用于改善隐私和安全计算的各种技术
市场调查报告书
商品编码
1351269

用于改善隐私和安全计算的各种技术

Privacy-Enhancing & Secure Computing Technologies

出版日期: | 出版商: ABI Research | 英文 42 Pages | 商品交期: 最快1-2个工作天内

价格
简介目录

本报告考察了隐私增强和安全计算的各种技术的市场,包括各种技术和解决方案的概述、市场影响因素和市场机会的分析以及主要供应商的分析。

报告的优点:

  • 了解用于保护隐私和机密性的各种安全技术的商业演变
  • 确定各种隐私增强技术 (PET) 和机密计算 (CC) 成熟的现实时间表
  • 确定 PET 和 CC 的目标市场和商业模式

关键问题的答案:

  • 使用哪些安全技术来确保机密性和隐私?
  • 哪些供应商提供 PET 和 CC 服务以及他们如何提供这些服务?
  • PET 和 CC 的市场机会有哪些?

研究亮点:

  • 目前市面上可用的 PET 和 CC 解决方案的概要视图
  • PET 与 CC 供应商生态系概览
  • 各种 PET 和 CC 技术的 TAM

目录

  • 技术概述
  • 多方计算
  • 同态加密
  • 差异隐私
  • 零知识证明
  • 综合数据
  • 联邦学习
  • TEE(可信任执行环境)
  • CC(机密计算)
  • TPM(可信任平台模组)
  • HSM(硬体安全模组)
  • 加密金钥管理与公钥基础设施
  • 分散式帐本技术
  • 分析
  • 摘要
简介目录
Product Code: PT-2289

Actionable Benefits:

  • Understand commercial developments of different security technologies being leveraged for privacy and confidentiality
  • Determine a realistic timeline for maturity of various Privacy Enhancing Technologies (PETs) and Confidential Computing (CC).
  • Identify target markets and business models for delivery of PET and CC.

Critical Questions Answered:

  • What types of security technologies are being leveraged for confidentiality and privacy?
  • Which vendors are offering PET and CC services and how are they delivering them?
  • What is the market opportunity for PET and CC?

Research Highlights:

  • High-level view of PET and CC solutions currently available on the market.
  • PET and CC vendor ecosystem snapshot.
  • Total Addressable Market (TAM) for various PET and CC technologies.

Who Should Read This?

  • Artificial Intelligence (AI)/Machine Learning (ML) developers to understand how to implement privacy and confidentiality.
  • Silicon Intellectual Property (IP) and semiconductor manufacturers to develop appropriate underlying secure hardware.
  • PET and CC vendors to forge partnerships for integration and interoperability.
  • Regulators and standards development organizations in order to assess technology specification maturity.

Table of Contents

  • Introduction
  • Technology Overview
  • Multi-Party Computation
  • Homomorphic Encryption
  • Differential Privacy
  • Zero-Knowledge Proof
  • Synthetic Data
  • Federated Learning
  • Trusted Execution Environment
  • Confidential Computing
  • Trusted Platform Module
  • Hardware Security Module
  • Encryption Key Management & Public Key Infrastructure
  • Distributed Ledger Technology
  • Analysis
  • Summary