Predominant Aspects on Security for Quantum Machine Learning: Literature Review

arXiv:2401.07774v2 Announce Type: replace-cross
Abstract: Quantum Machine Learning (QML) has emerged as a promising intersection of quantum computing and classical machine learning, anticipated to drive breakthroughs in computational tasks. This paper discusses the question which security concerns and strengths are connected to QML by means of a systematic literature review. We categorize and review the security of QML models, their vulnerabilities inherent to quantum architectures, and the mitigation strategies proposed. The survey reveals that while QML possesses unique strengths, it …

arxiv computational computing connected cs.cr drive intersection literature machine machine learning qml quant-ph quantum quantum computing question review security security concerns