AI Security VS AI Cybercrime

AI is the future of cybersecurity, and while Skynet may still be a few years away, we can already see real-world applications of AI in cybersecurity. But as with any technology, there are both pros and cons, and cybersecurity professionals must decide if AI should be part of their strategy.

AI can identify fresh vulnerabilities in networks, devices, and applications

AI is an effective tool for network monitoring, detecting anomalies in data traffic, and alerting IT departments to potential threats. By combining traditional methods with AI, organizations can boost their detection rates by up to 95 percent. Furthermore, AI can be trained to automatically neutralize threats, limiting the damage they cause to a company's network.

The technology is also used by security firms. For example, Symantec is developing a tool called TAA to detect and analyze cyberattacks. The company has poured significant resources into AI research and has now launched several innovative products. A recent example of this is its Darktrace Threat Visualizer, a product that connects similar attacks and enables planners to better understand the complexity of the threats they face.

AI also improves the context for security alerts. It can also surface the root causes of incidents. These are important features for enhancing human information security teams. Moreover, AI-powered systems can explain their recommendations, allowing them to get buy-in from various stakeholders.

AI can detect intrusions early

Artificial intelligence (AI) can detectintrusions early. It can analyze network traffic to identify and block attacks. It can also detect attacks on wide-area networks. To prevent intrusions, AI methods should be designed to minimize the human factor. Currently, existing technologies are not as effective as they could be.

Several techniques have been developed for this purpose, and many researchers are exploring AI-based ensembles to better identify intrusions. Although there is no single algorithm that can provide 100 percent accurate detection, AI-based ensembles have many benefits over other techniques. They have the potential to reduce false-positive rates while improving detection accuracy. However, this technique does have some limitations. The size and modification of the training dataset are major determinants of the ensemble's success. In addition, the type and number of base classifiers used also play a critical role in the detection performance.

AI-based systems can also help security professionals understand their security programs better and identify weak areas. They can predict the likely locations of intrusions and recommend processes and resources to improve those areas. They can also help to prevent cyberattacks and minimize the damage they cause.

AI can reduce the number of false positives

By using AI, cybersecurity officials can discover problems earlier than they would otherwise. With predictive analytics, AI can recognize patterns and trends that point to emerging threats. A Ponemon Institute study found that the average organization loses $1.3 million a year due to false positives. By reducing the number of false positives, AI can free security professionals to fix real threats.

Artificial intelligence can also help cybersecurity teams by assisting in context-based vulnerability risk scores, proactively detecting vulnerabilities, and performing sentiment analysis of vulnerability exploitation trends. These solutions can significantly reduce the amount of time and effort required to analyze large amounts of data. AI is also useful in other areas, such as endpoint protection, security recommendations, bot spam, and more.

The economic and reputational cost of cybercrime has skyrocketed as a result of data breaches. According to an Accenture study, the average cost of a corporate data breach last year was $11.7 million, a 23% increase over 2016. According to IBM, 95% of cybercrime was caused by human error. This means that traditional rule-based sensors cannot prevent all attacks. To be effective, tools should be fully automated, learn from past attacks, and use AI to identify emerging threats.

AI can speed up the detection process

Artificial intelligence (AI) has many uses in cybersecurity. For example, it can detect cybercrime by analyzing the way that it is transmitted. AI can also detect phishing emails. These emails are used to spread malware or collect valuable information. As such, AI can speed up the detection process of cybercrime.

AI is extremely effective at detecting cybercrime because it can recognize patterns in large amounts of data. It can also help security personnel by reporting suspicious activities to them. The use of AI is particularly valuable because cybercriminals are constantly looking for ways to attack organizations. In addition, human security personnel can get bored and fatigued, and they may miss important network updates.

However, the use of AI for cybersecurity is still limited. Most companies aren't yet turning over their cybersecurity programs to AI. Although many vendors are leveraging AI to improve cybersecurity efforts, companies are not relying on it in large-scale deployments. Most AI is being used in a limited fashion for email filtering and malware identification.