Improving connectivity of compromised digital networks via algebraic connectivity maximisation

Automation and digitalisation in the logistics industry enhance the performance of customer service, while sabotage of the digital logistics network adversely deteriorates the performance. Although precau-tionary strategies are implemented to protect critical assets in the digital logistics network, a high-level adversary can still penetrate the network and launch attacks inside the organisation. Thus, real-time re-covery plays an important role in facing real-time cyberattacks. This paper proposes a novel max-min integer programming model subject to a budget constraint to improve network connectivity of a com-promised digital logistics network via a strategy of maximising algebraic connectivity. Due to the NP-hardness of the maximisation problem, the optimal solution may not be found quickly. Thus, several heuristic algorithms, including greedy algorithms, tabu search and relaxed semidefinite programming (SDP) with rounding, are proposed. Verification of these heuristic algorithms is achieved by applying them, firstly to a hypothetical network, then to a large scale-free network which mimics a digital logis -tics network. (c) 2021 Elsevier B.V. All rights reserved.