Towards security and privacy for edge ai in iot/ioe based digital marketing environments
Abstract
Edge Artificial Intelligence (Edge AI) is a crucial aspect of the current and futuristic digital marketing Internet of Things (IoT) / Internet of Everything (IoE) environment. Consumers often provide data to marketers which is used to enhance services and provide a personalized customer experience (CX). However, use, storage and processing of data has been a key concern. Edge computing can enhance security and privacy which has been said to raise the current state of the art in these areas. For example, when certain processing of data can be done local to where requested, security and privacy can be enhanced. However, Edge AI in such an environment can be prone to its own security and privacy considerations, especially in the digital marketing context where personal data is involved. An ongoing challenge is maintaining security in such context and meeting various legal privacy requirements as they themselves continue to evolve, and many of which are not entirely clear from the technical perspective. This paper navigates some key security and privacy issues for Edge AI in IoT/IoE digital marketing environments along with some possible mitigations.
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Edge AI can analyse customer data, including purchase history and behaviour, to provide personalized recommendations and improve customer experiences.
“Business Marketing: Edge AI can be used to analyse customer data, including purchase history and behaviour, to provide personalized recommendations and improve customer experiences [163].”
From Edge AI: A survey (2023) · cites this paper as [163]
Computation for data handled via edge computing is much shorter than transmitting data to a centralised data centre, which is useful for time-sensitive software such as video games and augmented reality.
“Minimize delay: Compared to transmitting data to a centralised data centre, the computation for data handled via edge computing is much shorter.This is useful for time-sensitive software, such as video games and augmented reality [163].”
From Edge AI: A survey (2023) · cites this paper as [163]
By keeping sensitive information secret, edge AI makes meeting data regulations much easier.
“By keeping sensitive information secret, edge AI makes meeting data regulations much easier [163].”
From Edge AI: A survey (2023) · cites this paper as [163]
Cited by
Sorted by citations
Singh, R., & Gill, S. S. (2023) · Internet of Things and Cyber-Physical Systems · doi:10.1016/j.iotcps.2023.02.004 · Cited by 572 · see citing works
- Authors
- Sachdev, R.
- Affiliations
- Columbia University (US)
- Corresponding author
- Sachdev, Raj
- Venue
- 2020 Fifth International Conference on Fog and Mobile Edge Computing (FMEC)
- Publisher
- IEEE
- Published
- 2020-04
- Pages
- 341-346
- OpenAlex
- W3044404482
- Cited by
- 52
- References
- 0
- Citations by year
- 2026: 6 · 2025: 10 · 2024: 16 · 2023: 13 · 2022: 4 · 2021: 3
- FWCI
- 4.19
- Type
- conference paper
- Language
- en
- Open access
- closed
- Licence
- Locations
- International Conference on Fog and Mobile Edge Computing (FMEC) (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
- Physical Sciences › Computer Science › Information Systems › Internet of Things and AI
- Physical Sciences › Computer Science › Artificial Intelligence › Privacy-Preserving Technologies in Data
- Keywords
- edge AI, edge computing, Internet of Things, Internet of Everything, digital marketing, data privacy, data security, personal data protection, privacy regulation, personalized customer experience, security risk mitigation
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