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市場調查報告書

IoT安全及詐騙防止的人工智能 (AI)的市場:2016-2021年

Market for Artificial Intelligence in Internet of Things (IoT) Security and Fraud Prevention 2016 - 2021

出版商 Mind Commerce 商品編碼 366644
出版日期 內容資訊 英文 83 Pages
商品交期: 最快1-2個工作天內
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IoT安全及詐騙防止的人工智能 (AI)的市場:2016-2021年 Market for Artificial Intelligence in Internet of Things (IoT) Security and Fraud Prevention 2016 - 2021
出版日期: 2016年08月12日 內容資訊: 英文 83 Pages
簡介

人工智能 (AI) 的IoT用詐騙防止&安全情報解決方案的收益規模,預計2021年達到近15億美元的規模。

本報告提供人工智能 (AI) 的IoT用安全技術的相關調查,IoT的安全上的疑慮,IoT安全的焦點區域,IoT用安全解決方案的開發的課題,IoT用安全解決方案的收益預測,各地區明細,以及主要企業的簡介等彙整。

第1章 簡介

第2章 摘要整理

第3章 概要

  • 網路安全
  • 網路安全上的威脅的衍生影響
  • IoT
  • 一般的IoT安全上的疑慮
  • IoT安全的焦點區域
  • 分散式IoT:霧運算
    • 邊運算
    • 邊運算 vs 簇運算
    • 行動網路邊界運算
    • 霧運算
    • 雲端運算 vs 霧運算
  • 霧運算的固有安全課題

第4章 IoT用安全解決方案

  • IoT用安全解決方案的開發中的課題
    • IoT商務的多廠商性
    • 缺乏標準的安全實踐
    • 現有IoT設備缺乏強大安全性
    • 日益先進化的威脅
    • IoT資料比設備更受擔憂
  • IoT保護的解決方案領域
  • 安全IoT的一般步驟
    • 設備的保護
    • 安全的通訊協議的利用
    • 資料的保障與保護
  • 一般的IoT安全對策
    • 安全策略的整合
    • 行動設備和應用的保護
    • IoT雲端基礎設施的保護
  • IoT安全的課題促進AI需求
    • 霧運算的安全上的疑慮:進化的課題
    • 超越資產保護的重要性:在分析、決策中Ai所扮演的角色

第5章 AI為基礎的IoT安全解決方案的預測

  • 全球市場的預測
  • 各地區的預測
    • 北美
    • 歐洲
    • 亞太地區
    • 中東、非洲
    • 南美

第6章 安全企業

  • ARM Holdings
  • Attivo Networks
  • Bastille
  • Black Duck Software
  • Check Point Software Technologies
  • Cisco Systems
  • Cylance
  • IBM Corporation
  • Infineon Technologies AG
  • Intel Security Group (McAfee)
  • Inside Secure SA
  • Mocana
  • Neustar
  • Overwatch
  • Spirent Security
  • Symantec
  • Trend Micro
  • TrustPoint IT
  • Wedge Networks
  • Wurldtech Security Technologies (GE)

第7章 總論、建議

圖表

目錄

Overview:

Artificial Intelligence (AI) is rapidly becoming integrated into many aspects of communication, applications, content, and commerce. The Internet of Things (IoT) is a particularly important area for AI as a means for safeguarding assets, reducing fraud, and supporting analytics and automated decision making. Mind Commerce estimates that global AI-based IoT anti-fraud and security intelligence solution revenue will reach nearly $1.5B USD by 2021.

This report evaluates that technologies, market opportunities, and outlook for AI-based security in IoT. The report includes analysis of AI in specific IoT deployment scenarios such as Fog Computing architectures. The report provides forecasting for 2016 to 2021.

