Demystifying Intelligent Multimode Security Systems: An Edge-To-Cloud Cybersecurity Solutions Guide
暫譯: 揭開智能多模式安全系統的神秘面紗：邊緣到雲端的網路安全解決方案指南
Booth, Jody, Metz, Werner, Cheruvu, Sunil
相關主題
商品描述
Use this practical guide to understand the concepts behind Intelligent Multi-modal Security Systems (IMSS) and how to implement security within an IMSS system to improve the robustness of the devices and of the end-to-end solution.
There are nearly half a million active IMSS cameras globally, with over 100 million added annually. These cameras are used across enterprises (companies, traffic monitoring, driver enforcement, etc.), in peoples' homes, on mobile devices (drones, on-vehicle, etc.), and are worn on the body.
IMSS systems with a camera and network video recorder for storage are becoming the normal infrastructure for capturing, storing, and transmitting video content (sometimes up to 100 streams) in a secure manner and while protecting privacy.
Military, aerospace, and government entities are also embracing digital security and surveillance. IMSS content serves as evidence in courts of law.
Security within all of these types of IMSS systems needs to be bolstered by leveraging Intel hardware and software as the last line of defense, and this book provides you with best practices and solutions for maximizing security in your system implementation.
What You Will Learn
- Review the relevant technologies in a surveillance system
- Define and dissect the data pipeline with a focus on key criteria and understand the mapping of this pipeline to Intel hardware blocks
- Optimize the partition and future-proof it with security and manageability
- Understand threat modeling terminology, the assets pertinent to DSS, and emerging threats, and learn how to mitigate these threats using Intel hardware and software
- Understand the unique risks and threats to the intelligence in IMSS (machine learning training and inferencing, regulations, and standards) and explore the solution space for mitigations to these threats
- Sample applications illustrate how to design in security for several types of IMSS.--
- Explore ways to keep both yourself and your systems up to date in a rapidly changing technology and threat environment
Who This Book Is For
Surveillance system designers, integrators, and consultants; professional systems, hardware, and software designers who design, recommend, or integrate surveillance systems; security system integrators; video analytics engineers; agencies that write RFPs and/or RFIs; government, police, and security agencies; and corporate security divisions
商品描述(中文翻譯)
使用這本實用指南來理解智能多模態安全系統（Intelligent Multi-modal Security Systems, IMSS）背後的概念，以及如何在IMSS系統中實施安全性，以提高設備和端到端解決方案的穩健性。
全球目前有近五十萬台活躍的IMSS攝影機，每年新增超過一億台。這些攝影機被廣泛應用於企業（公司、交通監控、駕駛執法等）、家庭、移動設備（無人機、車載設備等），以及穿戴在身上。
配備攝影機和網絡視頻錄影機進行存儲的IMSS系統，正成為捕捉、存儲和安全傳輸視頻內容（有時多達100個串流）的正常基礎設施，同時保護隱私。
軍事、航空航天和政府機構也在擁抱數位安全和監控。IMSS內容在法庭上作為證據使用。
所有這些類型的IMSS系統中的安全性需要通過利用Intel硬體和軟體作為最後的防線來加強，本書為您提供最佳實踐和解決方案，以最大化系統實施中的安全性。
您將學到什麼
- 回顧監控系統中的相關技術
- 定義並剖析數據管道，重點關注關鍵標準，並理解該管道與Intel硬體模塊的映射
- 優化分區並以安全性和可管理性未來證明其有效性
- 理解威脅建模術語、與DSS相關的資產及新興威脅，並學習如何利用Intel硬體和軟體來減輕這些威脅
- 理解IMSS中智能的獨特風險和威脅（機器學習訓練和推斷、法規和標準），並探索減輕這些威脅的解決方案空間
- 範例應用展示如何為多種類型的IMSS設計安全性。
- 探索在快速變化的技術和威脅環境中保持自己和系統更新的方法
本書適合誰
監控系統設計師、整合商和顧問；專業系統、硬體和軟體設計師，設計、推薦或整合監控系統；安全系統整合商；視頻分析工程師；撰寫RFP和/或RFI的機構；政府、警察和安全機構；以及企業安全部門。
作者簡介
Lawrence Booth has been a systems architect and a systems-on-silicon architect focused on imaging and media-related processing for more than 30 years. After three years in secure video gateway cybersecurity architecture, he joined Intel's Internet of Things group, returning to his greatest interest--vision systems.
Dr. Werner Metz is a system architect with over 30 years of experience in architecting, developing, and implementing digital imaging systems. He has contributed at the level of image sensor architecture and design, conventional and deep learning imaging algorithms, digital image processor architecture, and analog image signal processor design. He has architected a wide range of consumer, commercial, and industrial imaging systems spanning visible, IR, thermal, and UV wavelengths for both human viewing and computer vision. He is currently responsible for the E2E video architecture at Intel, spanning camera to gateway to data center, with an emphasis on edge devices.
Sunil Cheruvu is Chief IoT Security Architect in the Internet of Things group at Intel Corporation. He has over 27 years of experience in architecting complex systems involving HW/FW/SW on multiple architectures, including Intel, ARM, and MIPS/PowerPC. At Intel, he leads security across all of the IoT vertical domains and he was the Content Protection and Trusted Data Path System Architect (end-to-end premium content protection within an SoC). He is the subject matter expert for IoT security across Intel and outside of Intel. At Microsoft, as a SW design engineer, he was the tech lead for vehicle bus networking stacks, threat modeling, and mitigations in the Windows Mobile for Automotive (WMfA) platform. At 3com and Conexant, he implemented the code for baseline privacy security in DOCSIS-compliant cable modems.
作者簡介(中文翻譯)
Lawrence Booth 在影像和媒體相關處理方面擔任系統架構師和矽晶片系統架構師已有超過 30 年的經驗。在從事三年的安全視頻閘道網路安全架構後，他加入了英特爾的物聯網團隊，回到了他最感興趣的領域——視覺系統。
Dr. Werner Metz 是一位系統架構師，擁有超過 30 年的數位影像系統架構、開發和實施經驗。他在影像感測器架構和設計、傳統及深度學習影像演算法、數位影像處理器架構以及類比影像信號處理器設計方面做出了貢獻。他設計了各種消費性、商業及工業影像系統，涵蓋可見光、紅外線、熱成像及紫外線波長，適用於人類觀察和電腦視覺。他目前負責英特爾的端到端視頻架構，涵蓋從攝影機到閘道再到數據中心，並強調邊緣設備。
Sunil Cheruvu 是英特爾公司物聯網團隊的首席物聯網安全架構師。他在架構涉及多種架構的硬體/韌體/軟體的複雜系統方面擁有超過 27 年的經驗，包括英特爾、ARM 和 MIPS/PowerPC。在英特爾，他負責所有物聯網垂直領域的安全性，並曾擔任內容保護和受信數據通道系統架構師（在 SoC 中的端到端高級內容保護）。他是英特爾內外物聯網安全的主題專家。在微軟擔任軟體設計工程師時，他是 Windows Mobile for Automotive (WMfA) 平台上車輛總線網路堆疊、威脅建模和緩解措施的技術負責人。在 3com 和 Conexant，他實現了符合 DOCSIS 標準的有線調製解調器的基線隱私安全代碼。
