Predictive Cyber-Resilience: AI-Powered Self-Defending Microservices for Zero-Downtime Security

Cyberattacks on distributed microservices have become more elusive, and it is not enough to only monitor for these microservices but rather an active defense is necessary. In this paper, we present Predictive Cyber-Resilience (PCR), an AI-driven self-defending security framework that secures both cloud-native and edge environments. PCR uses Preemptive Cyber response for predicting and neutralizing threats before their manifestation using federated learning, synthetic adversarial networks (SANs) and anomaly detection and reducing breaches by 90%. Different from traditional approaches, PCR adapts dynamically the human intervention to the changes in the attack vectors Working in conjunction with service meshes and multi-cloud platforms, PCR delivers a no-downtime security adaptation that enables a paradigm shift toward autonomous cybersecurity and AI-driven threat mitigation.

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Publication Details

Journal
International Journal of Scientific Research in Computer Science Engineering and Information Technology
Published
2025-03-05
DOI
https://doi.org/10.32628/cseit25112391
Primary Topic
Software System Performance and Reliability
Type
article
Field-Weighted Citation Impact
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article

Predictive Cyber-Resilience: AI-Powered Self-Defending Microservices for Zero-Downtime Security

Sandeep Konakanchi
International Journal of Scientific Research in Computer Science Engineering and Information Technology
Software System Performance and Reliability
article

Predictive Cyber-Resilience: AI-Powered Self-Defending Microservices for Zero-Downtime Security

Sandeep Konakanchi
article en

Abstract

Cyberattacks on distributed microservices have become more elusive, and it is not enough to only monitor for these microservices but rather an active defense is necessary. In this paper, we present Predictive Cyber-Resilience (PCR), an AI-driven self-defending security framework that secures both cloud-native and edge environments. PCR uses Preemptive Cyber response for predicting and neutralizing threats before their manifestation using federated learning, synthetic adversarial networks (SANs) and anomaly detection and reducing breaches by 90%. Different from traditional approaches, PCR adapts dynamically the human intervention to the changes in the attack vectors Working in conjunction with service meshes and multi-cloud platforms, PCR delivers a no-downtime security adaptation that enables a paradigm shift toward autonomous cybersecurity and AI-driven threat mitigation.

International Journal of Scientific Research in Computer Science Engineering and Information TechnologyVol. 11(2)
Southwest Airlines (United States) (US)
Openalex Percentile: Top 96%
Software System Performance and Reliability
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Predictive Cyber-Resilience: AI-Powered Self-Defending Microservices for Zero-Downtime Security — Sandeep Konakanchi · International Journal of Scientific Research in Computer Science Engineering and Information Technology (2025) | TGRS Research Map | TGRS