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Unisys Advanced Machine Learning Cyber Security Analytics presentation


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Learn how leading corporations around the world are leveraging Unisys Cyber Intelligence Platform to guard against threats from outside (including the Dark Web) and within the organization with proactive analytics that spot suspicious user behavior and predict security issues across your many digital assets and connections.

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Unisys Advanced Machine Learning Cyber Security Analytics presentation

  1. 1. May 2017 Advanced Machine Learning Cyber Security Analytics
  2. 2. © 2017 Unisys Corporation. All rights reserved. 22 Unisys Builds Large Advanced Data Analytics Mission Critical Knowledge Environments We process more than 1.3 Billion transactions a day and 700,000 queries a day predicting threats against the US. Unisys has been supporting DHS for more than 15 years. On a Typical Day, Department of Homeland Security- Customs and Border Protection (DHS-CBP) • Processes 932,456 passengers and pedestrians • Processes 64,483 truck, rail, and sea containers • Seizes 13,717 pounds of drugs
  3. 3. © 2017 Unisys Corporation. All rights reserved. 33 Unisys Advanced Cyber Intelligence Platform • Behavioral Anomaly Detection Models – Models for the prediction of malicious network activity across the enterprise – Works with your current Security information and event management (SIEM) • Threat Intelligence Engine – Models providing increased visibility into known threats – Improved context and intelligence through the correlation of multiple threat feeds – Unique partnership with Team Cymru, Recorded Future, Farsight and Unisys Intelligence Feeds • Advanced Dynamic Microsegmentation Model – Utilizes network data to provide near real time microsegmentation – Integrates with most Software Designed Security (SDS) Solutions including Unisys Stealth Our Cyber Intelligence Platform can easily be integrated with your current Security Operations Center (SOC) operations for increased security capabilities leveraging machine learning and predictive models
  4. 4. © 2017 Unisys Corporation. All rights reserved. 44 Cyber Intelligence Platform
  5. 5. © 2017 Unisys Corporation. All rights reserved. 55 Reconnaissance Lateral movement Command and control Exfiltration Threat behavior use cases IP address Host name URL UserID Hash Registry entry and file Discrete indicators of compromiseVulnerabilities Compliance Malware analysis Open source intel Industry licensed intel Unisys-specific intel Advanced Predictive Model API MSS Cyber Threat Intelligence • Normalization • Threat actor tracking • Attacker use cases Managed Security Services (MSS) Cyber Threat Intelligence Team Unisys Cyber Threat Intelligence Platform Unisys SOC Network
  6. 6. © 2017 Unisys Corporation. All rights reserved. 66 Retail Bank Social and Dark Web Threat Intelligence Business Problem • Need for additional threat intelligence and context for risks to the enterprise Business Benefits • Physical threat to locations and executives • Intelligence on dark web chatter specifically focused on the brand and banking threats in general • Exposed network credentials, phishing attempts, CC numbers and advanced intelligence prior to events • Integration with current SIM and security tools for easy implementation into existing processes Our Solution • Our unified social and dark web listening solution eliminates noise and provides a level of intelligence that has not been available before
  7. 7. © 2017 Unisys Corporation. All rights reserved. 77 Large Utility Client Advanced ML and Predictive Threat Detection Business Problem • Ingest network data from existing SIEM tool and SOC environment to identify cyber threats before they occur Business Benefits • Identifying network anomalies for both external and internal threats near-real time • Expanding the overall capabilities and time to action for the SOC and Security personnel • Reduced false positives • Identification of unknown malicious activities through advanced anomaly detection Our Solution • Our unified cyber security-risk platform — implementing machine-learning to provide a comprehensive cyber-threat defense capability
  8. 8. © 2017 Unisys Corporation. All rights reserved. 88 University Network Application Optimization Business Problem • Extreme network peaks and degradation in availability; unidentified issues causing network failure Business Benefits • Network behavioral models identify high demand peaks and application utilization • Machine Learning helps to provide insights to predict potential network issues before they happen • Optimization of hardware and cloud infrastructure investment to maintain network performance Our Solution • Our network anomaly detection models for applications and machine learning provide real time insights and predict patterns of usage through actionable intelligence
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