuf decentralizes the tracking of repository activity, ensuring that a single entity cannot manipulate repository events. Third, gittuf decentralizes policy enforcement by enabling all developers to independently verify the policy, eliminating the single point of trust placed in the forge as the only arbiter for whether a change in the repository is authorized. Thus, gittuf can provide strong security guarantees in the event of a compromise of the centralized forge, the underlying infrastructure, or a subset of privileged developers trusted to set policy. gittuf also implements policy features that can protect against unauthorized changes to branches and tags i.e., pushes as well as files/folders i.e., commits. Our analysis of gittuf shows that its properties and policy features provide protections against previously seen version control system attacks. In addition, our evaluation of gittuf shows it is viable even for large repositories with a high volume of activity such as those of Git and Kubernetes (less than 4% storage overhead and under 0.59s of time to verify each push).

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.

Permalink

The post NDSS 2025 – Rethinking Trust In Forge-Based Git Security appeared first on Security Boulevard.

Session 9D: Github + OSN Security

Authors, Creators & Presenters: Aditya Sirish A Yelgundhalli (New York University), Patrick Zielinski (New York University), Reza Curtmola (New Jersey Institute of Technology), Justin Cappos (New York University)

PAPER
Rethinking Trust In Forge-Based Git Security

Git is the most popular version control system today, with Git forges such as GitHub, GitLab, and Bitbucket used to add functionality. Significantly, these forges are used to enforce security controls. However, due to the lack of an open protocol for ensuring a repository's integrity, forges cannot prove themselves to be trustworthy, and have to carry the responsibility of being non-verifiable trusted third parties in modern software supply chains. In this paper, we present gittuf, a system that decentralizes Git security and enables every user to contribute to collectively enforcing the repository's security. First, gittuf enables distributing of policy declaration and management responsibilities among more parties such that no single user is trusted entirely or unilaterally. Second, gittuf decentralizes the tracking of repository activity, ensuring that a single entity cannot manipulate repository events. Third, gittuf decentralizes policy enforcement by enabling all developers to independently verify the policy, eliminating the single point of trust placed in the forge as the only arbiter for whether a change in the repository is authorized. Thus, gittuf can provide strong security guarantees in the event of a compromise of the centralized forge, the underlying infrastructure, or a subset of privileged developers trusted to set policy. gittuf also implements policy features that can protect against unauthorized changes to branches and tags i.e., pushes as well as files/folders i.e., commits. Our analysis of gittuf shows that its properties and policy features provide protections against previously seen version control system attacks. In addition, our evaluation of gittuf shows it is viable even for large repositories with a high volume of activity such as those of Git and Kubernetes (less than 4% storage overhead and under 0.59s of time to verify each push).

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.

Permalink

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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.

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.

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Seattle-based Code.org laid off 18 employees, or about 14% of its staff, the nonprofit confirmed to GeekWire on Wednesday.

Following the cuts, Code.org’s staff now numbers 107. 

“Code.org has made the difficult decision to part ways with 18 colleagues as part of efforts to ensure our long-term sustainability,” the organization said in an emailed statement. “Their contributions helped millions of educators and students around the world, and we are grateful for their efforts.”

Code.org was launched in 2013 by brothers Hadi and Ali Partovi with a mission to expand computer science education to K-12 students. Backed by nearly $60 million in funding from the likes of Microsoft, Amazon, Google and others, Code.org counts 102 million students and 3 million teachers on its platform today, with 232 million projects created by students around the world.

CEO Hadi Partovi is a former Microsoft manager and was an early investor in companies including Facebook, DropBox, Airbnb and Uber.

“Our mission remains unchanged,” the organization said in its statement. “We will continue our Hour of AI campaign, along with our work to reform policies and new curriculum supporting CS+AI education in classrooms.”

Previously:

• ‘We are all kids in the age of AI’: Trevor Noah teaches 5th graders — and learns a few things himself
• Code.org CEO rips NY Times for stoking ‘populist fears’ over computer science jobs and AI

Authors, Creators & Presenters: Zhuo Chen (Zhejiang University), Yufeng Hu (Zhejiang University), Bowen He (Zhejiang University), Dong Luo (Zhejiang University), Lei Wu (Zhejiang University), Yajin Zhou (Zhejiang University)

