Cybersecurity Enhancements for ERP Systems: A Technical Framework

Enterprise Resource Planning systems are now the digital backbone of contemporary organizations, consolidating business-critical functions while concurrently putting enterprises into an ever-more sophisticated landscape of cyber threats. The transition to cloud-native architectures and API-driven ecosystems has radically changed the security challenges for ERP deployments, demanding end-to-end cybersecurity frameworks that go beyond the perimeter-based traditional defenses. Global cybercrime expenses keep rising, with economic losses potentially hitting record highs as cyber attackers evolve more sophisticated attack methods aimed at enterprise environments. Geographic spread of cybercrime identifies high-concentration threat areas in which organized crime groups take advantage of local vulnerabilities and gaps in technological infrastructure to attack high-value ERP implementations. Advanced cybersecurity models today need to combat several vectors in unison, such as AI-facilitated attacks, supply chain breaches, and advanced social engineering attacks, which have seen an enormous rise over the last few years. Zero Trust models are a break from conventional security methodologies, which institute continuous authentication processes that consider all users and devices to be potentially breached while ensuring operational agility. Application safety posture control solutions provide holistic vulnerability scanning competencies that integrate numerous scanning technologies to prioritize remediation via commercial enterprise effect and exploitability. State-of-the-art chance detection technologies utilize device learning algorithms to stumble upon behavioral anomalies and assault styles that traditional safety solutions aren't capable of detecting. The usage of lightweight cryptographic algorithms and consumer-focused audit structures ensures end-to-end statistics protection without compromising the performance developments important for real-time enterprise tactics.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-09-26
DOI
https://doi.org/10.5281/zenodo.17211221
Primary Topic
Agriculture and Social Issues
Type
article
Field-Weighted Citation Impact
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article

Cybersecurity Enhancements for ERP Systems: A Technical Framework

Zenodo (CERN European Organization for Nuclear Research)
Agriculture and Social Issues
article

Cybersecurity Enhancements for ERP Systems: A Technical Framework

article en

Abstract

Enterprise Resource Planning systems are now the digital backbone of contemporary organizations, consolidating business-critical functions while concurrently putting enterprises into an ever-more sophisticated landscape of cyber threats. The transition to cloud-native architectures and API-driven ecosystems has radically changed the security challenges for ERP deployments, demanding end-to-end cybersecurity frameworks that go beyond the perimeter-based traditional defenses. Global cybercrime expenses keep rising, with economic losses potentially hitting record highs as cyber attackers evolve more sophisticated attack methods aimed at enterprise environments. Geographic spread of cybercrime identifies high-concentration threat areas in which organized crime groups take advantage of local vulnerabilities and gaps in technological infrastructure to attack high-value ERP implementations. Advanced cybersecurity models today need to combat several vectors in unison, such as AI-facilitated attacks, supply chain breaches, and advanced social engineering attacks, which have seen an enormous rise over the last few years. Zero Trust models are a break from conventional security methodologies, which institute continuous authentication processes that consider all users and devices to be potentially breached while ensuring operational agility. Application safety posture control solutions provide holistic vulnerability scanning competencies that integrate numerous scanning technologies to prioritize remediation via commercial enterprise effect and exploitability. State-of-the-art chance detection technologies utilize device learning algorithms to stumble upon behavioral anomalies and assault styles that traditional safety solutions aren't capable of detecting. The usage of lightweight cryptographic algorithms and consumer-focused audit structures ensures end-to-end statistics protection without compromising the performance developments important for real-time enterprise tactics.

Zenodo (CERN European Organization for Nuclear Research)
Kakatiya University (IN)
Openalex Percentile: Top 34%
Agriculture and Social Issues
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