AI Technology Application is One of the Future Development Directions for Robotics
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The application of AI technology is one of the future development directions for robotics, and companies are conducting preliminary research and validation work in this area.
AI technology has brought us many conveniences, but it has also introduced a series of security risks. The establishment of AI security working groups strengthens research and protection in AI technology security, ensuring the safety and privacy of people when using AI technology.
Despite the disruptive experiences AI brings, the accompanying cybersecurity challenges cannot be underestimated. According to the latest report from British cybersecurity company Darktrace, attackers using generative AI like ChatGPT have increased social engineering attacks by 135% by enhancing text descriptions, punctuation, and sentence length.
Of course, technology has always been a double-edged sword, and AI is now widely used in cyber offense and defense. In fact, numerous research data indicate that the accelerated application of AI will drive explosive growth in the AI security market. According to research by foreign agency MarketsandMarkets, global organizations are expected to spend $22.4 billion on AI cybersecurity solutions in 2023. Precedence Research predicts that the AI cybersecurity market will exceed $100 billion by 2032.
Currently, a new round of technological revolution and industrial transformation is emerging. Driven by technologies such as 5G, big data, cloud computing, and deep learning, artificial intelligence (AI), as an important strategic technology for new infrastructure, is accelerating its development and innovatively integrating with various industries, triggering chain reactions. Particularly in the field of cyberspace security, AI has unique value and advantages in threat identification, situational awareness, risk scoring, malicious detection, harmful content governance, fraud call detection, and gray/black industry identification, leading to a leap in application demand and significant spillover effects.
From the perspective of product layout and application fields, the main competitors in China's AI security industry have similar product layouts, primarily focusing on big data analytics-driven security management platform products. From a technical standpoint, Chinese companies' products are based on big data platforms, collecting diverse and heterogeneous logs and using correlation analysis, machine learning, and threat intelligence technologies to provide security operations tools for professionals. Industry players rely on integrated modeling scenarios such as correlation, rules, and statistics for comprehensive conception, mastery, and implementation, achieving proactive management of security objects and timely analysis of security incidents through active monitoring, precise protection, intelligent analysis, and operational coordination, with little difference from domestic competitors.
This year, the highly popular large models have become a fiercely contested field, showcasing a "hundred-model battle."
As is well known, AI has a particularly profound impact on cybersecurity. Before AI, cybersecurity was essentially a human-to-human confrontation. With the advent of AI, its applications have introduced new threats and challenges to cybersecurity.
On one hand, AI's fragility, unpredictability, and lack of interpretability lead to trust issues, privacy data theft, and vulnerabilities to attacks. At the same time, AI misuse can trigger security risks, including deepfakes and large-scale, high-efficiency attacks. For example, in traditional cyberattacks, balancing scale and efficiency is difficult, but with AI automating attacks, hackers can launch large-scale, automated attacks at low cost, causing severe harm.
According to MIT Technology Review's interview data, in 2021, 60% of respondents struggled to counter automated cyberattacks, and 96% had already experienced AI-driven cyberattacks.
On the other side of the double-edged sword, AI can empower cybersecurity, driving offensive and defensive technologies toward automation and intelligence. Leveraging high computing power and machine learning, AI analyzes vast amounts of data and automates decision-making, improving the automation and intelligence of prediction, prevention, detection, and response in cybersecurity, enhancing protection speed and accuracy while reducing human errors and management costs.
Recently, NSFOCUS's "Fengyun Guardian" security large model and the "SecLLM Technical White Paper for the Security Industry" were released. This vertical industry large model, trained on massive security expertise, is a cybersecurity operations decision-support system covering scenarios such as security operations, detection and response, offense and defense, and knowledge Q&A.
Liu Wenmao, General Manager of NSFOCUS Innovation Research Institute, explained that the three enhanced capabilities of general large language models (LLMs)—general knowledge semantics, logical analysis, and interactive decision-making—play a crucial role in the security field. The cybersecurity industry requires speed, comprehensive coverage, and professional depth to meet the needs of major security guarantees, operations, and emergency responses across various customer scenarios.
The large model embodies six key advantages: enhancement of high-quality secure datasets, efficient parallel acceleration for incremental training, effective fine-tuning for downstream tasks, low-computing-power inference acceleration, human-AI alignment safety control, and secure private-domain interactions.
AI Security Industry Market Opportunity Analysis
Recent developments in the cybersecurity sector indicate that major security vendors, both domestic and international, have detected positive signals and are accelerating their AI deployments.
Internationally, at the end of March, Microsoft launched its next-generation AI product, Microsoft Security Copilot, applying AI technology to the cybersecurity field. This tool provides security professionals with an effective means to quickly detect and respond to threats while gaining better insights into the threat landscape.
At the end of April, during RSAC 2023, Google Cloud unveiled its latest Security AI Workbench product. Based on a new security-specific large language model called Sec-PaLM, it integrates Google Cloud's extensive threat data with Mandiant's intelligence on vulnerabilities and malware, aiming to help enterprises alleviate security operation pressures.
In terms of security intelligence, NSFOCUS released its "Fengyun Guardian" security large model. Trained on vast amounts of security expertise, it constructs a cybersecurity operation decision-support system covering various scenarios such as security operations, detection and response, offensive and defensive engagements, and knowledge Q&A.
Additionally, efforts are being made across three dimensions: "scenario-driven, technology-powered, and ecosystem collaboration." AI is being applied to reshape the working paradigms of the security industry, with large models addressing three major challenges: real-time situational command and dispatch, red-blue teaming decision support, and security operation efficiency enhancement.
Previously, Wangsu Technology announced a five-year investment of 1 billion yuan in a dedicated security business fund, focusing on cutting-edge offensive and defensive technologies, promoting the innovative application of big data and AI, and enhancing intelligent security protection capabilities.
As AI becomes a foundational capability and essential application across industries, the continuous emergence of new threats and protection demands will impose higher requirements on security technologies, paving the way for deeper integration of "AI + security." For security vendors, possessing a competitive edge in AI security capabilities will be a critical differentiator in this expanding market. Those who establish early and sustained leadership in this domain are likely to secure a strong market position.
China's cybersecurity industry has already reached a considerable market size, maintaining rapid growth over the years, offering companies opportunities to capture larger market shares. However, as user demands for cybersecurity products and services continue to rise, competition within the industry is intensifying due to the growing scale and competitiveness of existing players and the influx of new entrants.
AI security industry research reports primarily analyze the market size, supply and demand dynamics, competitive landscape, and key players' market shares in the AI security sector. They also provide scientific forecasts for the industry's future development. These reports assist investors in evaluating the current market conditions, predicting industry prospects, identifying investment opportunities, and offering strategic recommendations for investment, production, and marketing.