Tootfinder

Chat Control: quando la protezione dei minori sfida la riservatezza digitale
#ChatControl UE: la nuova proposta di regolamento che rischia di compromettere la #privacy digitale. Scansione preventiva dei messaggi per proteggere i minori vs. sorveglianza di massa. Analisi dei rischi e …

NFL pre-camp observations, plus crazy NBA-style trade proposals and Buccaneers All-Pro to miss start of season

https://www.cbssports.com/nfl/news/nfl-p…

LDP$^3$: An Extensible and Multi-Threaded Toolkit for Local Differential Privacy Protocols and Post-Processing Methods
Berkay Kemal Balioglu, Alireza Khodaie, Mehmet Emre Gursoy
https://arxiv.org/abs/2507.05872

LDP$^3$: An Extensible and Multi-Threaded Toolkit for Local Differential Privacy Protocols and Post-Processing Methods
Local differential privacy (LDP) has become a prominent notion for privacy-preserving data collection. While numerous LDP protocols and post-processing (PP) methods have been developed, selecting an optimal combination under different privacy budgets and datasets remains a challenge. Moreover, the lack of a comprehensive and extensible LDP benchmarking toolkit raises difficulties in evaluating new protocols and PP methods. To address these concerns, this paper presents LDP$^3$ (pronounced LDP-C…

Search for GeV-PeV neutrinos from nova T Coronae Borealis with IceCube
Jessie Thwaites, Justin Vandenbroucke
https://arxiv.org/abs/2507.07096 https://

Search for GeV-PeV neutrinos from nova T Coronae Borealis with IceCube
The widely anticipated outburst of recurrent nova T Coronae Borealis (T CrB), which is near the end of its 80-year cycle, provides an excellent opportunity to search for neutrinos from novae. Novae are an energetic class of transients, which have been studied for hundreds of years. Because many of them are located nearby, novae provide an excellent astrophysical laboratory to study shock-powered emission in our own backyard. Several recent novae have previously been detected in GeV gamma rays, …

Dan Adams, tech lead for Neuralink Blindsight brain implant development, reports that he is at the National Foundation of the Blind annual convention in New Orleans.
For those of you who happen to be there perhaps a great opportunity for a chat. #blind #blindness

Dan Adams (@Dan___Adams) on X
I’m thrilled to be at the annual convention of the National Foundation of the Blind in New Orleans. Learning from this incredible community at the largest gathering of blind people in the world is fascinating and inspiring! https://t.co/l3Ob4FaKBA #NFB_voice #Blindsight

Existence and nonexistence of commutativity gadgets for entangled CSPs
Eric Culf, Josse van Dobben de Bruyn, Matthijs Vernooij, Peter Zeman
https://arxiv.org/abs/2509.07835 http…

Existence and nonexistence of commutativity gadgets for entangled CSPs
Commutativity gadgets allow NP-hardness proofs for classical constraint satisfaction problems (CSPs) to be carried over to undecidability proofs for the corresponding entangled CSPs. This has been done, for instance, for NP-complete boolean CSPs and 3-colouring in the work of Culf and Mastel. For many CSPs over larger alphabets, including $k$-colouring when $k \geq 4$, it is not known whether or not commutativity gadgets exist, or if the entangled CSP is decidable. In this paper, we study commu…

PropVG: End-to-End Proposal-Driven Visual Grounding with Multi-Granularity Discrimination
Ming Dai, Wenxuan Cheng, Jiedong Zhuang, Jiang-jiang Liu, Hongshen Zhao, Zhenhua Feng, Wankou Yang
https://arxiv.org/abs/2509.04833

PropVG: End-to-End Proposal-Driven Visual Grounding with Multi-Granularity Discrimination
Recent advances in visual grounding have largely shifted away from traditional proposal-based two-stage frameworks due to their inefficiency and high computational complexity, favoring end-to-end direct reference paradigms. However, these methods rely exclusively on the referred target for supervision, overlooking the potential benefits of prominent prospective targets. Moreover, existing approaches often fail to incorporate multi-granularity discrimination, which is crucial for robust object i…

Towards Reliable Service Provisioning for Dynamic UAV Clusters in Low-Altitude Economy Networks
Yanwei Gong, Ruichen Zhang, Xiaoqing Wang, Xiaolin Chang, Bo Ai, Junchao Fan, Bocheng Ju, Dusit Niyato
https://arxiv.org/abs/2509.06112

Towards Reliable Service Provisioning for Dynamic UAV Clusters in Low-Altitude Economy Networks
Unmanned Aerial Vehicle (UAV) cluster services are crucial for promoting the low-altitude economy by enabling scalable, flexible, and adaptive aerial networks. To meet diverse service demands, clusters must dynamically incorporate a New UAVs (NUAVs) or an Existing UAV (EUAV). However, achieving sustained service reliability remains challenging due to the need for efficient and scalable NUAV authentication, privacy-preserving cross-cluster authentication for EUAVs, and robust protection of the c…

From Perception to Protection: A Developer-Centered Study of Security and Privacy Threats in Extended Reality (XR)
Kunlin Cai, Jinghuai Zhang, Ying Li, Zhiyuan Wang, Xun Chen, Tianshi Li, Yuan Tian
https://arxiv.org/abs/2509.06368

From Perception to Protection: A Developer-Centered Study of Security and Privacy Threats in Extended Reality (XR)
The immersive nature of XR introduces a fundamentally different set of security and privacy (S&P) challenges due to the unprecedented user interactions and data collection that traditional paradigms struggle to mitigate. As the primary architects of XR applications, developers play a critical role in addressing novel threats. However, to effectively support developers, we must first understand how they perceive and respond to different threats. Despite the growing importance of this issue, ther…

FedP3E: Privacy-Preserving Prototype Exchange for Non-IID IoT Malware Detection in Cross-Silo Federated Learning
Rami Darwish, Mahmoud Abdelsalam, Sajad Khorsandroo, Kaushik Roy
https://arxiv.org/abs/2507.07258

FedP3E: Privacy-Preserving Prototype Exchange for Non-IID IoT Malware Detection in Cross-Silo Federated Learning
As IoT ecosystems continue to expand across critical sectors, they have become prominent targets for increasingly sophisticated and large-scale malware attacks. The evolving threat landscape, combined with the sensitive nature of IoT-generated data, demands detection frameworks that are both privacy-preserving and resilient to data heterogeneity. Federated Learning (FL) offers a promising solution by enabling decentralized model training without exposing raw data. However, standard FL algorithm…