Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Search research articles

Related Experiment Videos

Security by design in artificial intelligence-enabled energy management systems: a sociotechnical framework.

Theodore Kindong¹, Gianluigi Viscusi¹, Björn Johansson¹

¹Linköping University, Linköping, Sweden.

Frontiers in Artificial Intelligence

|July 11, 2026

Summary

Related Concept Videos

Control Systems: Applications

Control Systems: Applications

Electrical engineering plays a pivotal role in our daily lives, with control systems at the heart of many applications, from home appliances to sophisticated space shuttles. Control systems manage and regulate the behavior of devices and processes, ensuring they function safely, correctly, and efficiently.
In modern vehicles, control systems manage various functions to enhance performance and safety. The steering wheel and accelerator are primary inputs in a car's control system. The direction...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Long-term ocular symptoms following COVID-19 linked to immune dysregulation, dysautonomia and peripheral neuropathy.

Nature communications·2026

Same author

Risk factors for posterior capsule opacification following phacovitrectomy: a six-year retrospective analysis.

International ophthalmology·2026

Same author

Understanding sustainability data through unit manufacturing process representations: a case study on stone production.

Procedia CIRP·2024

Same author

SEGUID v2: Extending SEGUID checksums for circular, linear, single- and double-stranded biological sequences.

bioRxiv : the preprint server for biology·2024

Same author

Pedagogical Orientations and Evolving Responsibilities of Technological Universities: A Literature Review of the History of Engineering Education.

Science and engineering ethics·2023

Same author

Psychological Stress and Atopic Dermatitis: A Focus Group Study.

Annals of dermatology·2023

Artificial intelligence (AI)-enabled Energy Management Systems (EMS) are crucial for smart grids but pose security risks. This study proposes the Prevent-Audit-Learn-Harden (PALH) framework to address AI-EMS data security challenges throughout the system lifecycle.

Area of Science:

Computer Science, Cybersecurity, Energy Systems Engineering

Background:

The global energy sector is digitizing, increasing reliance on AI-enabled Energy Management Systems (EMS) for smart grids.
These advanced systems introduce significant data security and governance challenges.
Ensuring trustworthy and resilient energy infrastructure requires addressing these new vulnerabilities.

Purpose of the Study:

To investigate security issues in the development and implementation of AI-enabled EMS.
To develop a conceptual framework and practical design principles for securing AI-EMS.
To propose a holistic, lifecycle-oriented approach to data security in smart energy systems.

Main Methods:

Employed a Design Science Research (DSR) approach.
Conducted a literature analysis of academic and practice-oriented sources.

Keywords:

artificial intelligence design science research energy management systems security smart grid

Related Experiment Videos

Developed a conceptual framework with a lifecycle perspective (data generation, sensing, model development, deployment).

Main Results:

A conceptual artifact categorizing data security challenges across AI-EMS lifecycle phases.
Four design principles formulated to address identified security vulnerabilities.
The Prevent-Audit-Learn-Harden (PALH) framework proposed for secure AI-EMS design, deployment, and operation.

Conclusions:

Addressing AI-EMS security requires coordinated stakeholder action across system layers.
Dedicated security tools and governance mechanisms are essential.
A lifecycle-oriented security approach is vital for the transition to decentralized smart grids.