UI traces of actions and timings from LLM browser agents enable identification of the underlying model with up to 96% F1 across 14 models and multiple tasks.
Sponge Examples: Energy-Latency Attacks on Neural Networks
8 Pith papers cite this work. Polarity classification is still indexing.
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Post-processing fairness methods (ROC and EqOdds) provide the most stable fairness-utility trade-offs when training classifiers on DP synthetic tabular data, outperforming pre- and in-processing interventions.
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.
An encoding of Solidity contracts and first-order Hennessy-Milner logic into Lustre enables Kind 2 model checking of complex temporal properties in smart contracts.
Structured CTI standards like ATT&CK describe adversary actions but lack the ordering, preconditions, and environmental details needed for direct multi-stage emulation, and a translation method can bridge this gap when assumptions are recorded.
Electromagnetic side-channel attacks recover ECDSA secrets from OpenSSL on post-2019 SoCs including Snapdragon 750G and Broadcom BCM2711, showing that libgcrypt countermeasures do not fully mitigate the Nonce@Once attack.
OpDiffer applies LLMs and static analysis to opcode-level differential testing of EVMs, reporting 26 previously unknown bugs across nine implementations along with coverage gains and an estimate that 7.21% of real contracts could trigger the bugs.
The paper proposes a bottom-up framework for safe agentic AI systems that treats each component as a dual-use interface where added capabilities also expand attack surfaces across single agents, multi-agent systems, and interoperable ecosystems.
citing papers explorer
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Known By Their Actions: Fingerprinting LLM Browser Agents via UI Traces
UI traces of actions and timings from LLM browser agents enable identification of the underlying model with up to 96% F1 across 14 models and multiple tasks.
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Where to Intervene? Benchmarking Fairness-Aware Learning on Differentially Private Synthetic Tabular Data
Post-processing fairness methods (ROC and EqOdds) provide the most stable fairness-utility trade-offs when training classifiers on DP synthetic tabular data, outperforming pre- and in-processing interventions.
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Secrets Best Not Shared: DNS Privacy Enhancements for the Constrained IoT
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.
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KindHML: formal verification of smart contracts based on Hennessy-Milner logic
An encoding of Solidity contracts and first-order Hennessy-Milner logic into Lustre enables Kind 2 model checking of complex temporal properties in smart contracts.
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The Procedural Semantics Gap in Structured CTI: A Measurement-Driven STIX Analysis for APT Emulation
Structured CTI standards like ATT&CK describe adversary actions but lack the ordering, preconditions, and environmental details needed for direct multi-stage emulation, and a translation method can bridge this gap when assumptions are recorded.
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Breaking ECDSA with Electromagnetic Side-Channel Attacks: Challenges and Practicality on Modern Smartphones
Electromagnetic side-channel attacks recover ECDSA secrets from OpenSSL on post-2019 SoCs including Snapdragon 750G and Broadcom BCM2711, showing that libgcrypt countermeasures do not fully mitigate the Nonce@Once attack.
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OpDiffer: LLM-Assisted Opcode-Level Differential Testing of Ethereum Virtual Machine
OpDiffer applies LLMs and static analysis to opcode-level differential testing of EVMs, reporting 26 previously unknown bugs across nine implementations along with coverage gains and an estimate that 7.21% of real contracts could trigger the bugs.
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Toward a Safe Internet of Agents
The paper proposes a bottom-up framework for safe agentic AI systems that treats each component as a dual-use interface where added capabilities also expand attack surfaces across single agents, multi-agent systems, and interoperable ecosystems.