Apple and Chinese Telecom Firms to Combat Spam with Machine Learning

Security Breaches in China

In an effort to fight spam, attempted security breaches, and protect their Chinese customers, Apple will employ sophisticated algorithms based on advances in the field of machine learning. The California-based tech giant is looking to enlist the help of Chinese telecom operators to identify messages by source, presumably. “We are in touch with telco companies to see what additional steps could be taken to reduce this inconvenience,” Reuters quoted an Apple spokesperson as saying.

Apple plans to use machine learning to determine whether a message is spam or not, cites a report from Reuters. The tools, which are being developed will also help bar fraudulent accounts from sending spam messages. An Apple spokesperson was quoted as saying, “We are currently working on additional ways to further reduce it, including more advanced machine learning models to identify it and more tools to block fraudulent accounts.”

The Crux of the Matter

Apple was forced to act when the official state broadcaster, worried by the growing volume of spam messages Apple users were receiving through the messaging app and in an attempt to protect citizens who are most vulnerable, accused the American multinational corporation of allowing gambling apps on their devices – gambling is illegal in China.

The allegation forced the US manufacturer to take more effective action against unsolicited messages, which potentially cheats people out of their money, lowers consumer confidence in online commerce, and threaten the digital economy.

The issue of spam and unsolicited calls is a common problem in China, where individuals can get phone numbers from black markets. So, the Apple situation isn’t an isolated one. In fact, spam problem is so rife in China that a Spam Laws content claimed spam grows faster than the Chinese population.

On its part, the Chinese government is making efforts to curb spam through an organization created explicitly for this purpose, the “China Anti-spam Alliance.”

Undefined Engagement Objectives

Apple partnering with Chinese telecom operators is a step in the right direction. However, it is not yet clear what possible role the telecom companies could play with regard to fighting spam, or how they could help the tech giant, bearing in mind that Apple’s native messenger, iMessage uses the manufacturer’s servers and all data communication between end users is encrypted with a secure encryption algorithm.

As mentioned, they would likely be asked to provide the tech giant with information regarding the identity of spammers to enable Apple to block the messages from source using advanced machine learning algorithms.

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How Artificial Intelligence and Machine Learning Will Impact Cyber Security

AI Security and Intelligence Services

The efforts of security and intelligence services to counter threats has led experts to consider using new concepts that are fast becoming part of our daily life such as artificial intelligence (AI) and machine learning as a defense to boost skills for countering cyber-attack.

Industry experts have always believed that AI will have a growing impact on cybersecurity technology thanks to its potential to improve threat detection. Believe however turned to reality when Alphabet launched a cybersecurity intelligence system designed to fight crime on a global scale back in January. If one ever needed proof of how AI-based solutions will improve existing technologies and drive greater efficacy and efficiency in the war against cybersecurity, Chronicle is it. Before we proceed to discuss their impact on cybersecurity, it is essential to first understand, from a technical standpoint, what is meant by artificial intelligence and machine learning.

What is Artificial Intelligence?

Artificial intelligence is an aspect of computer science that gives prominence to the creation of applications that engage in tasks that require mental processes of a high level such as memory organization, perceptual learning, and critical thinking.

In other words, artificial intelligence borders on the development of machines that work and react like humans by performing activities such as problem-solving, learning, planning, and speech recognition, among others.

What is Machine Learning?

Kris Lahiri, co-founder and chief security officer of Egnyte, in an article published on Forbes, defined machine learning (ML) as “a branch of artificial intelligence (AI) that refers to technologies that enable computers to learn and adapt through experience.”

How Will AI and ML Impact Cybersecurity?

With technologies advancing very quickly, the sophistication of hackers is fast emerging as a threat to internet security. Cybercriminals continue to develop new attack strategies meant to avoid existing security systems. This makes organizations act defensively rather than proactively. The difficulty in knowing precisely what attackers are planning makes it hard to take preventive measures.

As the level of sophistication across the entire global threat landscape continues to increase rapidly, security outfits must use advanced tools to get ahead of the threats before they do any damage. Given their sophistication and intelligence, it is believed that the use of AI and machine learning tools will enable companies to detect, investigate and remediate breaches faster.

This is because AI allows organizations to automate complex processes for detecting attacks and responding to breaches. And since AI and ML work hand-in-hand, AI can leverage ML capabilities to enhance its abilities and evolve. In this manner, AI security solutions powered by ML can rely on ML use data from previous attacks to react to newer and similar risks.

Tech professionals believe that the efficacy of this approach rests on the fact that hackers build on old threats. Therefore, by deploying AI and ML, new dangers can be detected more quickly and dealt with before they do any harm.

 

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