How Will Artificial Intelligence and Cybersecurity Be Seen Moving Forward?
Artificial intelligence (AI) in cybersecurity can be a double-edged sword. While AI can effectively mitigate threats and prevent potential cyberattacks, criminals can also exploit the technology to their advantage – putting businesses and customers at significant risk. This, in turn, increases the need for greater security and protection.
We’re still dealing with the side effects of COVID-19, not only the pandemic itself but also the increased cases of cybercrimes happening worldwide. Cyberattacks are on the rise, with the recent Colonial Pipeline and Pulse Secure VPN attacks being added to SolarWinds and Microsoft Exchange Server as notable attacks with far reaching consequences.
Cybersecurity Threats Continue to Evolve
In 2020, the United States experienced 1001 data breach cases, and 155.8 million individuals faced data exposure (accidentally revealing sensitive information). The FBI saw a fourfold increase in cybersecurity complaints during the COVID-19 outbreak, and according to a recent McAfee report, global losses due to cybercrimes have surpassed $1 trillion.
Cyber threats continue to become more sophisticated, as malicious actors have learned to use AI more effectively, including initiating attacks and gathering business intelligence. Even more nefarious, they use AI to conceal malicious code that is programmed to execute at a later date and create intelligent malware programs that can adapt accordingly during an attack.
What Role Does AI Play in Cybersecurity?
With more online activity and devices being used today than ever before, it can be challenging to defend your business against unknown threats. Advanced cloud features, the 5G rollout, and the internet of things (IoT) continue ramping up around the world and cybercriminals are constantly seeking ways to take advantage of unsuspecting users. To better protect their networks and users against cyberattacks, organizations are turning to AI and machine learning to detect and respond to threats in real time.
The amount of data that exists today is beyond what humans can monitor and defend. A self-learning, AI-based cybersecurity management system is increasingly necessary for businesses to effectively protect themselves against threats. Technology can work continuously, gathering data across information systems and analyzing it to expose dangers, inventory IT assets, predict breach risks, respond to security alerts, and more.
AI can analyze mass amounts of data at lightning speed to detect security threats in real time or predict potential threats before they occur. By consuming data from various sources (structured and unstructured), machine learning techniques can help AI better “understand” cyber risks, empowering security analysts to respond faster to threats.
According to IBM, secure AI applications can provide greater accuracy in threat detection and proactively safeguard against ensuing threats. Businesses can incorporate advanced AI technology to evaluate risk levels of specific users for specific sessions. By monitoring behavior, systems can continuously verify risks and respond accordingly.
Today, AI is being used in cybersecurity in the following common applications:
- Threat Prevention: In order to guard against threats, this technology learns every day about the billions of URL’s, Domains and IP addresses across the internet and knows which are dangerous or have a bad reputation. This continually updated intelligence is used in cybersecurity solutions to ensure that downstream, devices and networks are protected.
- Virus Protection: Antivirus software, included in cybersecurity solutions, uses advanced AI to anticipate, detect and instantly block even the newest threats before they can cause damage to downstream devices and networks. It learns about new actual and potential threats every single day.
- Web Filter: Web filtering technologies use AI intelligence to sort billions of URLs (websites) into categories. These categories are updated every day and are used to ensure that devices and networks are safe, but also used to optimize for what should be prioritized (or allowed) on networks. For example, schools will want ‘sensitive’ categories to be blocked. Every day, new websites become available, and AI technologies find them, categorize them and allow control over them to protect and optimize business networks and devices running on them.
- Email protection: This technique focuses on the content of emails and constantly learns about new actual and potential malware attack attempts. Cybersecurity products, such as Untangle, use this technology to ensure that spam, malware, phishing scams and other types of dangerous attempts to cause harm through emails are blocked.
Barriers to the Adoption of Artificial Intelligence in Cybersecurity
Many SMBs realize the pros to AI are numerous, however, they still believe there are barriers to introduce more AI cybersecurity measures to their organizations. Most cited are the skills gap in IT professionals who can implement and manage the more sophisticated programs and an insufficient budget for AI technologies. However, as listed above, there are numerous cost effective, robust platforms for SMBs to include in their network security platform.
The Cost of Cybersecurity for Businesses
The costs of a security breach can reach millions of dollars, much more than the costs to implement proper network security measures, yet many companies are slow to make the investment. However, cybercriminals are becoming increasingly sophisticated by using AI in their attacks. To “fight fire with fire” and stay ahead of these attacks, companies must incorporate AI into their security solutions. Once only thought to be available for large organizations, SMBs can also employ AI technology to keep their networks, employees and valuable data safe.
