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偽情報対策(ディープフェイク・フェイクニュース)ソリューション市場(2020年~2026年)

Counter Misinformation (DeepFake & Fake News) Solutions Market: 2020-2026

出版日: | 発行: Homeland Security Research Corporation (HSRC) | ページ情報: 英文 136 Pages; 99 Tables & Figures | 納期: 即日から翌営業日

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偽情報対策(ディープフェイク・フェイクニュース)ソリューション市場(2020年~2026年)
出版日: 2020年12月30日
発行: Homeland Security Research Corporation (HSRC)
ページ情報: 英文 136 Pages; 99 Tables & Figures
納期: 即日から翌営業日
  • 全表示
  • 概要
  • 目次
概要

過去1世紀の間、偽情報を拡散のための報道機関やソーシャルメディアプラットフォームの利用が広まり、フェイクニュースは重大な問題となりました。特に政治的、経済的、社会的環境におけるフェイクニュースの悪影響は増大しており、これらのフェイクニュースの記事をほぼリアルタイムで検出および特定する必要性が強調されています。

諜報機関、法執行機関、およびその他の政府機関は、偽情報戦がもたらす脅威に取り組む上で積極的な役割を果たしており、フェイクニュースやディープフェイクメディアの検出・対策可能なテクノロジーの予算を増やしています。

ディープフェイク検証ツールをすべての人が利用できるようにする必要性などから、同市場の予測期間中における急速な成長が予測されています。ただし、この技術は開発の初期段階にあり、開発者はツールを広くリリースする前に、改善およびハッカーから保護する必要があります。

当レポートは、世界の偽情報対策(ディープフェイク・フェイクニュース)ソリューション市場について調査しており、市場規模や予測、成長および抑制要因、規制の枠組み、テクノロジーやソリューション、地域別の市場分析、主要企業のプロファイルなどの情報を提供しています。

目次

第1章 エグゼクティブサマリー

  • 主な調査結果と結論
  • 市場力学と機会
  • 市場規模:評価と予測(2020-2026)
  • 市場力学(2020-2026)
  • 市場の内訳(2020-2026)

第2章 国土安全保障、公共安全および国家安全保障市場の背景と評価における偽情報

  • 偽情報の定義と背景
  • フェイクニュースの定義と背景
  • ディープフェイク定義と背景
  • フェイクニュースとディープフェイクの経済的損害

第3章 国土安全保障、公共安全および国家安全保障市場の背景と評価における偽情報対策

  • カウンターの偽情報の背景
  • 偽情報対策市場:成長要因と抑制要因
    • 偽情報対策市場の推進要因
    • 偽情報対策市場の抑制要因
  • 国土安全保障、公共安全、および国家安全保障市場の組織図における偽情報対策
  • 国土安全保障、公共安全、および国家安全保障市場の推計・予測における偽情報対策

第4章 偽情報対策:国の規制の枠組み

第5章 国土安全保障、公共安全、国家安全保障における各偽情報対策プロジェクトとプログラム

第6章 世界のセキュリティの懸念と評価

  • 世界のリスク(2020):地域の認識
  • 北米:国土安全保障および公共安全市場の成長要因
  • サイバー攻撃
  • データ詐欺または盗難
  • テロの脅威
  • 欧州:国土安全保障および公共安全市場の成長要因
  • サイバー攻撃
  • 資産バブル
  • 州間紛争
  • テロ資金調達
  • アジア太平洋:国土安全保障および公共安全市場の成長要因
  • 水危機
  • テロ攻撃
  • 人為的な環境災害
  • 自然災害
  • サイバー攻撃
  • 州間紛争
  • 中東・アフリカ:国土安全保障および公共安全市場の成長要因
  • 失業または不完全雇用
  • 財政危機
  • エネルギー価格ショック
  • ラテンアメリカとカリブ海地域:国土安全保障および公共安全市場の成長要因
  • 国家統治の失敗
  • 経済問題
  • 主なインフラストラクチャの障害
  • COVID-19パンデミックの背景と評価
  • 北米:COVID-19評価
  • 欧州:COVID-19評価
  • ラテンアメリカ:COVID-19評価
  • アジア太平洋:COVID-19評価
  • 中東・アフリカ:COVID-19評価

