Flashy sci-fi movies and talking robots may be the first things that come to mind when thinking of artificial intelligence (AI). But you may not be aware that AI is already all around us: from online purchase recommendations and self-driving cars to virtual assistants like Siri and Alexa and AI cybersecurity. Let’s take a look at how AI works.
Artificial intelligence is the science of making computers smarter. Complex algorithms allow computers to solve problems that were previously only solvable by humans. AI can learn to complete a specific task by going through vast amounts of data independently, a process that is called machine learning.
AI does have its limitations, as it cannot transfer skills easily or grasp abstract concepts yet. But when it comes to cognitive tasks, it can help us tremendously. Especially in fields that could use new technologies to relieve some of its existing limitations, like cybersecurity.
AI and Cybersecurity
Cyber security statistics show that the number of cyber-attacks is increasing every day. A recent study from the University of Maryland shows that one hacker attack happens every 39 seconds. It’s clear that present cybersecurity technologies aren’t 100% waterproof.
AI cybersecurity can complement cybersecurity experts by taking some workload off them. Machines are great at processing vast volumes of data quickly and picking out any strange or interesting information for people to examine. AI really is the building block for helping to discover cyber threats as it finds any issues quickly.
Threat Identification and Prediction
AI models can detect potential security threats, vulnerabilities, and malicious activities to stop them before causing any harm.
Examples of this are California-based Avata Intelligence, which uses machine learning and security to predict future terrorist threats. Deep Instinct is another global cybersecurity platform that uses predictive analysis to detect variations in known malware code.
There are two important aspects of network security: security settings and network topography. The first help differentiate legitimate and malicious connections, while the latter reduces the effect of disabled devices on the network’s performance.
Using AI in cybersecurity can help automate these procedures using network traffic patterns.
Password Protection and Authentication
Weak passwords are a huge security risk, making it easy for hackers to access personal details from your accounts. While having a strong password is a great first step, combining AI cybersecurity with biometric verifications can add an extra security layer.
An excellent example is the iPhone’s Face ID. The built-in infrared sensors and neural engines detect 30.000 different reference points across the face, forming a vector model of a user’s facial features. AI then matches it with the stored data to confirm your identity.
Passwords alone are a weak security measure since it’s comparatively easy for cyber attackers to access personal accounts. Even though biometric verifications are used today as a good alternative, it’s still not completely secure. Using AI cybersecurity with biometric verifications can help eliminate the existing issues. By reducing the number of unauthorized logins, this combination offers more security to your accounts and files.)
Avoiding Human Errors
While it’s human to make mistakes, the strengths of AI in cybersecurity systems lie in its precision, especially when performing repetitive tasks. Human error is one of the main causes of data breaches, and AI can avoid this.
It’s important to note that AI isn’t a replacement for cybersecurity experts, but they can work together to create better security tools.
Benefits of Using AI in Cybersecurity
With so many uses for artificial intelligence in cybersecurity, it brings many benefits, including:
Big Data statistics show that there are 40 trillion gigabytes of data in 2020. The internet is growing exponentially, and people can’t keep up with the vast amount of data created every day.
Because AI’s strengths lay in the speed and accuracy in which it can process data, it can help us filter through information to find any faults or dangers.
(One of the main concerns with present cybersecurity is the amount of data that needs to be processed. AI can solve this, as it processes data much quicker.
Statistics show that technology replaced 800,000 jobs between 2001 and 2015 in the UK, but it also created 3.5 million new ones. Automation creates more jobs and opportunities.
One of the main uses for artificial intelligence is automating easy and repetitive tasks in which humans tend to make mistakes. This gives the manual workforce time to concentrate on more critical jobs.
Identifying Small Cyber Threats
Cyber attackers use advanced techniques that make most threats go unnoticed by the human eyes. AI can recognize the slightest changes in network patterns and quickly identifies them.
Faster Detection and Response Time
AI detects incidents that can cause security threats in real-time and eliminate them quickly.
Websites that allow users to log in or make payments need additional security. Incorporating AI authentication methods like facial recognition can help with this.
With so many benefits that come with AI, it comes as no surprise that it’s implemented in many new cybersecurity technologies. Let’s now look at the latest trends.
AI Cybersecurity Trends
With an ever-expanding online world, cybercriminals are more active than ever before. AI is emerging as a game-changer in the cybersecurity industry, helping professionals create smarter security building methods.
