AI Complicates Cybersecurity: Here’s How to Keep Your Systems Safer
Cybercriminals attack more than 2 million computers every year, robbing individuals and organizations over $4 billion annually. Unfortunately, one of the biggest enablers of cybercrime is also one of the most popular tech innovations of the past decade – Artificial Intelligence (AI).
How AI Enables Cybercrime
By definition, AI is a branch of computer science that focuses on the development and deployment of intelligent systems that can mimic human behavior. Key topics in AI include machine learning, speech recognition, and problem-solving.
All these are technologies that can aid the execution of a cyberattack.
Currently, for example, our adversaries rely on human resources to craft and coordinate attacks. But, through machine learning, they can automate the entire process. Similarly, just as we now look upon AI to complement human resources and cut overhead costs, so can cybercriminals.
It’s also possible to disguise AI cyberattacks such that they become almost impossible to recognize.
3 Common Ways AI Abets Cyberattacks
Automation of attacks
This is perhaps the biggest threat at the moment. Through automation, AI has the potential to accelerate the volume of attacks multifold. Distributed Denial of Service (DDOS) attacks, in particular, become super easy to multiply and expand through automation. Furthermore, AI makes it easier for cybercriminals to both preserve their anonymity and distance from the victims, thus seriously complicating investigations.
Makes password cracking easier
As already mentioned, one of the foundational topics in AI is machine learning (ML). AI robots are designed to “learn” from large datasets. It means that all criminals need is a large pool of real-life passwords to be able to predict high-probability passwords. Since getting real-life passwords on the black market is easy, people who use the same password on different devices or only alter the original passwords slightly are in trouble.
Increases the attack surface
In an effort to defend themselves better from attackers, organizations will, in the future, likely deploy advanced technologies, including AI and automation. These technologies create defensible “choke points” that are easier to secure. The problem, however, is that the more you automate, the more you expose your system to AI-enabled cyberattacks. Criminals can, for example, target your chatbots to interfere with customer relationships and internal decision-making.
Bolstering Cybersecurity in the AI Age
Organizations can act in different ways to contain new threats. The following are just a few steps you can take to secure your systems from AI-enabled cyberattacks while at the time boosting the overall security of your information systems;
Turn ML into a threat detection tool
Machine learning has proven to be very useful in the early detection of potential cyber threats. By continuously analyzing company data, you can identify potential risk before it exploits a vulnerability in your computer systems.
Think of it as proactively predicting threats. Rather than wait for an anomaly in the information system, machine learning equips the organization to adapt algorithms based on data received at every moment. Traditional technologies can help too. But, the difference is that machine learning can analyze tons of data per second. Also, traditional methods rely too much on past data. Machine learning, meanwhile, works in real-time.
Use AI in password protection and authentication
Some organizations have already automated password reset processes as a way of dealing with related hacking threats. Avatier, for instance, is an IT security company that provides IT security chatbots that automate password resets. Automating password resets not only helps users generate stronger passwords but also frees up IT support to deal with other threats.
Beyond Avatier and the ilk, organizations must also strongly consider solutions such as advanced biometric authentication. The iPhone X facial recognition software, known as Face ID, for instance, leverages AI to deliver a sophisticated, fool-proof way to authenticate users.
Use Machine Learning techniques to fight phishing attacks
Phishing emails are extremely prevalent. Today, out of every 99 emails sent, one is a phishing attack. ML can help you mount a fight against phishing attacks.
Artificial intelligence, for instance, has made it easy to differentiate between a genuine a fake website. When it comes to emails, AI, especially machine learning, can be vital in preventing and deterring potential attacks. First off, machine learning makes it possible to track more than 10,000 active phishing sources at a go. You can also react and remediate the attacks much faster. Additionally, advanced machine learning solutions can flag malicious emails with much higher accuracy than humans.
Leverage AI to manage vulnerabilities actively
Hackers tend to use known vulnerabilities to execute their attacks. Unfortunately, some of the vulnerabilities are impossible to eliminate. Some network patterns, for instance, are critical to the working of computer systems. And, yet, they are some of the biggest loopholes in any information system. In 2019 alone, there were over 2,000 well-known vulnerabilities.
AI can help organizations deal with some vulnerabilities. First, with AI, it’s possible to monitor activity on a computer system to identify anomalies closely. Secondly, AI makes it possible to take the monitoring to the dark web. Above all, you can also use machine learning to figure out common attack patterns. The information can then be used to determine when and how a threat might reach a potential target.
Get Ahead of Today’s Cybersecurity Threats with United Perfectum
AI cybersecurity threats are real. A few organizations have already paid the price for ill preparation. Don’t be the next victim. Partner with UP today to fully secure your systems.