第7章 国土安全保障、公安、および国家安全保障機関の背景

第8章 データの急増

第9章 データソースのタイプ

  • パッシブデータソース
  • アクティブデータソース
  • データソース
    • OSINT(ソーシャルメディアとWeb)

第10章 偽情報キャンペーンによって生成される脅威

  • 選挙運動と政治
  • 金融詐欺
  • 公衆衛生
  • なりすまし
  • サイバー対応の犯罪
  • リベンジポルノ・セクストレーション

第11章 テクノロジー

  • 関連市場(2020-2026)
  • 市場分析(2020-2026)
  • 市場力学(2020-2026)
  • 市場の内訳(2020-2026)
  • 偽情報対策技術の背景
  • 偽情報対策テクノロジーイネーブラーとアプリケーション
    • AIと機械学習
    • 自然言語処理(NLP)
  • ボットネットワーク
    • ボットネットワークとは
    • ボットネットワーク検出ツール
  • 偽情報対策テクノロジータイプとソリューション
    • フェイクニュース検出ソリューション
    • ディープフェイク検出ソリューション
    • 市場規模:評価と予測(2020-2026)
    • 市場力学(2020-2026)
    • 市場の内訳(2020-2026)

第12章 垂直市場

  • 関連市場(2020-2026)
  • 市場分析(2020-2026)
  • 市場力学(2020-2026)
  • 市場の内訳(2020-2026)
  • 政府情報機関
  • LEAとファーストレスポンダー
  • ファイナンシャルインテリジェンスと不正検出
  • サイバーセキュリティ機関
  • 軍事および国防情報
  • 商業著作権保護

第13章 地域市場

  • 北米市場
  • 欧州、中東・アフリカ(EMEA)市場
  • アジア太平洋市場

第14章 主要ベンダー

  • ソーシャルメディアプラットフォームのコングロマリット偽情報検出イニシアチブ
  • Cheq
  • Cyabra
  • Falso Tech
  • Sensity
  • Microsoft
  • Axon
  • Logically
  • Datalytics24
  • Wordproof
  • Truepic
  • Right of Reply
  • Factmata
  • Digital Fingerprints
  • Trueinchain
  • Fabula AI (a Twitter company)
  • Shieldsquare
  • Imperva
  • Fastly

第15章 免責事項と著作権

目次

For the past century Fake News has become a significant problem, as exploiting news outlets and social media platforms to disseminate misinformation to influence individuals' actions has become widespread. The negative impact of Fake News, especially within the political, economic, and social environments is increasing, emphasizing the need to detect and identify these Fake News stories in near real-time. Furthermore, the latest trend of using Artificial Intelligence (AI) to create fake videos, known as "DeepFakes" or "FakeNews 2.0", is a fast-growing phenomenon creating major concerns. AI technology enables, basically anyone, to create a fake video that shows a person or persons performing an action at an event that never occurred. Although DeepFakes are not as prevalent and widespread as Fake News articles, they are increasing in popularity and have a much greater effect on the general population. In addition, the sophistication behind the creation of DeepFake videos increases the difficulty of identifying and detecting them, making them a much more effective and destructive tool for perpetrators.

As the usage and threat of DeepFakes and Fake News intensifies, so do efforts to develop new detection methods, resulting in the next wave of (mis)information warfare. The proliferation of technology, specifically Artificial Intelligence, allow wide scale and easy to use solutions to create synthetic media that seems very real, either in video, photos, or text. In combination with networks of fake profiles, bot networks and smart utilization of social media, the attackers have many ways to influence either the public or specific individuals. As media and technology are now being used for cyber terrorism, criminal activity, espionage and military warfare, the new age of information warfare threatens democracies worldwide, pushing governments to combat this threat with large investments.

Intelligence, Law Enforcement, and other Governmental agencies are taking active roles in tackling the threat that (mis)information warfare poses and are spending growing budgets on technology that can detect and counter Fake News and DeepFake media.

The Counter Deepfake and Counter Fake News Software Solutions Market report is the first report to cover this up and coming market, focused on detection and mitigation solutions for Fake News and DeepFakes:

  • Fake News - the deliberate creation of false reality to influence public perception.
  • DeepFake - manipulated videos or audio produced by AI, that yield fabricated images and sounds that appear to be real.

In many cases the two are used simultaneously, however each one requires different tools and methods to detect and mitigate. Currently, most of the market spending goes towards the detection and monitoring part of the Information Warfare, while a smaller portion is invested towards digital forensics, trying to trace the source, after the damage has been done.

