Edge intelligence: a game changer in protecting user data
Edge computing is the answer to AI security concerns
As AI and machine learning have developed, these technologies have been integrated into all kinds of smart devices.
And, with an estimated 75.4 billion IoT devices installed worldwide by 2025, it’s no surprise that these smart devices are predicted to increase as a cyber-attack target throughout 2023.
This begs the question, should this AI and ML work be done in the cloud or at the Edge?
As of right now, AI work is predominantly cloud-based, which is increasing the demand for cloud security.
While cloud-based data storage and AI can be equipped with cyber security measures to prevent data breaches, cloud data centers can be (and are!) still getting hacked.
Companies that host a large amount of valuable customer data in the cloud must be careful, as even a partial breach can have far-reaching adverse effects.
This is because a company’s cloud storage contains enormous hordes of extraordinarily valuable data. So, even if an attacker only gains access to a fraction of it, they can do serious damage.
Edge solutions have been a savior as they offer uncompromised services while keeping up with data protection measures in many ways.
For example, Edge intelligence makes it possible to eliminate security vulnerabilities by keeping data local. Additionally, Edge computing and Edge AI protect sensitive user information by only sending processed patterns and meta information to the cloud for analytics and training purposes.
On top of this, intelligent Edge devices are the perfect choice for adhering to rules and regulations that dictate how far data can travel from the source and filtering data before transferring it to the cloud.
Additionally, user awareness about data privacy is crucial, and there are strict rules around transparency and consent in many parts of the world. Again, edge computing excels here, as it keeps users well-informed about the data processed and generated using its applications.
To learn more about cyber security in the world of AI and Edge AI, explore the info below.
Outsmarting the scammers
This article discusses the top threat vectors in cyber security for 2023 and offers advice on protecting against them.
According to a survey conducted in mid-2022, 75% of cybersecurity professionals stated that social engineering and phishing are the most dangerous threats to organizations.
This author suggests businesses pay attention to these threat vectors and seek guidance from cyber security professionals.
The Most Dangerous Cyber Security Threats of 2023
Protecting sensitive data with Edge computing
The article below explores how Edge computing-based network intelligence solutions are becoming increasingly popular as network operators are now required to comply with various regulations worldwide.
Edge intelligence eliminates security vulnerabilities by keeping data local and not transmitting it to external networks.
Additionally, it protects sensitive user information by only sending processed patterns and meta-data containing contextual information to the cloud for analysis.
Here’s Why Edge AI-Based Network Intelligence Solutions Are Gaining Momentum
A new era of network security with federated learning
The Metaverse is a new internet iteration incorporating technologies such as AI, machine learning, Edge computing, and 5G infrastructure.
This contributes to a vast amount of data, including an unlimited number of touch sensors communicating between wearable devices, which are prime targets for hackers.
This accumulation of data poses security risks and privacy concerns.
To address this, Federated Learning is used, which applies machine learning in a decentralized manner to train a model at the network’s edge where data remains on the device rather than being transferred to a server.
This method increases network speed, bandwidth optimization, and data security.
Cybersecurity in the AI-Based Metaverse: A Survey
Some extra resources
Living life on the Edge
This article notes that running artificial intelligence in the cloud has been the norm for many years.
Nevertheless, with the rise in Edge computing, it’s increasingly asked if running AI in the cloud is always necessary.
How is Data Processed in Edge Computing?
5G-fueled market growth
The "Global Edge AI Hardware Market Report" predicts market opportunities for Edge AI hardware with special consideration given to the emergence of 5G networks that integrate IT and telecom.
The report covers the Edge AI market by function, device type, component, vertical, and regional outlook, from 2022 to 2028.
Global Edge AI Hardware Market Report 2022
Edge computer vision: A business perspective
This article explores the potential of computer vision (CV) in Edge applications through a three-part deep dive.
The first part of the article presents the new business outcomes that CV can unlock for enterprises.
The second part describes the key CV technologies used to achieve these outcomes. The third part explores the challenges in adopting Edge CV technologies and suggests strategies enterprises can implement to overcome these.
Intro to Edge Computer Vision Technology
Xailient’s newest article
This week’s article discusses the importance of integrating AI and Edge AI into smart home products, focusing on the features and benefits these technologies bring.
Ultimately, incorporating AI into smart home products is about creating a home that truly understands and adapts to its users, making their lives more comfortable, efficient, and secure.
To learn more, check out Why Are AI-Enabled Smart Home Products the Next Big Thing?
Thanks for reading,
See you next week!