Establishing a leader in a pairwise comparisons method
This work addresses manipulation vulnerabilities in decision-making systems, but it is incremental as it builds directly on previous research.
The authors tackled the problem of manipulation in pairwise comparison decision-making methods by developing two algorithms that enable attackers to equalize the weights of selected alternatives and choose a leader, with Monte Carlo simulations showing how matrix size and inconsistency affect manipulation ease.
Abstract Like electoral systems, decision-making methods are also vulnerable to manipulation by decision-makers. The ability to effectively defend against such threats can only come from thoroughly understanding the manipulation mechanisms. In the presented article, we show two algorithms that can be used to launch a manipulation attack. They allow for equating the weights of two selected alternatives in the pairwise comparison method and, consequently, choosing a leader. The theoretical considerations are accompanied by a Monte Carlo simulation showing the relationship between the size of the PC matrix, the degree of inconsistency, and the ease of manipulation. This work is a continuation of our previous research published in the paper (Szybowski et al., 2023)