There are two major categories of DeepFake detection tools:

  • Pattern Analysis - looking and analyzing the behavior of people in the videos, learning the patterns, from hand gestures to pauses in speech, and comparing it to real life patterns. This approach has the advantage of possibly working even if the video quality itself is essentially perfect.
  • Quality of Video Analysis - analyzing the differences between deepfakes and real videos. Most deepfake videos are created by merging individually generated frames into videos. By analyzing the essential data from the faces in individual frames of a video and then tracking them through sets of concurrent frames one is able to detect inconsistencies in the flow of the information from one frame to another. This can also be used for face audio detection.

At the end of the day, it may be that both types of DeepFake detection methods will be needed in order to mitigate this potential threat.

Fake News are disseminated via networks of fake profiles, bot networks and smart utilization of social media, therefore, most tools developed and used to detect fake news are geared towards finding, analyzing and stopping these networks and bots. These tools are a mix of OSINT and Cyber technologies.

The counter DeepFake and counter Fake News software market forecast report presents for each submarket 2019 data and projects the 2020-2026 market. We address the "money trail" - each dollar spent - via the following 3 orthogonal market segments:

By Type of misinformation:

  • 1. Fake News
  • 2. DeepFake

By End User:

  • 1. Police & Law Enforcement
  • 2. Intelligence Organizations
  • 3. Military
  • 4. Other Government Organizations
  • 5. Commercial Businesses
  • 6. Consumers

By Regional Markets:

  • 1. North America
  • 2. Europe, Middle East & Africa (EMEA)
  • 3. Asia Pacific

As most of the misinformation activity and content dissemination is done on social media platforms, the report covers the activity of tech giants to tackle this threat over their platforms and beyond. Facebook, Twitter, Microsoft, Youtube and other leading content platforms are investing time and money to better understand and detect deepfakes to make sure their platforms are not misused by criminals and state-owned operators. However, these efforts alone will not be enough and other institutions will have to take a more prominent role by allocating larger budgets to purchase or develop capabilities to mitigate the risk. In addition to detecting these fakes, journalists and the social media platforms also need to figure out how best to warn people about deepfakes when they are detected to minimize the damage done.

Such as in most tech heavily markets, end users are debating whether to work with an external vendor or to rely on internal developed capabilities as well as existing OSINT monitoring tools re-directed to a dedicated team. The report contains a detailed list and short profile of the companies that provide solutions for counter DeepFake and FakeNews monitoring and detection. Many of these companies are startups such as Cheq, Metafact, Cyabra, Falso Tech, Sensity, and others. In addition, large and mature corporations are also active in the market, some of them via M&A activities and other are developing solutions internally, such players include Axon, Microsoft, Facebook, Twitter and others.

These companies are leveraging several high-end technologies and methods to tackle this threat, such as:

  • AI analytics that can identify synthetic media
  • Digital authentication solutions
  • Content and social media monitoring tools (OSINT)
  • Fake profiles detectors
  • Fact checking tools
  • Related cybercrime activity

In addition to technological solutions, regulatory frameworks are also being put forth by Judicial systems across the globe as a method to deal with this threat. However, there are many issues regarding personal rights and the freedom of speech that make it hard to fight this kind of campaigns by only using the law.

Questions answered in this market report include:

  • What will be the counter deepfake and counter fake news software market size in 2019-2025? What will the relevant trends be during that time?
  • What will be the deepfake detection software market size in 2019-2025?
  • What will be the fake news detection software market size in 2019-2025?
  • Which submarkets in this field provide attractive business opportunities?
  • Which regions are expected to invest most in these capabilities?
  • Which end users are expected to invest most in these capabilities?
  • What are the market drivers and inhibitors?
  • Who are the prominent vendors in the market?
  • What type of regulations are countries implementing to fight the threats posed by deepfake and fake news activities?

Ideally, a deepfake verification tool should be available to everyone. However, this technology is in the early stages of development. Furthermore, developers need to improve the tools and protect them against hackers before releasing them broadly. Therefore, HSRC estimates this market will grow rapidly during the forecast period.

