Gartner Research

Competitive Landscape: Distributed Deception Platforms, 2016

Published: 04 August 2016

ID: G00310123

Analyst(s): Lawrence Pingree

Summary

Distributed deception platforms are now a viable option for enhancing detection within enterprise security programs. Product marketing managers must understand the competitive positioning of their products and crucial market dynamics in order to compete effectively in the DDP market.

Table Of Contents

Analysis

  • Market Definition
    • DDP Features
  • Market Drivers
    • Technological Developments and a Shift Toward Enhancing Detection by Security Programs Drive Greater Interest and Value in DDP Solutions
    • Buyers Understand That "Trapping" the Attacker Moves the Needle in Their Favor
    • Advanced-Threat Actors Continue to Evade Detection Technologies
  • Market Inhibitors
    • The Preventive-Versus-Detective-Technology Debate Still Rages On
    • Many Organizations Often Have "Low-Hanging Fruit" and a Compliance Focus
    • Lack of Incident Response and Information Security Resources
  • Competitive Situation and Trends
  • Current Trends
    • Mapping the Kill Chain Phases
    • Providers Continue Adding Decoy Services (Such as Supervisory Control and Data Acquisition [SCADA], Internet of Things [IoT] Protocols and Interactive Services)
    • Sales and Marketing Efforts Focus on Education About Deception and Enhancing Enterprise Detection With Distributed Decoys
  • Emerging Trends
    • Security Ecosystem Integrations Expanding
    • Leading DDP Providers Focusing on Operationalizing Aspects of Deployments to Deliver Deception Operations (Actively Managed Threat Deceptions)
    • Counterintelligence Support
    • Expanding Support for Public/Private Cloud and the IoT
  • Market Players
  • The Future of Competition
  • Competitive Profiles
    • Attivo Networks
    • Cymmetria
    • GuardiCore
    • illusive networks
    • Imperva
    • Javelin Networks
    • Smokescreen
    • TopSpin
    • TrapX
  • Other Notable DDP Providers
  • References and Methodology
  • Definitions

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