Artificial intelligence (AI) is now having a major impact in nearly every area of our lives: it can provide better medical diagnosis and treatment; detect and reduce the risk of financial fraud; improve inventory management; and provide better support for Friday nights. of streaming movies provides the right recommendations. However, we can also make a strong case that some of the most important impacts of artificial intelligence will be in cybersecurity.
Artificial intelligence’s ability to learn, adapt, and predict rapidly evolving threats makes it an indispensable tool for protecting the world’s businesses and governments. From basic applications like spam filtering to advanced predictive analytics and AI-assisted responses, AI plays a critical role on the front lines, protecting our digital assets from cybercriminals.
However, the future of artificial intelligence in cybersecurity isn’t all rainbows and roses. Today, we can see early signs of a major shift driven by the democratization of AI technology. While artificial intelligence continues to help organizations build stronger defenses, it is also giving threat actors the tools to launch more sophisticated and stealthy attacks.
In this blog, we’ll review the changing threat landscape, track the evolving role of artificial intelligence in cyber defense, and consider the implications of protecting against future attacks.
Artificial Intelligence in Cybersecurity: The First Wave (2000-2010)
As we usher in the new millennium, the initial stages of digital transformation are beginning to impact our personal and professional lives. In most organizations, knowledge workers perform their work in tightly managed IT environments, utilizing desktop and laptop computers and local data centers that form the backbone of the organization’s IT infrastructure.
High-profile cyber threats at this time are focused on creating chaos and gaining notoriety. The early 2000s saw the creation of malware such as ILOVEYOU, Melissa, and MyDoom, which spread like wildfire and caused severe global damage. In the mid-2000s, the lure of financial gain led to a proliferation of phishing schemes and financial malware. The Zeus banking Trojan has emerged as a significant threat, quietly stealing banking credentials from unsuspecting users.
Organizations rely heavily on basic security controls, such as signature-based antivirus software and firewalls, to try to fend off intruders and protect digital assets. As improved intrusion detection systems entered the network security arsenal, the concept of network security began to evolve. Two-factor authentication (2FA) is gaining traction at this time, adding an extra layer of security to sensitive systems and data.
This is also when artificial intelligence first begins to show tremendous value for defenders.隨著垃圾郵件數量激增，不請自來的（通常是惡意的）電子郵件堵塞了郵件伺服器和收件箱，透過快速致富計畫、非法藥品和類似的誘惑來誘騙用戶洩露有價值的個人information. While artificial intelligence still seems like science fiction to many in the IT world, it is proving to be an ideal tool for quickly identifying and isolating suspicious messages with previously unimaginable efficiency, helping to significantly reduce risk and recover. Lost productivity. Although artificial intelligence is still in its infancy, it has already demonstrated its potential to help organizations protect themselves against rapidly evolving threats at scale.
Artificial Intelligence in Cybersecurity: Second Wave (2010-2020)
As we enter the second decade of this century, the makeup of IT infrastructure has changed dramatically. The explosive growth of SaaS (software as a service) applications, cloud computing, BYOD (bring your own device) policies, and the emergence of shadow IT have made the IT landscape more dynamic than ever before. At the same time, it creates an ever-expanding attack surface for threat actors to explore and exploit.
Threat actors have become more sophisticated and their targets broader; intellectual property theft, infrastructure disruption, and larger-scale monetization attacks have become commonplace. More and more organizations are becoming aware of nation-state threats driven by well-funded and highly sophisticated adversaries. This, in turn, drives the need for equally sophisticated defenses that can learn autonomously quickly enough to stay one step ahead. The Stuxnet worm that targeted Iran’s nuclear facilities, as well as devastating attacks against high-profile companies such as Target and Sony Pictures, gained notoriety and highlighted the escalating risks.
At the same time, supply chain vulnerabilities are in the spotlight, as exemplified by the SolarWinds breach that affected tens of thousands of organizations around the world. Perhaps most notably, there has been a surge in ransomware and wiper attacks, with notorious viruses like WannaCry and NotPetya wreaking havoc around the world. While relatively easy to detect, the volume of these threats requires defenses to scale with speed and accuracy that far exceeds the capabilities of human analysts.
During this time, artificial intelligence has become an indispensable tool for defenders. Leading this trend is Cylance, a company founded in 2012 that aims to replace heavyweight traditional antivirus software with lightweight machine learning models. These models are trained to quickly and effectively identify and block rapidly evolving malware. The role of artificial intelligence in cybersecurity continues to expand, with machine learning techniques used to detect anomalies, flag unusual patterns or behaviors that indicate sophisticated attacks, and perform predictive analytics to anticipate and prevent possible attack vectors.
Artificial Intelligence in Cybersecurity: The Third Wave (2020-Present)
Today, the application of artificial intelligence in cybersecurity is undergoing a profound transformation. The ubiquity of remote working, coupled with highly connected and distributed IT systems, has blurred traditional security boundaries. As the Internet of Things (IoT) and connected devices proliferate, from smart homes to smart cars and entire cities, the attack surface expands exponentially.
In this context, the role of artificial intelligence has evolved from a pure defense mechanism to a double-edged sword that is also exploited by adversaries. While commercially generated AI tools such as ChatGPT attempt to erect guardrails to prevent bad actors from exploiting the technology for malicious purposes, the emergence of adversarial tools such as WormGPT has filled the void for attackers.
Potential examples include:
- Artificial Intelligence Generated Phishing Campaign: With the help of generative artificial intelligence, attackers can now craft highly convincing phishing emails, making these deceptive messages increasingly difficult to decipher. Recent research has also confirmed that generative artificial intelligence can save attackers days of work for each phishing campaign they create.
- Artificial intelligence-assisted target recognition: By leveraging machine learning algorithms to analyze social media and other online data, attackers can more effectively identify high-value targets and tailor their attacks accordingly.
- Artificial intelligence-driven behavioral analysis: Malware powered by artificial intelligence can learn typical user or network behaviors to evade detection by better mimicking normal activities to carry out attacks or data exfiltration.
- Automatic vulnerability scanning: Artificial intelligence-driven reconnaissance tools can facilitate autonomous scanning of network vulnerabilities and automatically select the most effective exploits.
- Smart data sorting: Instead of mass-copying all available data, artificial intelligence can identify and select the most valuable information to leak, further reducing the chance of discovery.
- Artificial intelligence-assisted social engineering: The use of artificial intelligence-generated deepfake audio or video in phishing attacks can convincingly impersonate a trusted individual, providing greater credibility to social engineering attacks that convince employees to disclose sensitive information.
The unfolding of the third wave of artificial intelligence highlights a critical inflection point in cybersecurity. The dual use of artificial intelligence—both as a shield and as a spear—highlights the need for organizations to stay informed.
in conclusion
The evolution of cybersecurity has emphasized the relentless creativity of threat actors and the need for defenders to remain well-equipped and informed. As we transition to the stage where artificial intelligence serves as both an ally and a potential adversary, the story becomes more complex and fascinating.
Cylance® AI has been around since the beginning, as a pioneer and recognized leader in the market for artificial intelligence-driven cybersecurity. Looking to the future, BlackBerry® will continue to push the boundaries of Cylance AI technology and explore future development trends. Stay tuned for our upcoming blog as we dive into how generative AI is entering the scene as a powerful tool for defenders, providing new perspectives for predicting and countering complex threats in the future.
The future holds promise for those who are ready to embrace the growing advances in AI-driven cybersecurity.
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Notes – This article was carefully written by Jay Goodman, Director of Product Marketing at BlackBerry.