Table of Contents

1 Executive Summary

  • 1.1 Major Findings & Conclusions
  • 1.2 Market Dynamics & Opportunities
  • 1.3 Market Size - Assessment and Forecast - 2020-2026
  • 1.4 Market Dynamics 2020-2026
  • 1.5 Market Breakdown 2020-2026

2 Misinformation in Homeland Security, Public Safety and National Security Market Background & Assessment

  • 2.1 Misinformation Definition & Background
    • 2.1.1 Fake News Definition & Background
    • 2.1.2 DeepFake Definition & Background
    • 2.1.3 Fake News & DeepFake Economic Damages

3 Counter Misinformation in Homeland Security, Public Safety and National Security Market Background & Assessment

  • 3.1 Counter Misinformation Background
  • 3.2 Counter Misinformation Industry: SWOT Analysis
    • 3.2.1 Strengths
    • 3.2.2 Weaknesses
    • 3.2.3 Opportunities
    • 3.2.4 Threats
  • 3.3 Counter Misinformation Market Drivers
  • 3.4 Counter Misinformation Market Inhibitors
  • 3.5 Counter Misinformation in Homeland Security, Public Safety, and National Security Market Organogram
  • 3.6 Counter Misinformation in Homeland Security, Public Safety, and National Security Market Estimations and Forecast

4 Global Security Concerns & Assessment

  • 4.1 Global Risks 2020: A Regional Perceptive
  • 4.2 North America Homeland Security & Public Safety Market Drivers
    • 4.2.1 Cyber Attacks
    • 4.2.2 Data Fraud or Theft
    • 4.2.3 Terrorism Threat
  • 4.3 Europe Homeland Security & Public Safety Market Drivers
    • 4.3.1 Cyberattacks
    • 4.3.2 Assets bubble
    • 4.3.3 Interstate conflict
  • 4.4 APAC Homeland Security & Public Safety Market Drivers
    • 4.4.1 Water Crises
    • 4.4.2 Terrorist attacks
    • 4.4.3 Manmade environmental catastrophes
    • 4.4.4 Natural catastrophes
    • 4.4.5 Cyberattacks
    • 4.4.6 Interstate conflict
  • 4.5 Middle East and Africa Homeland Security & Public Safety Market Drivers
    • 4.5.1 Unemployment or underemployment
    • 4.5.2 Fiscal crises
    • 4.5.3 Energy price shock
  • 4.6 Latin America and the Caribbean Homeland Security & Public Safety Market Drivers
    • 4.6.1 Failure of national governance
    • 4.6.2 Economic issues
    • 4.6.3 Failure of critical infrastructure
  • 4.7 COVID-19 Pandemic Background & Assessment
    • 4.7.1 North America COVID-19 Assessment
    • 4.7.2 Europe COVID-19 Assessment
    • 4.7.3 LATAM COVID-19 Assessment
    • 4.7.4 APAC COVID-19 Assessment
    • 4.7.5 Middle East & Africa COVID-19 Assessment

5 Homeland Security, Public Safety, and National Security Agencies Background

6 Proliferation of Data

7 Type of Data Sources

  • 7.1 Passive Data Sources
  • 7.2 Active Data Sources
  • 7.3 Data Sources
    • 7.3.1 OSINT (Social Media and Web)
      • 7.3.1.1 Social Media Sources
      • 7.3.1.2 Leading Social Media Platforms

8 Threats Generated by Misinformation Campaigns

  • 8.1 Election Campaigns and Politics
  • 8.2 Financial Frauds
  • 8.3 Public health
  • 8.4 Personality Theft
  • 8.5 Revenge Porn

9 Technology

  • 9.1 Counter Misinformation Technology Background
  • 9.2 Counter Misinformation Technology Enablers
    • 9.2.1 AI & Machine Learning
    • 9.2.2 Machine Learning Methods
    • 9.2.3 Deep Machine Learning
  • 9.3 Counter Misinformation Technology Types & Applications
    • 9.3.1 Fake News Detection Solutions
    • 9.3.2 DeepFake Detection Solutions
    • 9.3.3 Natural Language Processing (NLP)
    • 9.3.4 Natural Language Processing Components
    • 9.3.5 Natural Language Processing Application Types
      • 9.3.5.1 Document Translation
      • 9.3.5.2 Text Classification and Categorization
      • 9.3.5.3 Enlarge the Data of Cyber Security
      • 9.3.5.4 Speech Recognition & Machine Hearing
    • 9.3.6 Machine Vision
      • 9.3.6.1 Applications Types

