Guest Post by Tim Roemer, President & GM, Public Sector, ThriveDX
Artificial intelligence (AI) is a rapidly-growing field that has the potential to change many aspects of our lives. From healthcare to transportation, AI is being used to improve the world. The average American may not be aware of all the ways that AI is already being used, but it’s likely that they have encountered it in some form and benefited from it in surprising ways.
As cyber attacks increase and the AI capabilities improve, it’s important to comprehend that AI is not a one size fits all solution and no resource can offer 100% security. Organizations that think an AI tool can solve all of their problems are in for a rude awakening. In fact, many CISO’s believe AI should be referred to as “assisted intelligence,” because although it is a significant help to cybersecurity officials, it still needs to be appropriately configured and managed.
It’s imperative to understand that nearly 82% of cyber incidents are caused by a human element, according to Verizon’s annual cybersecurity report. That’s why it’s critical for cybersecurity teams around the world to understand that one tool or one technology can’t solve all of your cyber resiliency needs, and at the end of the day creating a culture of cybersecurity awareness among all end users is still the best strategy for securing your networks.
Healthcare and transportation
Healthcare and transportation are two industries harnessing the power of AI algorithms to improve patient outcomes and reduce accidents caused by human error.
In healthcare, AI algorithms analyze medical imaging to assist doctors in making diagnoses, potentially leading to faster and more accurate diagnoses. By analyzing large amounts of data, AI can also identify patterns and trends to improve patient outcomes. AI algorithms can also identify patients at high risk of developing certain conditions, such as heart disease or diabetes, so that they can receive preventative care.
In transportation, self-driving cars are now on the road, using AI algorithms to navigate roads, avoid obstacles, and make decisions about when to brake or accelerate. Additionally, AI is being used to optimize traffic flow and reduce bottlenecks.
AI & Cybersecurity
One of the most significant advantages of using AI in cybersecurity is its ability to detect and respond to threats in real time. Traditional security systems rely on predefined rules and patterns to identify threats. Experienced cybercriminals know how to avoid this type of detection.
AI is always learning. As new threats emerge, AI pivots and makes it much more difficult for attackers to evade detection. The concern for security teams is the volume of data increases tenfold each day, making it harder to process. AI can automate repetitive tasks currently performed by human security analysts to analyze large amounts of data and identify patterns that may evade security team detection.
Detection & Response
One specific area where AI is making a big impact in cybersecurity is in the field of threat detection and response. By analyzing large amounts of data from various sources, AI algorithms can detect patterns and anomalies that indicate the presence of a threat. AI can identify malware, detect suspicious network traffic, and identify phishing attempts. Once a threat is detected, AI can also be used to automatically respond to it, such as by quarantining a compromised device or blocking suspicious network traffic.
AI improves intrusion detection and prevention systems (IDPS). These systems are designed to detect and prevent unauthorized access to a network or system. They often generate a high number of false positives, overwhelming security teams. AI analyzes the data generated by IDPS so security teams can identify and respond to real threats while reducing the number of false positives they spend time on.
Machine learning algorithms
AI enhances cybersecurity via machine learning algorithms. The tech analyzes and understands the behavior of users and devices on a network. If a device suddenly starts communicating with a large number of new devices, this could indicate that it has been compromised and is being used to launch an attack. Understanding these interactions can make it easier for AI to detect unusual activity that might indicate a breach.
Mobile devices are always at risk for sophisticated cyberattacks. By analyzing mobile apps and the data they access, AI can detect potential security risks and sound the alarm. AI can identify malicious apps that have been downloaded or detect apps accessing sensitive data without permission.
AI also has the potential to improve the security of Internet of Things (IoT) devices. These devices are increasingly common in homes and businesses. They often have limited processing power and are difficult to secure. AI can be used to analyze the data generated by IoT devices and detect unusual activity that might indicate a breach.
The security of cloud-based systems can always be improved. Cloud computing is becoming increasingly popular. However, it also presents new security challenges. For instance, if a large number of login attempts are coming from a single IP address, this could indicate that an attacker is trying to gain unauthorized access to the system. By analyzing data like this from cloud-based systems, AI can detect patterns that indicate a compromise.
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