Tootfinder

FARFETCH'D: A Side-Channel Analysis Framework for Privacy Applications on Confidential Virtual Machines
Ruiyi Zhang, Albert Cheu, Adria Gascon, Daniel Moghimi, Phillipp Schoppmann, Michael Schwarz, Octavian Suciu
https://arxiv.org/abs/2506.15924

FARFETCH'D: A Side-Channel Analysis Framework for Privacy Applications on Confidential Virtual Machines
Confidential virtual machines (CVMs) based on trusted execution environments (TEEs) enable new privacy-preserving solutions. Yet, they leave side-channel leakage outside their threat model, shifting the responsibility of mitigating such attacks to developers. However, mitigations are either not generic or too slow for practical use, and developers currently lack a systematic, efficient way to measure and compare leakage across real-world deployments. In this paper, we present FARFETCH'D, an ope…

Beat the heat and treat yourself! Enjoy delicious ice cream, generously sponsored by Voyager Search. Available at the partner area.
#bbuzz

We decided to trade in our aged Mazda on a new car. Was always going to be an EV for our next car so bit the bullet and took advantage of some good prices and a generous trade-in to get an MGS5. #ev

Beat the heat and treat yourself! Enjoy delicious ice cream, generously sponsored by Voyager Search. Available at the partner area.
#bbuzz

Detecting Hard-Coded Credentials in Software Repositories via LLMs
Chidera Biringa, Gokhan Kul
https://arxiv.org/abs/2506.13090 https://

Detecting Hard-Coded Credentials in Software Repositories via LLMs
Software developers frequently hard-code credentials such as passwords, generic secrets, private keys, and generic tokens in software repositories, even though it is strictly advised against due to the severe threat to the security of the software. These credentials create attack surfaces exploitable by a potential adversary to conduct malicious exploits such as backdoor attacks. Recent detection efforts utilize embedding models to vectorize textual credentials before passing them to classifier…

Stream DaQ: Stream-First Data Quality Monitoring
Vasileios Papastergios, Anastasios Gounaris
https://arxiv.org/abs/2506.06147 https://

Stream DaQ: Stream-First Data Quality Monitoring
Data quality is fundamental to modern data science workflows, where data continuously flows as unbounded streams feeding critical downstream tasks, from elementary analytics to advanced artificial intelligence models. Existing data quality approaches either focus exclusively on static data or treat streaming as an extension of batch processing, lacking the temporal granularity and contextual awareness required for true streaming applications. In this paper, we present a novel data quality monit…

Detecting Hard-Coded Credentials in Software Repositories via LLMs
Chidera Biringa, Gokhan Kul
https://arxiv.org/abs/2506.13090 https://

Detecting Hard-Coded Credentials in Software Repositories via LLMs
Software developers frequently hard-code credentials such as passwords, generic secrets, private keys, and generic tokens in software repositories, even though it is strictly advised against due to the severe threat to the security of the software. These credentials create attack surfaces exploitable by a potential adversary to conduct malicious exploits such as backdoor attacks. Recent detection efforts utilize embedding models to vectorize textual credentials before passing them to classifier…

This https://arxiv.org/abs/1903.01933 has been replaced.
link: https://scholar.google.com/scholar?q=a

Sparkling saddle loops of vector fields on surfaces
We study bifurcations of vector fields on 2-manifolds with handles in generic one-parameter families unfolding vector fields with a separatrix loop of a hyperbolic saddle. These bifurcations can differ drastically from the analogous bifurcations on the sphere. The reason is that, on a surface, a free separatrix of a hyperbolic saddle may wind toward the separatrix loop of the same saddle. When this loop is broken, sparkling saddle loops emerge. In the orientable case, the parameter values corre…

Way back in 2022, as the world tried to readjust back to "normal" following COVID - I helped to co-organise a bootcamp with sponsorhop from the @… IASC, @… and a generous dollop of help from @… and @… colleagues.
We gathered 10 senior scientist mentors and 22 students in an old torpedo research station (now used by Roskilde University) for 10 days. It was an extremely intense period but the 4th paper produced by this talented group has just come out.
I consider facilitating #EarlyCareerScientists to work on important science problems an extremely rewarding part of my job, and I'm looking forward to the next one already as part of our PISCO project.
In the mean time, go and read this extremely cool work, collecting together a huge number of radiosonde observations going back to the 1950s over the Arctic Ocean and using them to assess how well CMIP6 models represent lower atmosphere.
#CMIP6 #ClimateModels #Arctic #ArcticClimate #SeaIce
https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2024JD041412