Coming up are some of the latest trends involving artificial intelligence in cybersecurity.
AI Against Cyberattacks
AI learns from patterns and past behavior, which enables it to be a great cyber defender. An example of AI in security can be found in the defense against spam/phishing emails. Learning from previous data, AI can protect us from any malicious activity. That’s why most of the top antivirus suites take advantage of AI.
AI in Improved Ecosystems
We can use AI’s contextual understanding to detect false-positives, helping businesses build a more secure cyber ecosystem. Utilizing AI cybersecurity lifts some work off any company’s security teams, allowing them to focus on tasks that require a human mind.
AI in EWS
Early Warning Systems (EWS) has been used against cyber-attacks for a long time, but as the level of cyber threats increases, it needs some help. Combining traditional EWS with AI can create virtual sensors and sophisticated data manipulation for logic models.
These concepts can improve AI’s reliability, scalability, flexibility, and use against cyber threats. We can use AI to detect attacks from LANs and WANs to protect the network protocols from malicious activities.
Generative Adversarial Networks (GANs)
Generative Adversarial Networks are two AI systems competing against each other. One of them simulates original content, whereas the other spots its mistakes. This technology helps improve cybersecurity systems and other networks alike.
Is Artificial Intelligence a Threat?
So far we’ve looked only at the benefits of using this technology. Still, hackers using AI can be of great concern.
Hackers can develop AI-resistant malware using the same technology. This type of malware can understand the detection patterns used by cybersecurity professionals, allowing them to penetrate even the most secure solutions.
Cyber attackers can target data used to train the AI cybersecurity models. This threat can affect both the accuracy and performance of cyber threat detection systems.
AI is still in its infancy. When used in cybersecurity, it has a lot to learn and process. Therefore, the chance of false-positive results is relatively high.
Integrating AI and cybersecurity is the way forward, considering the increase in cyber attacks worldwide.
AI can help the current cybersecurity technology automate threat detection and track down potential cyber-attacks within a limited time frame. Considering the robust and flexible characteristics of AI cybersecurity, it’s for sure that it can build a robust defense system.
But we can’t ignore that AI can also help malicious actors create new cyber threats. Even though AI has a long way ahead to reach its full potential, it will help us in unimaginable ways.
The four types of AI are:
- Reactive Machines: These basic AI types make basic predictions but cannot make decisions based on memory. For example, it can predict its opponent’s moves on a chessboard by identifying the pieces and choosing the most optimal moves, but not from previous activity. These machines can’t function beyond the specific task it has been assigned to, and cannot interact with the world.
- Limited Memory: This type of AI can use memory to make decisions. Self-driven cars are classic examples: limited memory AI remembers things like lane marking on roads and traffic lights to avoid accidents.
- Theory Of Mind: In a more advanced form, AI can form representations and understand other creatures and objects in the world.
- Self-Awareness: The last AI type can form representations about themselves. As humans, it’s aware of itself, its feelings, and can predict how its actions will affect others.
Combining AI and cybersecurity offers a variety of highly intelligent security tools. AI analyses patterns in data on past cyber incidents to identify potential threats. This will help security professionals to concentrate more on the crucial processes.
AI cybersecurity also predicts future cyberattacks, assures network security, password protection, and authentication by creating an efficient defense system against cyber attacks.
AI can be a blessing and a threat to cybersecurity systems. On one side, combining AI with cybersecurity can improve efficiency, performance, flexibility, scalability, thereby defeating potential cyber threats and combats.
But on the other side, cyber attackers can use AI to prey on the system’s vulnerability and create new types of cyber threats.
Artificial intelligence improves cybersecurity in many ways, including faster data processing, security database updating, automating repetitive tasks, reducing the error rate, and improving the authentication practices. It can also help prevent cyber threats by identifying unusual activities.
Statistics show that 5.8 billion automotive and enterprise gadgets will be on IoT by the end of 2020. As the number of IoT devices keeps increasing, so does the risk of potential cyber threats.
Therefore, the opportunities for artificial intelligence in cybersecurity are plenty. With the growing popularity of cloud-based solutions, the need for AI cybersecurity will inevitably rise too.
With all of this in mind, AI cybersecurity’s value is expected to reach $40.61 billion by 2026 from $4.89 billion in 2018, growing at a CAGR of 30.12%.