Empirical analysis of 444 iOS apps using dynamic traffic interception found 282 leaking LLM API keys across ten providers, with only 28% remediation after three months.
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In: IEEE Symposium on Security and Privacy (S&P)
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MHOT achieves provably minimal tree height via discriminative-bit indexing and hierarchical proofs, delivering up to 9X write throughput, 4X lower amplification, 2X smaller proofs, and 0% Nurgle attack success versus MPT on Ethereum workloads.
Formulates privacy-constrained advertising measurement as a robust causal decision problem under signal loss and derives a sharp decision frontier separating certifiable from unresolved incrementality claims.
Decentralized block building is an exact potential game with an asymptotically tight factor-2 Price of Anarchy and utility concentration bounds showing the lowest-utility builder earns at least half the highest.
PACZero achieves zero mutual information privacy in LLM fine-tuning via sign-quantized subset-aggregated ZO gradients, delivering near non-private accuracy on SST-2 at I=0.
A low-stake adversary can degrade a liquid staking pool's performance via consensus manipulation and profit from the resulting drop in its LST value through application-layer financial positions.
Cond-DP conditions DPSGD on public features with decaying spectra to achieve faster convergence guarantees and better empirical performance in label-DP regression.
ResAware improves cross-environment website fingerprinting robustness by distilling resource-privileged knowledge into a traffic-only student model, raising Var-CNN F1 from 72.77% to 81.49% under 150-day drift on a 160k-sample dataset.
Embedding and removing a dummy backdoor reduces unknown backdoor success in generative LLMs by targeting shared trigger-activated internal mechanisms.
GapFuzz detects cross-plane divergences in distributed SDN clusters by injecting timed contradictory Northbound requests on backup nodes and reconstructing state via replica queries plus kernel probes, reporting 81.7% detection on ONOS 2.7.
DNS over CoAP with packet length equalization, block-wise transfer, header and payload compression reduces DNS identification accuracy to 77-86% in constrained IoT scenarios, outperforming DNS over HTTPS.
TraceCodec is a compiler-backed neural codec that lifts packets to state-aware action latents for high-fidelity multi-flow trace generation, matching real traces within 0.03% on CICIDS2017.
A systematic review of on-device AI inference security finds defenses are imbalanced, with roughly half focused on IP theft while one-third of attacks (adversarial examples) lack any associated defenses.
PoisonCap uses a new poison capability format to deliver strict use-after-free and initialization safety for CHERI systems with no fundamental overhead over Cornucopia baselines.
An automated static-analysis pipeline generates labeled structural units from virtualization-obfuscated binaries so LLMs can analyze them without exceeding token limits.
Current AI image watermark removal attacks replace the watermark with a different forensic signal, allowing independent detectors to distinguish processed outputs from clean images at over 98% true-positive rate under a 1% false-positive budget.
GRASP detects anomalies in system provenance graphs via self-supervised executable prediction from two-hop neighborhoods, outperforming prior PIDS on DARPA datasets by identifying all documented attacks where behaviors are learnable plus additional unlabeled suspicious activity.
Metaphors scaffold youth privacy reasoning and design, with relational metaphors potentially increasing disclosure by framing systems as loyal companions.
Pomegranate compartmentalizes commodity OS kernels via virtualization extensions, sentry functions, and EPT-enforced policies, achieving negligible overhead on a Linux network stack when compartment boundaries limit cross-talk.
Semia synthesizes Datalog representations of agent skills via constraint-guided loops to enable reachability queries for semantic risks, finding critical issues in over half of 13,728 real skills with 97.7% recall on expert-labeled samples.
BadStyle creates stealthy backdoors in LLMs by poisoning samples with imperceptible style triggers and using an auxiliary loss to stabilize payload injection, achieving high attack success rates across multiple models while evading defenses.
A differentially private pipeline using node-level DP summaries to fit ERGMs or SBMs, generate synthetic networks, and simulate SIS disease spread on ARTNet sexual contact data produces incidence, prevalence, and intervention effect sizes close to non-private versions.
PrivacyAkinator uses LLM-generated questions grounded in data-flow representations and a news-mined design space to help developers surface privacy decisions, yielding 47% more decisions identified in 73% less time than PRAM in a 24-person study.
ContentFuzz rewrites posts with LLM guidance from stance model confidence to flip machine labels without altering human intent, tested across four models and three datasets in two languages.
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