This open access book. 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
Conditions of Use
This book is licensed under a Creative Commons License (CC BY). You can download the ebook Demystifying Intelligent Multimode Security Systems for free.
- Title
- Demystifying Intelligent Multimode Security Systems
- Subtitle
- An Edge-to-Cloud Cybersecurity Solutions Guide
- Publisher
- Apress
- Author(s)
- Anahit Tarkhanyan, Jody Booth, Sunil Cheruvu, Werner Metz
- Published
- 2023-07-28
- Edition
- 1
- Format
- eBook (pdf, epub, mobi)
- Pages
- 299
- Language
- English
- ISBN-10
- 1484282965
- ISBN-13
- 9781484282977
- License
- CC BY
- Book Homepage
- Free eBook, Errata, Code, Solutions, etc.
Table of Contents About the Authors About the Technical Reviewer About the Intel Reviewers Acknowledgements Legal Notices and Disclaimers Abstract Chapter 1: Introduction and Overview Why You Should Read This Introduction and What to Expect …Because That’s Where the Money Is Cogito Ergo (Multiply and) Sum – Artificial Intelligence What This Means for You As a Security and Safety Professional Every Journey Begins with a Single Step – Maya Angelou Chapter 2: IMSS System Level View Summary History of Intelligent Multi-modal Security System Solutions Video 1.0 – Analog Video Technology Video 2.0 – IP-Connected Cameras and Video Recorders Current Intelligent Multi-modal Security Systems Solutions Video 3.0 – Intelligent Cameras and Video Recorders Bandwidth and Connectivity Cost/Power/Performance Ease of Development, Deployment, and Scaling Next-Generation Intelligent Multi-modal Security Systems Solutions Impact of Memory and Compute Improvements Design for Privacy Personal data Processing Protection Protection Security guidelines Principle IMSS System Components IMSS System View Smart IP Camera Network Video Recorder with Analytics Compute resources – General to Specialized, Key Performance Indicators (KPIs) Edge Server Operations Data Center Server End-to-End Security Cost Overheads for Security Confidentiality, Integrity, Availability Secure Data Storage Conclusion Chapter 3: Architecting and E2E IMSS Pipeline What Does It Take? IMSS Data Pipeline Terminology Defining the Data Pipeline – Key Concepts Desired Actions and Outcomes Three Basic Tasks – Storage, Display, and Analytics Basic Datatypes and Relationships – Sensed Data, Algorithms, and Metadata Evolution of IMSS Systems, or a Brief History of Crime IMSS 1.0 In the Beginning, There Was Analog… IMSS 2.0 …And Then There Was Digital… IMSS 3.0 …Better Together – Network Effects… Breaking Up Is Hard to Do…Packets Everywhere… Learning to Share… Hook Me Up…Let’s Get Together Data Rich, Information Sparse… IMSS 4.0…If I Only Had a Brain… Classical CV Techniques – Algorithms First, Then Test against Data Deep Learning – Data First, Then Create Algorithms Convolutional Neural Networks and Filters…Go Forth and Multiply…and Multiply Teaching a Network to Learn… Types of Neural Networks: Detection and Classification A Pragmatic Approach to Deep Learning …Key Performance Indicators (KPIs) One Size Doesn’t Fit All… IMSS 4.0: From Data to Information Information Rich, Target Rich… Task Graph – Describing the Use Case/Workload – Overview Sensors and Cameras – Sampling the Scene in Space, Time, and Spectra Converting Sampled Data to Video Transporting Data – Getting Safely from Point A to Point B NVR/Video Analytic Nodes – Making Sense of The World Storing Data – Data at Rest Converting Reconstructed Data to Information – Inferencing and Classification Humans Consumption – Display Machine Consumption – Algorithms, Databases, and Metadata Video Analytic Accelerators – Optimized Analytics Conclusions and Summary Chapter 4: Securing the IMSS Assets Why Should You Think About Threats? Summary Threat Modeling Threat Modeling Terminology Threat Taxonomy Basic Types of Software Threats Basic Types of Hardware Threats Insider, Supply Chain, and Authorized Agent Threats Side Channel Attack Threats Threat Analysis Methods Basic Concepts Common Criteria for Information Technology Security Evaluation STRIDE IMSS Assets Value of Assets Foundational Assets Data Assets Application Assets Threats Attackonomics Current Threats Vulnerabilities Malware Trends and Emerging Threats Designing a Secure Platform Using Intel Technologies Root of Trust (RoT) Secure IDs Provisioning the Device – FIDO Onboarding Secure Boot – Chain of Trust Securing Keys and Data Cryptographic Keys Data in Flight Data at Rest Trusted or Isolated Execution Defense in Depth OpenVINO Security Add-on Secure Development Lifecycle (SDL) Support and Response Summary Chapter 5: Machine Learning Security and Trustworthiness Usage of Machine Learning in IMSS Challenges and Risks Policy and Standards Regulatory Landscape IoT Security Baseline Privacy Compliance GDPR and Emerging EU AI Regulation AI/ML Trustworthiness Trustworthiness Journey AI Model and Data Provenance AI Risk Management IMSS with ML Protection Stakeholders and Assets Threats Threats for the Training Process Threats for the Inferencing Process Training at the Edge ML-based IMSS Protection and Trustworthiness Framework Foundational Device Security Workload Protection IP Protection OpenVINO™ Model Protection Security Data Protection, Privacy, and Provenance Federated Learning Homomorphic Encryption Data Provenance Trustworthiness Chapter 6: Sample Applications Putting It All Together – What Does It Take to Build a System? Resource Graph Crawl – Starting Small – Workstation: An SMB IMSS System SMB System Assets and Threats Using Information Security Techniques to Address These Threats to an SMB IMSS System Walk – Let’s Get Enterprising – Edge Server: Critical Infrastructure Edge Server Critical Infrastructure System Assets and Threats Using Information Security Techniques to Address the Threats to an Edge Critical Infrastructure System Run – Forecast: Partly Cloudy – Data Center: Building Blocks for a Smart City Smart City Data Center System Assets and Threats Using Information Security Techniques to Address the Threats to a Smart City System Chapter 7: Vision – Looking to the Future The Evolution of Intelligent Multimodal Security Systems Intelligence at the edge Multimodal Mobility Threats Defenses Trust Privacy What Should You Do? Chapter 8: As We Go to Press Growth of IMSS Cybersecurity General Technology Artificial Intelligence and Machine Learning Regulations Standards Final Exhortation Index
Related Books