PAPER
Dissecting Payload-Based Transaction Phishing On Ethereum

In recent years, a more advanced form of phishing has arisen on Ethereum, surpassing early-stage, simple transaction phishing. This new form, which we refer to as payload-based transaction phishing (PTXPHISH), manipulates smart contract interactions through the execution of malicious payloads to deceive users. PTXPHISH has rapidly emerged as a significant threat, leading to incidents that caused losses exceeding $70 million in 2023 reports. Despite its substantial impact, no previous studies have systematically explored PTXPHISH. In this paper, we present the first comprehensive study of the PTXPHISH on Ethereum. Firstly, we conduct a long-term data collection and put considerable effort into establishing the first ground-truth PTXPHISH dataset, consisting of 5,000 phishing transactions. Based on the dataset, we dissect PTXPHISH, categorizing phishing tactics into four primary categories and eleven sub-categories. Secondly, we propose a rule-based multi-dimensional detection approach to identify PTXPHISH, achieving an F1-score of over 99% and processing each block in an average of 390 ms. Finally, we conduct a large-scale detection spanning 300 days and discover a total of 130,637 phishing transactions on Ethereum, resulting in losses exceeding $341.9 million. Our in-depth analysis of these phishing transactions yielded valuable and insightful findings. Scammers consume approximately 13.4 ETH daily, which accounts for 12.5% of the total Ethereum gas, to propagate address poisoning scams. Additionally, our analysis reveals patterns in the cash-out process employed by phishing scammers, and we find that the top five phishing organizations are responsible for 40.7% of all losses. Furthermore, our work has made significant contributions to mitigating real-world threats. We have reported 1,726 phishing addresses to the community, accounting for 42.7% of total community contributions during the same period. Additionally, we have sent 2,539 on-chain alert messages, assisting 1,980 victims. This research serves as a valuable reference in combating the emerging PTXPHISH and safeguarding users' assets.

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.

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Session 9C: Phishing & Fraud 2

Authors, Creators & Presenters: Boladji Vinny Adjibi (Georgia Tech), Athanasios Avgetidis (Georgia Tech), Manos Antonakakis (Georgia Tech), Michael Bailey (Georgia Tech), Fabian Monrose (Georgia Tech)

PAPER
The Guardians of Name Street: Studying the Defensive Registration Practices of the Fortune 500

Using orthographic, phonetic, and semantic models, we study the prevalence of defensive registrations related to a wide spectrum of transformations of the base domain names of Fortune 500 companies. As part of a large-scale evaluation, we explore several questions aimed at (a) understanding whether there are explainable factors (e.g., the size of the company's security team or its domain name's popularity rank) that correlate with a company's level of engagement regarding defensive registrations; (b) identifying the main actors in the defensive registration ecosystem that Fortune 500 companies rely upon; (c) uncovering the strategies used by these actors, and d) assessing the efficacy of those strategies from the perspective of queries emanating from a large Internet Service Provider (ISP). Overall, we identified 19,523 domain names defensively registered by 447 Fortune 500 companies. These companies engage in defensive registrations sparingly, with almost 200 companies having fewer than ten defensive registrations. By analyzing the registrations, we found many similarities between the types of domain names the companies registered. For instance, they all registered many TLD-squatting domain names. As it turns out, those similarities are due to the companies' reliance on online brand protection (OBP) service providers to protect their brands. Our analysis of the efficacy of the strategies of those OBPs showed that they register domain names that receive most of the potential squatting traffic. Using regression models, we learned from those strategies to provide recommendations for future defensive registrants. Our measurement also revealed many domain names that received high proportions of traffic over long periods of time and could be registered for only 15 USD. To prevent the abusive use of such domain names, we recommend that OBP providers proactively leverage passive DNS data to identify and preemptively register highly queried available domain names.

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.

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World Liberty Forum to debut at Mar-a-Lago, featuring finance leaders from Goldman Sachs, Franklin Templeton, and FIFA.

The post World Liberty Financial to host inaugural forum at Mar-a-Lago with Goldman Sachs and Franklin Templeton CEOs appeared first on Crypto Briefing.

Pioneering mathematician Dr. Gladys West has passed away at the age of 95. Her name may not be familiar to you, but her contributions certainly are; West's work laid the foundation for the global positioning system. As you likely know from experience, GPS is now an essential component of industries ranging from aviation and emergency response, as well as ensuring that you get to that dinner date or job interview on time. 

West was born in 1930 in Virginia. Despite the oppression of Jim Crow laws in the south, she was able to pursue higher education at Virginia State College (now named Virginia State University), obtaining bachelor's and master's degrees in mathematics. In 1956, West was hired at what is now called the Naval Surface Warfare Center in Dahlgren, VA. Her focus during the 1970s and 1980s was creating accurate models of the Earth's shape based on satellite data, a complex task requiring the type of mathematical gymnastics that would make the average person dizzy. Those models later became the backbone for GPS. West worked at the Dahlgren center for 42 years, retiring in 1998. 

As has been the case with so many of the women, particularly those of color, behind tech and science breakthroughs in the US, West's work went largely uncelebrated for decades. After submitting a short biography of her accomplishments to a sorority function in 2018, members of Alpha Kappa Alpha helped West to receive belated recognition for her contributions. She was inducted into the US Air Force Space and Missiles Pioneers Hall of Fame and honored as Female Alumna of the Year by the Historically Black Colleges and Universities Awards in that same year. The Guardian published an interview with West in 2020 that shared some insights on her journey, including a note that when West was out and about, she favored paper maps over the technology she indirectly helped create.

