Technology continues to connect businesses, governments, and people at a momentous pace. With these new possibilities also come challenges. As a result, cybersecurity professionals must stay agile to challenges such as cyberattacks and an expanded attack surface.
One accepted solution is the application of artificial intelligence (AI) to cybersecurity strategies. Increasingly, security teams use artificial intelligence to protect business infrastructures from cybercriminals.
When trained and used correctly, AI technologies can automatically:
• Detect cyber threats
• Issue alerts
• Respond to cyber threats
• Protect vast amounts of data
• Identify new malware threats
By definition, AI uses automation to perform tasks that normally require human intelligence. This is accomplished by gathering data to learn how to react or make decisions. However, integrating this technology into security frameworks also presents challenges.
There could be unpredictable false positives that take your security team’s attention away from real threats. Furthermore, an AI-enabled machine that relies heavily on old data may not thwart new sophisticated attacks from bad actors.
Generally, human intervention is essential to strengthening your company’s security posture. However, automation of some tasks like system monitoring can increase threat detection capabilities. Doing so also helps your security save time when discovering new threats.
This added threat intelligence layer is vital against the ever-increasing sophistication of cyber attacks. Furthermore, automating certain aspects of cyber security integrates with existing business environments.
Other safety benefits of automating AI include:
• Improved decision-making: Automating cybersecurity strategies helps your IT team identify potential threats and make the appropriate corrections. This way, you can implement procedures for better network security.
• Decreased potential for human error: Most traditional security tools require human intervention, which, unfortunately, can lead to costly mistakes. The role of AI in cyber security removes the human factor from most processes.
• Cost-efficiency for incident response management: Your security professionals no longer have to perform the time-consuming data collection task. AI speeds this process along so IT can focus on value-added strategic activities.
Keep in mind that hackers will adjust their malicious methods to counter new AI technologies. They also use AI for advanced attacks and new forms of malware to target security systems.
The use of adversarial AI may circumvent your online defense strategies. For instance, cybercriminals will look for weaknesses in algorithms to exploit. Nevertheless, artificial intelligence offers enormous potential when used appropriately.
Advancements in research and development offer ways for future technologies to improve the predictive capabilities of suspicious activities. With better anomaly detection, your IT team can prevent cyber attacks from slipping under the radar.
Generally, the role of AI in cybersecurity can reinforce the threat intelligence gathered to prevent cybercrime. Security professionals use it to search for common characteristics of cyberattacks.
By doing so, IT can analyze data from fingerprints, voice patterns, and typing styles. Invariably, this data collection of human behavior authenticates authorized users and keeps bad actors away.
Applying machine learning and AI systems can combat evolving cyber attacks in real-time. Automating threat detection processes gives you a greater ability to respond more efficiently before irreparable harm disrupts business operations.
Here are seven ways AI solutions enforce good online IT security practices that protect endpoint devices in-house and remotely.
Artificial intelligence can help your company secure user accounts by protecting passwords with authentication measures. You can apply AI tools such as:
• Facial recognition
• CAPTCHA
• Fingerprint scanners
Either one of these methods can identify whether login attempts are from legitimate users or hackers. Extra layers of security keep sensitive data safe from cybercrime tactics.
Phishing remains one of the most prevalent security threats that businesses of all industries face. Applying AI solutions within email security practices helps your IT team discover anomalies. These solutions help with mitigating malicious messages by analyzing email content.
For example, AI identifies common signs of phishing, such as misspelled domains, fake LinkedIn profiles, email spoofing, and forged senders. This is done through machine learning algorithms, where AI learns from legitimate data.
By understanding user behavior, AI helps to prevent advanced threats before your network and systems suffer serious damage.
Despite the significant amount of time it takes, your company needs network security policies for all users to follow. The machine learning technologies of AI allow it to learn traffic patterns and recommend the right policies.
It can also assist your security team with determining which applications belong to specific workloads. Network security policies also set rules for identifying potential security incidents.
Cybercriminals relentlessly deploy methods and techniques to exploit potential vulnerabilities. As a result, this puts your company in a challenging position to prevent cyberattacks. AI solutions enable your team to analyze activities across all servers and devices.
By doing this in real-time, the power of AI protects your company even before an attack occurs.
Traditionally, security defenses relied on indicators of compromise and attack signatures to expose threats. This is not practical for today’s sophisticated attacks. Instead, your security professionals can implement an AI solution that enhances the ability to find threats.
Behavioral analytics is also helpful for processes that identify potential vulnerabilities and evolving cyber threats. Generally, AI collects data sets to teach machine learning algorithms to make predictions.
It develops profiles of the applications on your network. Additionally, it processes vast amounts of data from network users and devices. Analyzing incoming data exposes and prevents malicious activity.
A threat might not be so obvious when individuals have legitimate reasons to access your network. However, AI can also detect and respond to insider cyber threats. Through its analysis of user behavior, AI can identify and flag specific patterns.
AI solutions for endpoint security surpass traditional practices that rely on signature-based protection. Essentially, AI uses machine learning algorithms to identify abnormal behavior, enabling it to detect a previously known threat that might otherwise go unnoticed.
In addition to bolstering your cybersecurity measures, AI can serve as a resource multiplier. If you have a small IT department, the automating processes of artificial intelligence step in to fill certain duties.
This opens the opportunity for you to enhance cybersecurity investments. The results can lead to improved business operations, reducing the need to hire additional security professionals. Therefore, artificial intelligence helps to prioritize and complete tasks with or without human intervention.
You can leverage AI to get real-time updates on the latest security threats from hackers and bad actors. This ensures your IT is just as fast to either minimize or prevent damage. AI uses bots to draw from its database of learning.
This technology stores domain-specific knowledge along with mechanisms to obtain new knowledge as things change. Furthermore, it uses mechanisms such as deep learning, expert systems, machine learning, and neural networks to apply knowledge against threats.
• Deep learning is a subset of broader machine learning methods. Instead of task-specific algorithms, the mechanism learns data representations.
• Expert systems are AI systems that can solve problems that occur within specialized domains. They mimic how human experts think to make decisions by using rules-based reasoning from AI’s curated body of knowledge.
• Machine learning relies on statistical techniques so computer systems can learn how to use data. This mechanism works best as a task-oriented process instead of a wide-ranging mission.
• Neural networks use an AI programming model where a computer learns from vast amounts of observational data. AI determines whether the data is correct for use with a specific operation by assigning a weight to data inputs.
The power of AI holds immense potential to address the complex challenges businesses face from ransomware and other potential attacks from the threat landscape. Increasingly, AI and machine learning can have a significant role in your IT department’s ability to combat online threats.
The automation of threat detection and incident response practices helps your company augment its capabilities in cybersecurity solutions. As a result, you build superior resiliency to cyberattacks due to more effective decision-making when dealing with evolving risks.
The entire process of AI in cybersecurity helps to guarantee your team uses dependable results to combat cyber crimes. Adaptive responses are applied when appropriate, which further strengthens your security posture.
As the attack surface expands, the role of AI is to help identify and analyze these threats. Your security team joins in partnership with AI’s capabilities to prioritize risks and detect malware and other intrusions.
The role of artificial intelligence in cybersecurity brings both challenges and opportunities when used to build a robust defense against malicious activities. Carefully assessing your current security measures helps to ensure using AI does not compromise privacy and ethics.
As a tool, AI can amplify human abilities that remain the crux of security operations. Schedule a time to contact Meriplex at https://meriplex.com/contact/. Discuss with a representative how our AI solutions can help your company’s unique cybersecurity needs.
