Methods for Requirements Engineering, Verification, Security, Safety, and Robustness in AIoT Systems
Kapitel i bok, 2024

This chapter presents methods for requirements engineering, verification,
security, safety, and robustness with a special focus on AIoT systems. It
covers an architectural framework dealing with requirements engineering
aspects of distributed AIoT systems, covering several clusters of concern
dealing with the context description of the system, learning environment of
the deep-learning components, communication concerns, and a set of quality
concerns, such as ethical aspects, safety, power, security, and privacy aspects.
Each cluster contains a set of architectural views sorted into different levels
of abstraction. In addition, it introduces WebAssembly as an interoperable
environment that would run seamlessly across hardware devices and software
stacks while achieving good performance and a high level of security as a
critical requirement when processing data off-premises. To address security
aspects in AIoT systems, remote attestation and certification mechanisms are
introduced to provide a TOCTOU (time-of-check to time-of-use) secure way
of ensuring the system’s integrity.

AIoT

robustness

machine learning

security

WebAssembly

safety

verification

IoT

requirements engineering

TOC- TOU

Författare

Marcelo Pasin

Jämes Ménétrey

Pascal Felber

Valerio Schiavoni

Hans-Martin Heyn

Software Engineering 1

Eric Knauss

Chalmers, Data- och informationsteknik, Interaktionsdesign och Software Engineering

Anum Khurshid

Shahid Raza

Shaping the Future of IoT with Edge Intelligence

197-228
978-87-7004-027-3 (ISBN)

Very Efficient Deep Learning in IOT (VEDLIoT)

Europeiska kommissionen (EU) (EC/H2020/957197), 2020-11-01 -- 2023-10-31.

Styrkeområden

Informations- och kommunikationsteknik

Ämneskategorier

Data- och informationsvetenskap

DOI

10.1201/9788770040273

Mer information

Skapat

2024-11-15