This article originally appeared on Engadget at https://www.engadget.com/science/dr-gladys-west-whose-mathematical-models-inspired-gps-dies-at-95-234605023.html?src=rss

©

Session 9B: DNN Attack Surfaces

Authors, Creators & Presenters: Myungsuk Moon (Yonsei University), Minhee Kim (Yonsei University), Joonkyo Jung (Yonsei University), Dokyung Song (Yonsei University)

PAPER
ASGARD: Protecting On-Device Deep Neural Networks with Virtualization-Based Trusted Execution Environments

On-device deep learning, increasingly popular for enhancing user privacy, now poses a serious risk to the privacy of deep neural network (DNN) models. Researchers have proposed to leverage Arm TrustZone's trusted execution environment (TEE) to protect models from attacks originating in the rich execution environment (REE). Existing solutions, however, fall short: (i) those that fully contain DNN inference within a TEE either support inference on CPUs only, or require substantial modifications to closed-source proprietary software for incorporating accelerators; (ii) those that offload part of DNN inference to the REE either leave a portion of DNNs unprotected, or incur large run-time overheads due to frequent model (de)obfuscation and TEE-to-REE exits. We present ASGARD, the first virtualization-based TEE solution designed to protect on-device DNNs on legacy Armv8-A SoCs. Unlike prior work that uses TrustZone-based TEEs for model protection, ASGARD's TEEs remain compatible with existing proprietary software, maintain the trusted computing base (TCB) minimal, and incur near-zero run-time overhead. To this end, ASGARD (i) securely extends the boundaries of an existing TEE to incorporate an SoC-integrated accelerator via secure I/O passthrough, (ii) tightly controls the size of the TCB via our aggressive yet security-preserving platform- and application-level TCB debloating techniques, and (iii) mitigates the number of costly TEE-to-REE exits via our exit-coalescing DNN execution planning. We implemented ASGARD on RK3588S, an Armv8.2-A-based commodity Android platform equipped with a Rockchip NPU, without modifying Rockchip- nor Arm-proprietary software. Our evaluation demonstrates that ASGARD effectively protects on-device DNNs in legacy SoCs with a minimal TCB size and negligible inference latency overhead.

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.

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This partnership could enhance financial literacy and inclusion, fostering a more resilient digital economy in regions with limited access.

The post Tether partners with Bitqik to boost Bitcoin and stablecoin education appeared first on Crypto Briefing.

Session 9B: DNN Attack Surfaces

Authors, Creators & Presenters: Yanzuo Chen (The Hong Kong University of Science and Technology), Yuanyuan Yuan (The Hong Kong University of Science and Technology), Zhibo Liu (The Hong Kong University of Science and Technology), Sihang Hu (Huawei Technologies), Tianxiang Li (Huawei Technologies), Shuai Wang (The Hong Kong University of Science and Technology)

PAPER
BitShield: Defending Against Bit-Flip Attacks on DNN Executables

Recent research has demonstrated the severity and prevalence of bit-flip attacks (BFAs; e.g., with Rowhammer techniques) on deep neural networks (DNNs). BFAs can manipulate DNN prediction and completely deplete DNN intelligence, and can be launched against both DNNs running on deep learning (DL) frameworks like PyTorch, as well as those compiled into standalone executables by DL compilers. While BFA defenses have been proposed for models on DL frameworks, we find them incapable of protecting DNN executables due to the new attack vectors on these executables. This paper proposes the first defense against BFA for DNN executables. We first present a motivating study to demonstrate the fragility and unique attack surfaces of DNN executables. Specifically, attackers can flip bits in the section to alter the computation logic of DNN executables and consequently manipulate DNN predictions; previous defenses guarding model weights can also be easily evaded when implemented in DNN executables. Subsequently, we propose BitShield, a full-fledged defense that detects BFAs targeting both data and sections in DNN executables. We novelly model BFA on DNN executables as a process to corrupt their semantics, and base BitShield on semantic integrity checks. Moreover, by deliberately fusing code checksum routines into a DNN's semantics, we make BitShield highly resilient against BFAs targeting itself. BitShield is integrated in a popular DL compiler (Amazon TVM) and is compatible with all existing compilation and optimization passes. Unlike prior defenses, BitShield is designed to protect more vulnerable full-precision DNNs and does not assume specific attack methods, exhibiting high generality. BitShield also proactively detects ongoing BFA attempts instead of passively hardening DNNs. Evaluations show that BitShield provides strong protection against BFAs (average mitigation rate 97.51%) with low performance overhead (2.47% on average) even when faced with fully white-box, powerful attackers.

