Impact of the malicious input data modification on the efficiency of quantum spatial search

TL;DR

This paper shows how malicious data modifications can significantly affect the efficiency of quantum spatial search algorithms, highlighting potential vulnerabilities and providing a framework for analyzing such attacks.

Contribution

It introduces a framework for analyzing malicious attacks on quantum search algorithms and demonstrates their impact on different graph models.

Findings

Malicious data manipulation can alter quantum search efficiency.

The framework enables analysis of attack impacts on various graph structures.

Quantum search algorithms are vulnerable to input data attacks.

Abstract

In this paper we demonstrate that the efficiency of quantum algorithms can be significantly altered by malicious manipulation of the input data. We exemplify the possibility of attacks on quantum spatial search based on Szegedy walk. We achieve this by proposing a framework suitable for analysing efficiency of attacks on quantum search algorithms. We provide the analysis of proposed attacks for different models of random graphs.