# Perspectives on risk prioritization of data center vulnerabilities using rank aggregation and multi-objective optimization

arXiv: https://arxiv.org/abs/2202.07466 · HTML: https://mlsanity.com/paper/2202.07466/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 9 of its 64 references that are in the map.
- First posted on arXiv 12 Feb 2022.

## Builds on (most cited first, 9 of 9)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [A Practical Guide to Multi-Objective Reinforcement Learning and Planning](https://mlsanity.com/paper/2103.09568/) (2021)
- [A Survey of Multi-Objective Sequential Decision-Making](https://mlsanity.com/paper/1402.0590/) (2014)
- [Multi-Objective Multi-Agent Decision Making: A Utility-based Analysis and Survey](https://mlsanity.com/paper/1909.02964/) (2019)
- [Exploit Prediction Scoring System (EPSS)](https://mlsanity.com/paper/1908.04856/) (2019)
- [A Survey on Data-driven Software Vulnerability Assessment and Prioritization](https://mlsanity.com/paper/2107.08364/) (2021)
- [Multi-objective Ranking via Constrained Optimization](https://mlsanity.com/paper/2002.05753/) (2020)
- [A Look at the Time Delays in CVSS Vulnerability Scoring](https://mlsanity.com/paper/1801.00938/) (2018)
- [A Hybrid Ensemble Feature Selection Design for Candidate Biomarkers Discovery from Transcriptome Profiles](https://mlsanity.com/paper/2108.00290/) (2021)

## Abstract (arXiv)

Nowadays, data has become an invaluable asset to entities and companies, and keeping it secure represents a major challenge. Data centers are responsible for storing data provided by software applications. Nevertheless, the number of vulnerabilities has been increasing every day. Managing such vulnerabilities is essential for building a reliable and secure network environment. Releasing patches to fix security flaws in software is a common practice to handle these vulnerabilities. However, prioritization becomes crucial for organizations with an increasing number of vulnerabilities since time and resources to fix them are usually limited. This review intends to present a survey of vulnerability ranking techniques and promote a discussion on how multi-objective optimization could benefit the management of vulnerabilities risk prioritization. The state-of-the-art approaches for risk prioritization were reviewed, intending to develop an effective model for ranking vulnerabilities in data centers. The main contribution of this work is to point out multi-objective optimization as a not commonly explored but promising strategy to prioritize vulnerabilities, enabling better time management and increasing security.