Insights

Why understanding AI's role in data breach prevention is key to cyber resilience

UST Alpha AI

"All warfare is based on deception" - The Art of War

Although Sun Tzu's ancient wisdom was imparted as a military strategy many centuries ago, his core message reminds us today of warfare in cyber territory – deception is often the weapon of choice.

We are experiencing a world that has dramatically advanced with technological innovation, especially with the quantum leap in connectivity and information exchange. However, as digital technologies become a part of every aspect of modern daily living, the volume of data increases exponentially, exposing a much larger attack surface. Last year alone saw a 72% increase in data breaches since 2021, with 94 % of organizations reporting some form of email security incidents.

Cybersecurity has become a primary focus as our dependency on technology deepens with greater integration. Threat actors have evolved alongside technology to contrive unprecedented and sophisticated data theft attempts. With the global cost of cybercrimes estimated to reach a staggering 13.8 trillion US dollars by 2028, there is a heightened need for more preventive security measures, especially for entities dealing with massive amounts of critical public data such as healthcare, finance, or government organizations.

In the past year, artificial intelligence has completely shifted the world of technology, overturning the cyberattack landscape as we knew it. Cyberattackers are leveraging AI tools to carry out more sophisticated and widespread attacks than ever before. On the other hand, AI can also be the turning point in building fortitude against cyberattacks. With its passive processing and analytical powers, AI tools can bolster protection, keeping pace with cyber threat actors to prevent attacks.

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The evolving cyber threat landscape

Today's cyber risk arena is vast and evolving at warp speed. While hackers have been in play since the 80s, the nature and degree of attacks have matured. Malware, an umbrella term for any malicious software program, found its way from floppy disks to email attachments. In the last five years, 72.7% of all organizations worldwide fell prey to ransomware attacks, the most common type of attack that utilizes malware programmed to hold data or the device hostage while threatening to lock systems or leak sensitive data in demand of payment.

Alongside malware and ransomware attacks, data breaches have also played a major role in some of the largest cyberattacks today. Many remember the infamous Yahoo data breach in 2014, which impacted over 500 million user accounts. The attack likely originated as a phishing campaign in which the threat actor sent seemingly harmless emails to employees to divulge information. Phishing attacks operate via emails, text messages, or online communication, usually impersonating a familiar sender to trick users into sharing personal information or downloading virus-laden attachments. These attacks have powered some of the largest data breaches in history and continue to be on the rise as deception techniques become more advanced. In the age of generative AI, social engineering and other manipulation techniques, such as phishing, are finding new ground, leveraging tools that mimic genuine human dialogue or likeness, making victims more susceptible to targeted attacks.

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Challenges in traditional cyber security approaches

From the late 20th century, across the history of cybercrime, security solutions have evolved as responses to common threat techniques. Anti-virus software, firewalls, encryption, and software patch management, among others, are excellent munitions in the cybersecurity arsenal. However, today's cyber threats call for defense mechanisms that match pace in adaptability rather than operating in response.

Traditional security infrastructures lack the flexibility to conduct real-time threat detection. Most work on preset rules or signature-based detection systems that are effective against known attack patterns but require contextual understanding to identify intrusions or anomalous behavior that aren't predefined, resulting in attack vectors sneaking past the guard. With the rise in cloud technology, attackers have gained easier access to these unmapped areas, resulting in a significant rise in "Zero-Day attacks," which target unrecognized vulnerabilities.

Case in point: in 2021, the Microsoft Exchange Server was hacked via four Zero-Day exploits, gaining access to user emails and passwords. As threat actors continue to develop more complex attack mechanisms, similar attacks will continue to increase. With AI tools, that boom will likely be exponentially fast.

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Impact of AI on data breach defense

Last year, Best Buy's Machine Learning (ML)-based cybersecurity system improved the accuracy of detecting phishing emails to 96%. Such AI-powered security solutions can be the answer to cyber threats that are becoming more complex and personalized, using natural language and Deep Fake multimedia that is harder to detect.

AI algorithms utilize these same attack mechanisms for attack mitigation, processing vast datasets that are then correlated to recognize potential threat patterns in advance. This allows security teams to take a proactive approach compared to conventional security solutions, which tend to be more reactive.

