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Injected and Leaked: Actively Inducing Side-Channel Leakage Using Electromagnetic Injection and Hardware Nonlinearity

arXiv cs.CRby Haoran Yan ()1 min read6 · 4 reads
AI summary · glm-5.3-flashSummaries by Vani AI

Researchers introduce InjectEave, using electromagnetic injection and hardware nonlinearity to induce side-channel leakage and eavesdrop on headphone audio from 30 meters.

An arXiv paper shows electromagnetic injection can actively amplify side-channel leakage: nonlinear hardware such as amplifiers, ADCs, and power converters modulates secret electrical signals onto an injected EM carrier, upconverting low-frequency secrets into measurable EM emissions. By tuning injection frequency and amplitude, an adversary can shape the effective spectrum and entropy of the resulting leakage. The InjectEave attack demonstrated eavesdropping on wired and wireless headphone audio from up to 30 meters and in through-wall scenarios using accessible RF equipment, plus leakage of smart home device power consumption and analog sensor inputs. Case studies show closed-loop eavesdropping and manipulation of landline phone conversations, and the paper discusses mitigations.

Key facts
  • Ubiquitous amplifiers, ADCs, and power converters act as unintentional modulators of secrets.
  • Injection frequency and amplitude tune the leakage spectrum and entropy.
  • Demonstrated through-wall operation and attacks on landline calls; mitigations analyzed.
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From the original article

1 min read at arxiv.org

Electromagnetic (EM) side-channel leakage and injection are typically treated as distinct physical phenomena, threatening data confidentiality and integrity respectively. This work investigates how EM injection can be used to amplify side-channel leakage that is otherwise infeasible. We introduce a novel framework for Injection-Induced EM Side Channels to enable integrated, closed-loop EM security analysis.

arXiv cs.CR

By Haoran Yan · arxiv.org

Read the full article at arXiv cs.CR

A short excerpt; the article and its images belong to the publisher. Summary, key facts and assessment above are AI-written from the article and can be wrong.