An Overview of Tencent’s 2018 Cyber Security Report

The last few years have seen the exponential rise in the use of smartphones and cloud applications. With more use of digital services, there are more sensitive and valuable data are stored online. Therefore, the need for reliable cybersecurity is high so that the data stay fully protected from cyber attacks and malicious activities. Keeping this theme in mind, Tencent Holdings collaborated with Cybersecurity Innovation Institute published a detailed report titled “AI Empowers Cyberspace Security: Patterns and Practices” at world’s AI conference in Shanghai.

Tencent Cybersecurity Report –

The bottom line of Tencent Cybersecurity report states that artificial intelligence is the ultimate solution to almost all cybersecurity problems. This has come as a surprise to many as artificial intelligence is now behind used for cyber attacks.

The report breaks down the root cause of cyber attacks. It categorizes cybersecurity into network, online content and network infrastructure security. Besides, it also offers comprehensive AI cybersecurity measures for each of the categories. These AI cybersecurity measures are divided into predict, prevent, detect and respond.

Network Security –

Most of the cyber attacks take place through those networks that are unprotected and unattended.

Predict – Unsupervised networks are potential threats. The expert system, machine learning, and automation technology are used for identifying the threats and assessing the risks.

Prevent – Setting up AI-based cybersecurity prevention mechanisms. Use machine learning to mislead the attackers and hence, protection the more valuable assets.

Detect – Use of AI cybersecurity tools for monitoring traffic and real-time analysis of the unattended network. Use of expert system to identify the attack patterns.

Respond – The expert system classifies the threats and proceeds for intervention either manually or automated. It provides detailed direction for recovery and auditing.

Some of the popular applications in this connection are SparkCongnition, Deep Instinct, Invincea, Vectra Networks, DarkTrace, CyberX, and BluVector.

Online Content Security –

Predict – Use of deep learning and natural language processing for assessing the weak points and forecasting the risks in different scenarios.

Prevent – Upgrading the AI-based cybersecurity prevention tools with deep learning.

Detect – Use of image and video analysis tool along with natural language processing for recognizing and parsing content. Deploying AI cybersecurity tools to screen content.

Respond – Follow up investigation and audit are a must, and the use of automation is the crucial part.

Network Infrastructure Security –

Most of the cyber attacks take place taking advantage of the complexity of network infrastructure and intermingled technologies. Therefore, the report emphasizes smart traffic management for prevention.

Predict – The expert system uses machine learning to analyse the historical data and deep learning to forecast the traffic flow.

Prevent – Performing traffic control through optimized facilities to prevent the complexity and loopholes in interlacing technologies. The expert system is deployed along the entire path of the road system.

Detect – Real-time monitoring of traffic lights and vehicles to prevent traffic jams and quick dispatch of resources in unforeseen circumstances.
Respond –Use automation and AI to find out relevant information and provide follow-up guidance for investigation and control measurements.

Conclusion –

The use of AI cybersecurity solutions is on the rise, and in the last few years, major breakthroughs in AI cybersecurity solutions have come. It is estimated that by 2024, the AI-powered cybersecurity market will reach a valuation of $35 billion with a compounding growth of over 30%. Artificial intelligent(AI), machine learning(ML), deep learning(DL), and natural language processing(NLP) will go hand in hand in protecting the sensitive and valuable data of users as well as the corporate houses. Even with artificial intelligence, there is likely to be an increase of 25% in cybersecurity staff to proactive defenses against cyber attacks.