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Client-Side Probing of Deleted Ridge Statistics in Federated Unlearning
Researchers show malicious federated learning clients can probe broadcast classifiers to recover deleted samples, exposing exact label leakage on MNIST and CIFAR-10.
The paper shows that federated unlearning systems broadcasting updated linear classifiers leak compact additive training summaries to clients. A malicious client can submit known changes, identify server states from returned classifiers, and compare states around an isolated deletion to expose the deleted sample, class, or client summary, potentially enabling reinsertion. On MNIST and CIFAR-10, high-precision broadcasts allowed exact label recovery for every tested deletion, while lower precision sharply reduced fine-grained recovery.
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EFI Pairs Without One-Way Puzzles: Oracle Separations from Communication Complexity
Theorists build a classical oracle where one-way puzzles fail yet EFI pairs survive, separating two candidate minimal assumptions of quantum cryptography.
The paper constructs a single classical oracle relative to which one-way puzzles do not exist, even with an unbounded verifier, while an EFI pair survives every classical-query distinguisher holding advice, making one superposition query at the end. Security is proven by reducing adversary knowledge to communication complexity for Vector-in-Subspace, with the superposition query bounded using random matrix theory. Relative to the oracle, quantum polynomial time offers no advantage on tasks with classical inputs and outputs and there is no proof of quantumness, separating the leading minimal assumptions of quantum cryptography.
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Certifying Adversarial Robustness of Quantum Classifiers under Known-Readout Query Access
Framework certifies adversarial robustness of quantum classifiers using only measurement statistics and finite-shot outcomes, demonstrated on IBM Quantum hardware.
The paper introduces a measurement-only certification framework for adversarial robustness of quantum classifiers under known-readout query access, requiring no tomography, parameters, or gradients. It returns a lower bound ruling out untargeted errors within a radius and an attack-independent upper bound witnessing an adversarial state, both estimable with finite-sample guarantees. Evaluations show the lower bound tracks exact optima on tractable instances while the upper bound stays informative when standard attacks fail. The method was validated on IBM Quantum hardware using 40 executions of two 8-qubit quantum neural networks.
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Toward an Empirical Probabilistic Risk Manifestation Model of Organizational Cybersecurity in SMEs
Empirical study of 22 SME security assessments builds a probabilistic risk model and shows assessments can be cut 24-45% while retaining most critical findings.
Researchers analyzed 281 validated security findings from 22 real-world SME cybersecurity assessments conducted over two years via a pro bono university clinic. They derived an empirical Risk Manifestation Model linking eight organizational security functions to two exposure conditions, five attack mechanisms, and six outcome categories, using probability propagation to identify dominant risk pathways. The dominant pathway runs from asset exposure to credential compromise to unauthorized access, stable under leave-one-organization-out analysis. Retaining six functions reduces assessment burden by 24% while preserving 97% of critical findings; five functions cut burden 45% while preserving 89% of critical findings.
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Building a Linux GPU Driver for the M4 Mac Mini in One Month
Two developers built a fully OpenGL ES 3.0 compliant Linux GPU driver for the M4 Mac Mini in one month via clean-room reverse engineering.
Niklas and the author reverse engineered Apple's AGX GPU firmware ABI and user-space components in about a month, a process that normally takes years, producing an OpenGL ES 3.0 conformant driver fast enough to run Minecraft at 200fps on an M4 Mac Mini. The work was done transparently using hypervisor traces without examining Apple binaries, following clean-room practices, and included a custom shader compiler, command stream builder, and a full Linux kernel driver for the firmware ABI. The A18 Pro firmware ABI proved significantly more complex than the M1's, with 1.5x as many structs and twice as many pointers. All experiments and provenance evidence were published in public agx-re repositories.
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