Embracing AI in Cybersecurity: The Ultimate Resource Round-Up
By: Brittany Holmes, Corporate Communications Manager
As we move into the new year and reflect on 2023, we have learned the stakes for cybersecurity have reached unprecedented heights. Cyber threats continue to grow in complexity, leaving organizations and individuals vulnerable to data breaches, ransomware attacks, and increasingly sophisticated cyberattacks. Artificial Intelligence (AI) has emerged and risen as a powerful ally in the fight against threats and adversaries.
In this blog post, we’ll explore the current state of AI in cybersecurity as of 2023 and provide Adlumin’s AI round-up of resources to help equip you for the upcoming year.
AI in Cybersecurity
AI in cybersecurity has become integral to protecting modern digital systems this past year. Machine learning algorithms analyze and identify patterns in vast amounts of data, enabling organizations to efficiently detect and mitigate potential cyber threats.
Cybercriminals leverage AI to sabotage defenses, accelerate the development of their tactics and tools like phishing lures, and even lie dormant in the hands of an advanced persistent threat (APT) that’s playing a long game deploying an AI mole in the halls of government or in the defense industry.
To learn more, read ‘The Intersection of AI and Cybersecurity: A Closer Look.’
Making Cybersecurity Faster and Smarter
The concept of automation often blends into the artificial intelligence (AI) world, where AI makes decisions based on a number of technologies and learned variables. In principle, automation also makes these same types of decisions, but it’s based on rules and patterns. Nonetheless, in cybersecurity, automation is only as smart as we make it. The cyber-world is colossal, and different teams and operations can all use automation in different ways.
To learn more about automation in a Security Operation Center (SOC) and the pros and cons of automation used in cybersecurity, read ‘How Automation Makes Cybersecurity Faster and Smarter: The Pros and Cons.’
AI is Used to Detect Lateral Movement
Adlumin’s Data Science team constantly develops more robust and holistic solutions for automated defense against network intrusion and data exfiltration. Adlumin recently flagged lateral movement incidents on a customer’s network. The detection was achieved via an AI algorithm designed to aggregate suspicious incidents until they collectively project a high-fidelity threat signal. This prevented further compromise of valuable resources, and Adlumin detection response teams advised the client on remedial action.
Learn more about how Adlumin’s AI detected and remediated this incident in ‘How AI is Used to Detect Lateral Movement.’
Current, Upcoming, and Future AI Technology
At Adlumin, we develop AI applications for cyber defense, bringing specific techniques to bear. The central challenge for AI in cyber applications is to find “needle in haystack” anomalies from billions of data points that mostly appear indistinguishable. The applications in this domain are usefully grouped under the term User and Entity Behavior Analytics, involving mathematical baselining of users and devices on a computer network followed by machine-identification of suspicious deviations from baseline.
Organizations need to build a cybersecurity infrastructure embracing the power of AI, deep learning, and machine learning to handle the scale of analysis and data. AI has emerged as a required technology for cybersecurity teams to scale and protect the complex attack surfaces of organizations. So, when evaluating security operations platforms, organizations need to know how AI can help identify, prioritize risk, and help instantly spot intrusions before they start.
Learn more about suggested AI solutions to integrate into your cybersecurity plan, AI risks, and pitfalls in ‘Unraveling Cyber Defense Model Secrets: The Future of AI in Cybersecurity.’
Embracing AI in Cybersecurity
The AI round-up of resources highlights the significant role that artificial intelligence, deep learning, and machine learning techniques play in protecting organizations from the evolving landscape of cybersecurity threats. With the increasing complexity and sophistication of these threats, it is crucial for organizations to leverage powerful AI algorithms to analyze vast amounts of data and identify potential security breaches.
By embracing automation and integrating AI into their cybersecurity strategies, organizations can enhance their security operations, making them faster, smarter, and more effective in detecting and mitigating cyber threats. This collection of resources provides valuable insights and tools to help organizations build a robust cybersecurity infrastructure that can stay ahead of cybercriminals and safeguard their data and systems in the years to come.
Enhance Your Team
The chase to stay ahead of threats is not slowing down. Gain valuable insights into the future of threat detection and response with latest Gartner report on emerging tech.
Learn how AI can enhance your team’s capabilities and shine a bright light on hidden risks.