10 Vertical Markets

  • 10.1 Consolidated Market 2020-2026
  • 10.2 Market Analysis 2020-2026
  • 10.3 Market Dynamics 2020-2026
  • 10.4 Market Breakdown 2020-2026
  • 10.5 Government Intelligence Agencies
    • 10.5.1 Use Cases
    • 10.5.2 Market Size - Assessment and Forecast - 2020-2026
    • 10.5.3 Market Dynamics 2020-2026
    • 10.5.4 Market Breakdown 2020-2026
  • 10.6 LEAs & First Responders
    • 10.6.1 Use Cases
    • 10.6.2 Market Size - Assessment and Forecast - 2020-2026
    • 10.6.3 Market Dynamics 2020-2026
    • 10.6.4 Market Breakdown 2020-2026
  • 10.7 Financial Intelligence & Fraud Detection
    • 10.7.1 Use Cases
    • 10.7.2 Market Size - Assessment and Forecast - 2020-2026
    • 10.7.3 Market Dynamics 2020-2026
    • 10.7.4 Market Breakdown 2020-2026
  • 10.8 Cyber Security Agencies
    • 10.8.1 Use Cases
    • 10.8.2 Market Size - Assessment and Forecast - 2020-2026
    • 10.8.3 Market Dynamics 2020-2026
    • 10.8.4 Market Breakdown 2020-2026
  • 10.9 Military & Defense Intelligence
    • 10.9.1 Use Cases
    • 10.9.2 Market Size - Assessment and Forecast - 2020-2026
    • 10.9.3 Market Dynamics 2020-2026
    • 10.9.4 Market Breakdown 2020-2026
  • 10.10 Commercial Copyrights Protection
    • 10.10.1 Use Cases
    • 10.10.2 Market Size - Assessment and Forecast - 2020-2026
    • 10.10.3 Market Dynamics 2020-2026
    • 10.10.4 Market Breakdown 2020-2026

11 Regional Markets

  • 11.1 North America Market Background
    • 11.1.1 Market Size - Assessment and Forecast - 2020-2026
    • 11.1.2 Market Dynamics 2020-2026
    • 11.1.3 Market Breakdown 2020-2026
  • 11.2 Europe, Middle East & Africa (EMEA) Market Background
    • 11.2.1 Europe
    • 11.2.2 Middle East
    • 11.2.3 Africa
    • 11.2.4 Market Size - Assessment and Forecast - 2020-2026
    • 11.2.5 Market Dynamics 2020-2026
    • 11.2.6 Market Breakdown 2020-2026
  • 11.3 APAC Market Background
    • 11.3.1 Market Size - Assessment and Forecast - 2020-2026
    • 11.3.2 Market Dynamics 2020-2026
    • 11.3.3 Market Breakdown 2020-2026

12 Select Counter Misinformation Projects and Programs in Homeland Security, Public Safety & National Security

13 Leading Vendors

  • 13.1 Social Media Platform Conglomarates
    • 13.1.1 Misinformation Detection Solutions
  • 13.2 Accelerators Funding Counter Misinformation Startups
  • 13.3 Cheq
    • 13.3.1 Company Profile
    • 13.3.2 Misinformation Detection Solutions
  • 13.4 Cyabra
    • 13.4.1 Company Profile
    • 13.4.2 Misinformation Detection Solutions
  • 13.5 Falso Tech
    • 13.5.1 Company Profile
    • 13.5.2 Misinformation Detection Solutions
  • 13.6 Sensity
    • 13.6.1 Company Profile
    • 13.6.2 Misinformation Detection Solutions
  • 13.7 Microsoft
    • 13.7.1 Company profile
    • 13.7.2 Misinformation Detection Solutions
  • 13.8 Axon
    • 13.8.1 Company profile
    • 13.8.2 Misinformation Detection Solutions
  • 13.9 Logically
    • 13.9.1 Company profile
    • 13.9.2 Misinformation Detection Solutions
  • 13.10 Datalytics24
    • 13.10.1 Company profile
    • 13.10.2 Misinformation Detection Solutions
  • 13.11 Wordproof
    • 13.11.1 Company profile
    • 13.11.2 Misinformation Detection Solutions
  • 13.12 Truepic
    • 13.12.1 Company profile
    • 13.12.2 Misinformation Detection Solutions

14 Disclaimer & Copyright

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