Categorical Trust in Digitality
(eBook)

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Published
BookBaby, 2022.
Format
eBook
Language
English
ISBN
9781667872483

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APA Citation, 7th Edition (style guide)

Srinivas Kumar., & Srinivas Kumar|AUTHOR. (2022). Categorical Trust in Digitality . BookBaby.

Chicago / Turabian - Author Date Citation, 17th Edition (style guide)

Srinivas Kumar and Srinivas Kumar|AUTHOR. 2022. Categorical Trust in Digitality. BookBaby.

Chicago / Turabian - Humanities (Notes and Bibliography) Citation, 17th Edition (style guide)

Srinivas Kumar and Srinivas Kumar|AUTHOR. Categorical Trust in Digitality BookBaby, 2022.

MLA Citation, 9th Edition (style guide)

Srinivas Kumar, and Srinivas Kumar|AUTHOR. Categorical Trust in Digitality BookBaby, 2022.

Note! Citations contain only title, author, edition, publisher, and year published. Citations should be used as a guideline and should be double checked for accuracy. Citation formats are based on standards as of August 2021.

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Grouped Work ID3aeae24c-fb8f-a466-00d7-bbfeb8fd9fde-eng
Full titlecategorical trust in digitality
Authorkumar srinivas
Grouping Categorybook
Last Update2023-11-13 19:07:28PM
Last Indexed2024-03-27 02:59:36AM

Book Cover Information

Image Sourcehoopla
First LoadedJun 21, 2023
Last UsedJul 22, 2023

Hoopla Extract Information

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    [synopsis] => Categorical trust in digitality is nirvana for information technology (IT) and operational technology (OT) convergence from device manufacturing to provisioning, commissioning, and field operations in production environments. It may not require expensive hardware upgrades to legacy devices and may be achievable with cost effective software or firmware enhancements, to extend the operational lifetime and efficiency of brownfield and greenfield devices in production environments. Retrofitting trust in the minefield of unprotected devices already in existence is essential for interoperability and integrity of long-lived inter-connected systems.

Smart devices designed for the Internet of Things (IoT), industrial IoT, and operational technology (OT) in the emerging era of digital transformation require protection by design for cyber resilience. Cyberattacks by nation state actors and cybercrime syndicates cause system outages and disruption of essential services. This book is a call to action—for silicon chip makers, equipment manufacturers, managed security service providers, device owners and operators, to begin the journey towards collaborative cyber protection.

The traditional information technology (IT) detection and prevention methods based on threat models are inadequate to defend the billions of devices that are an intrinsic part of our daily regimen. It's essential to adopt protection models based on risk for modernization across all sectors—smart factories, smart cities, smart grids, smart transportation, smart homes, healthcare systems, aviation systems, public utility systems, defense systems, and law enforcement systems.

The power of scientific and technological innovations offers opportunities to transform and reform the way things are and the way they ought to be. If the past three decades are a gauge of the power of innovation, then the next three decades will be a harbinger of the power of transformation.

Over the years, there have been multiple waves of technological evolution. We've seen evolutions from analog to digital over copper, and then from copper to fiber, and fiber to wireless. Soon after that, we advanced from on-premises to cloud data centers, and then from local applications to online applications, then local storage advanced to cloud storage. All these advancements were remarkable endeavors.

The second wave of inventions included virtualization, cloud computing, high speed connections, software defined networking, online applications and remote services. All these advancements have shaped a global economy.

This book emphasizes that the third wave is coming. Recent advances in silicon technologies, field-programmable gate arrays, edge computing, zero trust models, artificial intelligence (AI), machine learning (ML) and deep learning (DL) collectively provide a platform for digital transformation at scale.

Data is the digital currency and trustworthiness is the measurement of digital intelligence. Devices dominate every aspect of our daily living at home, in public, and at work. Digitality and Cybersecurity (digital military) will inevitably shape the future of humanity in profound ways. Even as humans are intensely "machine learning", machines are reciprocally "human learning". Therefore, categorical trust in data and devices is imperative.
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