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A glance at some of the AI capabilities that can power cyber resilience

• Real-time detection
  Organizations struggle to keep pace with escalating and mutating new threat variants and face challenges in reducing the time to detect breaches. With powerful analytical and computing capabilities, AI tools are equipped with insights from multiple sources across network logs, security files, or user behavior logs to detect unusual activities within minutes of an attack on networks or endpoints, moving detection much closer to real-time.

• User behavior analysis and monitoring
  Cyberattackers leverage user behavior to identify infiltration touchpoints. AI can help do the same on the defense side. Take phishing, for example. ML algorithms study how users interact with fraudulent emails, which links they click, or what they type. Interpreting unusual logins, unauthorized access, or permission changes on files and monitoring suspicious data transfers can help bolster defenses against a wide range of attacks. On an organizational level, the ability of ML-powered tools to analyze larger sets of data across all employee accounts can significantly improve a security team's ability to detect and respond to potential threats.

• Automated incident response
  AI automation capabilities are transforming security tools, and team reach has been a game changer across industries. In cybersecurity, AI-powered tools can automate incident triage and response, streamlining processes through categorization based on severity, prioritizing alerts, generating detailed reports, and even activating remedial action such as isolating compromised systems and files or blocking malicious IP addresses.

• Vulnerability prediction and continuous adaptability
  AI systems can learn much from past incidents, especially vulnerabilities that slipped past traditional security measures, such as Zero-Day attacks through pattern identification. By analyzing device, server, and user activity, AI tools can spot anomalies that would have typically gone unnoticed, such as unknown devices or suspicious cloud app integrations. This anomaly flagging drives further pattern identification, allowing AI tools to learn and adapt continuously. By comparing novel attack attempts to past attacks, the technology can understand contextual nuances to identify and prevent new threats from spreading.

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Benefits of leveraging AI-powered data security

A challenge found in signature-based systems involved reporting false positives and flagging outliers that did not match known threats. This created a time-consuming manual inspection of innocuous incidents. AI technology helps accurately filter harmful incidents with more nuanced behavioral understanding. It also detects behavior that may seem harmless but could signal a larger cyber threat when seen together with other activities. This improves the accuracy and rate of threat detection.

Traditional security monitoring relies heavily on manual effort, draining resources on monitoring network traffic or analyzing security alert logs. This has contributed to a growing trend of alert fatigue in security analysts. With the sheer scale of cyber threats in today's landscape, AI can alleviate the human workload, especially by automating routine tasks that can free up bandwidth for strategic tasks that increase operational efficiency while cutting costs. AI-generated reports can also equip security teams with powerful insights and comparative analysis into the nature and degree of threats that improve and empower decision-making.

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Walking the tightrope: considerations for AI implementation

The transformative power of AI, alongside its potential to amplify existing threats, has made the technology a double-edged sword. AI misuse can have significant problematic ethical implications for society. As a result, security professionals must carefully navigate maximizing its benefits for cyber defense while simultaneously minimizing potential drawbacks. Organizations must consider establishing guardrails and regulatory frameworks that underscore the importance of unbiased training data and educating resources with the proper awareness of AI use.

Globally, investment in security and risk management is predicted to reach $215 billion in 2024, up 14% from last year. However, merely spending on AI tools may not move the needle for enterprises needing enhanced cyber protection. A holistic strategy is critical to security transformation that roadmaps an organization's unique challenges and requirements within its existing architecture beyond AI solutions. UST's AI practice, for example, fosters a continuous discovery and learning culture that helps organizations better understand their specific demands from intelligent tools and suggest appropriate AI solutions that fit organizational needs.

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Wrapping up

Building a cyber-resilient organization requires a critical understanding of modern solutions that leverage emerging AI technologies such as machine learning, automation, and Generative AI. Enterprise leadership must understand cyber warfare on a global and geopolitical scale to gain a macro view of the threat landscape and better prepare organizational strategies for cyber defense. Adopting a proactive stance in cybersecurity is essential to staying one step ahead of cyberattacks and preventing unwanted breaches.

In the era of rapid innovation, business intelligence can help make AI tools work for your organization. UST's AI experts aim to empower enterprises and accelerate innovation while keeping pace with a fast-changing world.

Visit UST Alpha AI to explore tailored solutions for your businesses.