Several defenses have been proposed to mitigate these attacks.We present detailed benchmarking of floating point performance for various operations based on operand values.

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We show that, POMP can accurately and efficiently pinpoint program statements that truly pertain to the crashes, making failure diagnosis significantly convenient.

Existing malware analysis platforms leave detectable fingerprints like uncommon string properties in QEMU, signatures in Android Java virtual machine, and artifacts in Linux kernel profiles.

Many proposed defenses against such side-channel attacks capitalize on this reliance.

This paper presents PThe duration of floating-point instructions is a known timing side channel that has been used to break Same-Origin Policy (SOP) privacy on Mozilla Firefox and the Fuzz differentially private database.

Our approach has been adopted by the Coccinelle team and is currently being integrated into the Linux kernel patch vetting.

Based on our study, we also provide practical solutions for anticipating double-fetch bugs and vulnerabilities.

Since these fingerprints provide the malware a chance to split its behavior depending on whether the analysis system is present or not, existing analysis systems are not sufficient to analyze the sophisticated malware.

In this paper, we propose NLast-Level Cache (LLC) attacks typically exploit timing side channels in hardware, and thus rely heavily on timers for their operation.

In this work, we propose POMP, an automated tool to facilitate the analysis of post-crash artifacts.

More specifically, POMP introduces a new reverse execution mechanism to construct the data flow that a program followed prior to its crash.

By using the data flow, POMP then performs backward taint analysis and highlights those program statements that actually contribute to the crash.