Recognized research
Indexed by NASA ADS & Harvard-Smithsonian.
QBER (Quantified Business Exposure to Risks) blends technical exposure with economic context to produce a loss-exceedance curve — the probability of exceeding any given dollar loss in a year.
IEEE COMPSAC 2025NASA ADSHarvard CfAarXiv:2405.03513DSCI FinSec
Loss-exceedance
$5.33M
P(loss > $5.33M) = 12.0% / yr
CVaR = E[ loss | loss > VaR ]
CVaR = E[ loss | loss > VaR ]
Library
Papers & technical briefs.
Cyber Risk Quantification Framework
Guide to QBER
Explore how Zeron's QBER model transforms cyber risk into business intelligence—enabling dynamic assessments, financial impact analysis, and data-driven decisions.
Guide to QBER
Download Advanced Risk Quantification
Advanced Risk Quantification
Explore FAIR, QBER, and Monte Carlo models—simplified by Zeron to deliver real-time, business-aligned cyber risk insights.
From FAIR to QBER: A Smarter Way to Quantify Cyber Risk
Download Vendor Risk Management
Vendor Risk Management
Learn how to manage vendor-related cyber risks with automation, proven frameworks, and real-world case studies from Zeron.
Best Practices & Real-World Results in Third-Party Risk Management
Download Compliance Made Easy
Compliance Made Easy
Learn how Zeron streamlines SEBI, DPDP, and global regulatory compliance through automation, evidence collection, and real-time monitoring.
Simplify SEBI & Global Compliance with Real-Time, Automated Controls
Download AI for Cyber Risk
AI for Cyber Risk
Discover how Zeron uses AI to detect threats, automate compliance, and prevent AI-powered attacks like deepfakes and adversarial exploits.
Leverage AI to Predict Threats for Cyber Risk Management
Download Cyber Risk Quantification
QBER Research Paper
Dive deep into the academic foundations of QBER—Zeron’s risk quantification model built to bridge technical, economic, and legal (TEL) impacts for strategic cybersecurity planning.
Quantifying Cyber Risk with Precision & Business Alignment
Download Cyber Risk Quantification.
QBER Constant
Discover how Zeron’s QBER Constant model redefines CVaR with dynamic exploitability, real-time mitigation efficiency, and sector-specific risk profiling—empowering smarter, quantifiable cybersecurity decisions.
A Next-Gen Framework for Cyber Value at Risk (CVaR)
Download PCAP Tool, PcapNinja
PcapNinja Research
Explore how PcapNinja uses machine learning and real-time traffic analysis to detect threats and visualize protocol behavior.
Lightweight ML-Powered Tool for Packet Capture & Threat Detection
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Vulnerability Weightage and Prioritization Model: Derived from Real Data and Community Insights
A dynamic vulnerability prioritization model fusing CVSS, EPSS, CWE, CAPEC and MITRE ATT&CK with community intelligence for real-time, risk-based remediation.
A dynamic prioritization model fusing CVSS, EPSS, CWE, CAPEC and MITRE ATT&CK with community intelligence for real-time, risk-based remediation.
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Extending the Attack Graph Model: Integrating Reconnaissance Stages
Integrating reconnaissance stages into NIST attack-graph modelling to visualise full attack paths and sharpen cyber-risk estimation.
Integrating reconnaissance stages into NIST attack-graph modelling to reveal full attack paths and sharpen cyber-risk estimation.
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Vendor PulseGen: Generative Vendor Risk Management Platform
A generative vendor-risk platform that auto-builds tailored questionnaires and quantifies third-party risk via Question, Compliance and External-Surface risk scores.
A generative platform that auto-builds tailored vendor questionnaires and quantifies third-party risk via QRS, CRS and ESR scores.
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Strengthening Cyber Resilience of Small Businesses in BFSI: A CIA-Driven Strategy for Investment and Risk Management
A CIA-driven strategy to optimise cybersecurity investment and risk management for small businesses in the BFSI sector.
A CIA-driven strategy to optimise cybersecurity investment and risk for small businesses in the BFSI sector.
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