The bright and dark sides of AI in cybersecurity

The bright and dark sides of AI in cybersecurity

With the influx of IoT devices in enterprise networks, migration of services and applications to the cloud, and integrations with several third parties, enterprise security has become incredibly complex. The surface area for cyberattacks has expanded, allowing attackers to exploit more and more loopholes in your network. This creates an urgency to formulate preemptive defences that can predict attacks at their earliest stages and nip them in the bud.

Artificial intelligence (AI) is fast becoming a panacea for everything digital. And its infusion into cybersecurity is being recognized as the best way to implement preemptive defences against threat actors. However, it's important to understand that AI's broad spectrum of capabilities can also be leveraged by attackers to up their ante. This blog covers how AI can be leveraged by both sides when it comes to cybersecurity.

AI as the white knight in cybersecurity

The benefits to having AI cybersecurity solutions are manifold. From insightful ways of predicting cyberthreats to performing routine security procedures, AI can simplify our approach to enterprise security. Here are some solid benefits to having AI-infused cybersecurity

Creating an asset inventory: AI can help you acquire a full inventory of all your network assets like servers, devices, and users. It can also help you categorize these assets by how critical they are to your business operations.

For example, AI can classify important servers with sensitive information as high priority. This helps security operations center (SOC) analysts better understand the network architecture and implement more stringent security for high-priority assets. This reduces the overall risk of exposure and not only saves the company monetary losses but spares them from legal consequences in the long run as well.

Extended scope for threat intelligence: AI can detect and analyze fragments of malicious code, learn from these fragments, and store this information to detect similar threats down the line. AI can also build threat forecasts based on new developments in the cybersecurity sphere. AI can be used to develop anticipatory intelligence by training it on historical data.

For example, AI can be trained to learn malicious IPv4 addresses. It can then predict IP addresses that have a close resemblance to known malicious IPs and identify them as addresses belonging to threat actors. This helps SOC analysts block potential malicious IP addresses before any intrusion takes place.

Enhanced incident response: AI can help build comprehensive context for security incidents. Seemingly random events across your network can sometimes be related. AI can determine if these individual events have a connection that indicate a serious security incident. This helps improve how security alerts are prioritized, leading to faster responses and better threat mitigation.

Automation of routine security tasks: Human effort in cybersecurity should be used for innovative tasks like building strategic defences for the network. Meanwhile, AI solutions can perform more routine tasks like security incident responses and management. Root cause analysis of security incidents can also be automated using an AI-based cybersecurity solution to improve the incident response time.

Breach risk prediction: Taking into account your IT assets, the security measures in place, and your company's data exposure to third parties, AI can predict the risk of your organization being breached. AI solutions can also identify weak spots in the network that need more attention, helping you can plan your security strategy accordingly.

The dark side of AI in cybersecurity: Believe it or not, AI can also be a bad penny when it comes to cybersecurity. Deepfakes are images and video that use AI's deep learning technology to create fake media—for example, a fake video of a CEO sharing false information about a company. Deepfakes can replace the face of a random person in a video with the face of a company CEO. This could have dire consequences for the company.

Constantly evolving threats: Attackers are innovative beings, constantly upping the game by devising new ways attacks can be carried out. Even if you have an AI solution in place for your security, it has to be retrained constantly to be able to detect and fend off new threats.

AI-based cyberthreats: Attackers can get their hands on AI-based cybersecurity solutions to test their malware. This helps them create a strain of malware that is resistant to AI's protective measures.

Adoption difficulties: AI cybersecurity solutions require high computation power when compared to existing defence solutions. It seems far easier to use traditional cybersecurity software than to train and build AI solutions that are tailored to your organization's security requirements.

Based on an analysis of what AI has to offer, AI has many benefits to offer to your organization's security. AI solutions are becoming more and more available, and over the next decade, we'll likely see easier ways for even small businesses to adopt AI as part of their security defenses.

If your organization's security budget and human resources can take on AI-based cybersecurity solutions at this point in time, we strongly recommend doing so, because it will be a good long-term investment. When attackers are leveraging AI, so should organizations.

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