Key Findings:

  • Intel's acquisition of McAfee was a big mistake
  • Cylance is a key acquisition target for IoT security
  • Cisco is in the best position to capitalize on IoT security
  • APAC anti-fraud and security revenue will reach $459M by 2021
  • Global AI-based IoT security revenue will reach nearly $1.5B USD by 2021

Report Benefits:

  • AI security in IoT security and fraud prevention 2016 - 2021
  • Learn about the relationship of IoT security to IoT Policy Management
  • Understand the architecture, planning, and engineering issues for IoT security
  • Identify opportunities for AI-based IoT security solutions in distributed computing
  • Understand the strategy to lead with IoT security and evolve towards other services

Target Audience:

  • Security companies
  • Wireless device manufacturers
  • Telephony infrastructure providers
  • Computer and semiconductor companies
  • Embedded hardware, software and OS providers
  • Wireless network operators and service providers

Table of Contents

1. Introduction

2. Executive Summary

3. Overview

  • 3.1. Cyber Security
  • 3.2. Ramification of Cyber Security Threats
  • 3.3. Internet of Things
  • 3.4. General IoT Security Concerns
  • 3.5. IoT Security Focus Areas
  • 3.6. Distributed IoT: Fog Computing
    • 3.6.1. Edge Computing
    • 3.6.2. Edge Computing vs. Cluster Computing
    • 3.6.3. Mobile Edge Computing
    • 3.6.4. Fog Computing
    • 3.6.5. Cloud Computing vs. Fog Computing
  • 3.7. Specific Security Concerns with Fog Computing

4. Security Solutions in IoT

  • 4.1. Challenges in Developing Security Solutions for IoT
    • 4.1.1. Multivendor Nature of IoT Business
    • 4.1.2. Lack of Standard Security Practices
    • 4.1.3. Existing IoT Devices lack Robust Security
    • 4.1.4. Security Threats are becoming Increasingly Sophisticated
    • 4.1.5. IoT Data is a Bigger Concern than Equipment
  • 4.2. Solution Areas for Securing IoT
  • 4.3. General Steps to Secure IoT
    • 4.3.1. Securing Device
    • 4.3.2. Using Secure Communication Protocols
    • 4.3.3. Securing and Protecting Data
  • 4.4. General IoT Security Measures
    • 4.4.1. Convergence of IT and OT Security Policies
    • 4.4.2. Securing Mobile Devices and Applications
    • 4.4.3. Securing IoT Cloud Infrastructure
  • 4.5. IoT Security Issues that Drive the Need for AI
    • 4.5.1. Fog Computing Security Concerns: An Evolving Issue
    • 4.5.2. Beyond Safeguarding Assets: The Role of AI in Analytics and Decision Making

5. AI-based IoT Security Solution Forecasts 2016-2021

  • 5.1. Global AI based Security Solutions in IoT Forecasts 2016-2021
  • 5.2. Regional AI based Security Solutions in IoT Forecasts 2016-2021
    • 5.2.1. North America AI based Security Solutions in IoT 2016-2021
    • 5.2.2. Europe AI based Security Solutions in IoT 2016-2021
    • 5.2.3. APAC AI based Security Solutions in IoT 2016-2021
    • 5.2.4. Middle East and Africa AI based Security Solutions in IoT 2016-2021
    • 5.2.5. Latin America AI based Security Solutions in IoT 2016-2021

6. Security Companies Evaluated

  • 6.1. ARM Holdings
  • 6.2. Attivo Networks
  • 6.3. Bastille
  • 6.4. Black Duck Software
  • 6.5. Check Point Software Technologies
  • 6.6. Cisco Systems
  • 6.7. Cylance
  • 6.8. IBM Corporation
  • 6.9. Infineon Technologies AG
  • 6.10. Intel Security Group (McAfee)
  • 6.11. Inside Secure SA
  • 6.12. Mocana
  • 6.13. Neustar
  • 6.14. Overwatch
  • 6.15. Spirent Security
  • 6.16. Symantec
  • 6.17. Trend Micro
  • 6.18. TrustPoint IT
  • 6.19. Wedge Networks
  • 6.20. Wurldtech Security Technologies (GE)

7. Conclusions and Recommendations

Figures

  • Figure 1: Fog Computing
  • Figure 2: Fog Computing and Cloud Architecture
  • Figure 2: Security in Fog Computing

Tables

  • Table 1: Cyber Crime in Top 15 Countries
  • Table 2: Cyber Crime by Category
  • Table 3: IoT Security Challenges and Solution Areas
  • Table 4: Global AI based Security Market 2016-2021
  • Table 5: North America AI based Security Market 2016-2021
  • Table 6: Europe AI based Security Market 2016-2021
  • Table 7: APAC AI based Security Market 2016-2021
  • Table 8: ME & Africa AI based Security Market 2016-2021
  • Table 9: Latin America AI based Security Market 2016-2021
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