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.

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Session 9B: DNN Attack Surfaces

Authors, Creators & Presenters: Yanzuo Chen (The Hong Kong University of Science and Technology), Zhibo Liu (The Hong Kong University of Science and Technology), Yuanyuan Yuan (The Hong Kong University of Science and Technology), Sihang Hu (Huawei Technologies), Tianxiang Li (Huawei Technologies), Shuai Wang (The Hong Kong University of Science and Technology)

PAPER
Compiled Models, Built-In Exploits: Uncovering Pervasive Bit-Flip Attack Surfaces in DNN Executables

Recent research has shown that bit-flip attacks (BFAs) can manipulate deep neural networks (DNNs) via DRAM Rowhammer exploitations. For high-level DNN models running on deep learning (DL) frameworks like PyTorch, extensive BFAs have been conducted to flip bits in model weights and shown effective. Defenses have also been proposed to guard model weights. Nevertheless, DNNs are increasingly compiled into DNN executables by DL compilers to leverage hardware primitives. These executables manifest new and distinct computation paradigms; we find existing research failing to accurately capture and expose the attack surface of BFAs on DNN executables. To this end, we launch the first systematic study of BFAs on DNN executables and reveal new attack surfaces neglected or underestimated in previous work. Specifically, prior BFAs in DL frameworks are limited to attacking model weights and assume a strong whitebox attacker with full knowledge of victim model weights, which is unrealistic as weights are often confidential. In contrast, we find that BFAs on DNN executables can achieve high effectiveness by exploiting the model structure (usually stored in the executable code), which only requires knowing the (often public) model structure. Importantly, such structure-based BFAs are pervasive, transferable, and more severe (e.g., single-bit flips lead to successful attacks) in DNN executables; they also slip past existing defenses. To realistically demonstrate the new attack surfaces, we assume a weak and more realistic attacker with no knowledge of victim model weights. We design an automated tool to identify vulnerable bits in victim executables with high confidence (70% compared to the baseline 2%). Launching this tool on DDR4 DRAM, we show that only 1.4 flips on average are needed to fully downgrade the accuracy of victim executables, including quantized models which could require 23× more flips previously, to random guesses. We comprehensively evaluate 16 DNN executables, covering three large-scale DNN models trained on three commonly-used datasets compiled by the two most popular DL compilers. Our finding calls for incorporating security mechanisms in future DNN compilation toolchains.

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.

Permalink

The post NDSS 2025 – Compiled Models, Built-In Exploits appeared first on Security Boulevard.

U.S. college graduates "have historically found jobs more quickly than people with only a high school degree," writes Bloomberg. "But that advantage is becoming a thing of the past, according to new research from the Federal Reserve Bank of Cleveland." "Recently, the job-finding rate for young college-educated workers has declined to be roughly in line with the rate for young high-school-educated workers, indicating that a long period of relatively easier job-finding prospects for college grads has ended," Cleveland Fed researchers Alexander Cline and BarıÅY Kaymak said in a blog post published Monday. The study follows the latest monthly employment data released on Nov. 20, which showed the unemployment rate for college-educated workers continued to rise in September amid an ongoing slowdown in white-collar hiring... The unemployment rate for people between the ages of 20 to 24 was 9.2% in September, up 2.2 percentage points from a year prior. There is a caveat. "Young college graduates maintain advantages in job stability and compensation once hired..." the researchers write. "The convergence we document concerns the initial step of securing employment rather than overall labor market outcomes." Their research includes a graph showing how the "unemployment gap" first increased dramatically after 2010 between college-educated and high school-educated workers, which the researchers attribute to "the prolonged jobless recovery after 2008". But that gap has been closing ever since, with that gap now smaller than at any time since the 1970s. "Young high school workers are riding the wave of the historically tight postpandemic labor market with well-below-average unemployment compared to that of past high school graduates, while young college workers are experiencing unemployment rates rarely observed among past college cohorts barring during recessions." The labor market advantages conferred by a college degree have historically justified individual investment in higher education and expanding support for college access. If the job-finding rate of college graduates continues to decline relative to the rate for high school graduates, we may see a reversal of these trends. The convergence we document concerns the initial step of securing employment rather than overall labor market outcomes. These details suggest a nuanced shift in employment dynamics, one in which college graduates face greater difficulty finding jobs than previously but maintain advantages compared with high school graduates in job stability and compensation once hired. Two key quotes: "Declining job prospects among young college graduates may reflect the continued growth in college attainment, adding ever larger cohorts of college graduates to the ranks of job seekers, even though technology no longer favors college-educated workers." "Developments related to AI, which may be affecting job-finding prospects in some cases, cannot explain the decades-long decline in the college job-finding rate."

Read more of this story at Slashdot.