two people programming cybersecurity

Will AI and Machine Learning Replace Humans in Cybersecurity?

As businesses, individuals, and organizations depend more on the conveniences provided by internet capability, the cybersecurity world grows more complex. Hackers develop more complicated and expensive techniques, and cybersecurity experts work tirelessly to mitigate these threats with more advanced software and techniques before valuable data is breached.

Becoming a more globally connected world provides efficient ways for businesses, governments, and various industries to become more efficient and successful. However, it doesn't come without costs. Internet capabilities, the internet of things (IoT), and dependence on remote communication provide new ways for cybercriminals to access data from distant locations without being detected. 

In recent years, many industries have struggled with creating an improved work/life balance for employees that included remote work and flexible hours. This process has been admittedly slow and cumbersome, partially due to the security risks involved. Recent changes to the world fast-tracked the leap into remote communication for practically all industries. With tight regulations and stay-at-home orders put in place across the globe, businesses, organizations, government offices, and schools had to scramble to find ways to adopt remote policies immediately. Unfortunately, this process included flaws that cybercriminals were prepared to take advantage of. 

As businesses adapted a deluge of new devices were introduced to the business, healthcare, and government networks. Many security software programs depend on algorithms that detect deviations from normal behavior to alert users of potential threats. During the transition to remote work, systems were drowning in unusual behavior, because "normal" from practically all employees is unusual when compared to past behavior within the organization. 

When all behavior is a deviation from normal behavior, machine learning software generates an abundance of false positives that block normal commerce and daily tasks from being completed. For most systems, numerous false positives result in one of two behaviors. Either the human analysts tasked with the investigation of alerts become overwhelmed, or the system threshold is raised to eliminate false positives from triggering the system. The system cries wolf too many times, and the company stops listening. This gives threat actors the perfect opportunity to sneak into the network undetected. 

Technically speaking, the AI systems were working as intended. However, machine learning can't determine the difference between in-company changes and the unusual behavior that indicates criminal activity. Most AI systems depend on what employees have taught them, making them unprepared for the dramatic shift in behavior. Internet use is always expanding. As a result, the cybersecurity world is ever-changing. Human employees will always be an integral part of the AI cybersecurity solution to teach AI systems to handle mundane tasks and maintain the system. 


How AI and Machine Learning Enhances Cybersecurity

While AI-enhanced systems didn't have a perfect answer to cybersecurity threats during the harsh transition to remote work presented by the pandemic, these systems worked better than those without machine learning. Cybersecurity systems without AI had only immediate manual interventions to stand between them and sophisticated threat actors prepared to take advantage of a bad situation. 

There's no doubt that AI and machine learning provide the necessary benefits to detect and prevent cybercriminals from exploiting vulnerabilities. Machine learning eliminates hours of tedious tasks, allowing your team to concentrate on other department roles. AI also can adapt to a variety of threats presented by advancing cybersecurity risks. AI adds these benefits to your complete cybersecurity solution. 

      • Even for small businesses, networks log thousands of entries for many devices. Machine learning software sorts and categorizes data in seconds that would take humans hours to navigate. 
      • A combination of programs allows AI systems to recognize the behavior of modern changing attacks and triage threats to begin remediation immediately. 
      • AI removes tedious tasks, helping to eliminate burn-out and allowing professionals to focus on cyberattack mitigation and preventative measures. 
      • AI performs a variety of tasks that would require an extensive team of IT professionals to complete with the same results. For many small and growing businesses, cybersecurity wouldn't be possible without software that includes machine learning. 
      • Cybersecurity software that incorporates machine learning can be programmed to meet the compliance requirements of industries like healthcare and higher education organizations for a two-fold solution that lowers security risks and eliminates the consequences of non-compliance. 
      • AI eliminates the technology gap that most organizations face when learning about the details of cybersecurity. 

Why Humans Are Still a Necessary Part of Modern Cybersecurity

AI provides many benefits, but it's not a complete cybersecurity solution. Threat actors continually find ways to adapt to machine learning and use it as a tool to confuse networks and evade detection. Professional human security analysts have intuition and the knowledge to predict human behavior and anticipate criminal behavior and the reasons threat actors target certain organizations. There isn't a way to introduce the creativity of humans to machine learning. 

It's no secret that IT and cybersecurity require a precise skill set and attention to detail. Yet, it often comes as a surprise that cybercriminals are intelligent individuals who work under the same technological conditions. When faced with firewalls, machine learning, and end-point security features, cybercriminals target human employees as an entry point into the network. Phishing emails are difficult to detect under normal circumstances. 

The pandemic created a perfect atmosphere for cybercriminals to take advantage of "fear ware". By preying on the fears of employees and consumers, threat actors can quickly entice users to click a link or download instructions. For instance, when you receive an email suggesting an important account is frozen, a common panicked response is to resolve the problem immediately by doing exactly what the email suggests. This technique was amplified when cybercriminals targeted healthcare facilities during the earliest phases of the pandemic. Made to appear official and claiming to contain vital information about the COVID-19 pandemic, hackers send emails that contain attachments or links that launch the ransomware. When employees open these emails, follow links or download attachments, they provide cybercriminals with a disguised entry into the network. To thwart these attempts at different levels within the system, cybersecurity professionals must coordinate multiple security modules that depend on different algorithms and monitor the system consistently for new threats. 

In the world of cybersecurity, humans augment a variety of software types, some of which include AI, to complete the tasks needed for a robust cybersecurity system. Human professionals set up AI systems, modify them, individualize them to work for each organization. and monitor systems to adapt to new threats as they arise. Human intuition and creativity will always be a part of the battle against growing cyberattacks. 

5 Ways Software Fails to Protect Organizations Alone

Cybersecurity software contains a variety of advanced programs designed to protect sensitive data from threat actors. The software has AI learning capabilities to assist in detecting and eliminating new threats. However, out-of-the-box cybersecurity software isn't prepared to eliminate threats alone. For the advanced results required by most organizations, the software should be programmed to work with the network, individual workings, and daily functions of an organization.

The majority of executives and CEOs of any organization aren't cybersecurity experts. After all, individuals in top management positions already have a full schedule and countless responsibilities related to running a company. When administrators purchase software to avoid cybersecurity risks but don't have an internal cybersecurity team to deploy and maintain the programs, failures result. 

Out-of-the-Box Software Only Provides Minimal Settings

The idea of simply purchasing and downloading cybersecurity software for complete protection is an attractive one, but it's not realistic. Cybersecurity software that uses AI and SIEM technology is designed to learn to work with your business or organization. Without cybersecurity experts to handle the installation, the software only responds to basic threats. 

AI Produces False Alarms

Machine learning requires a training period for the system to establish a baseline of normal behavior. During this window, security analysts become overwhelmed with false alarms. All too often, the response to this problem is to change the security settings creating a weaker defense. When false alarms continue, the IT team becomes numb to them and fails to react to genuine threats. 

Without Updates, Software Is Inefficient

Cyberthreats evolve continually. For every advancement in security, threat actors find new ways to exploit protections and create new vulnerabilities. When a security company discovers vulnerabilities, a software update is released. Most companies don't install these updates right away. Without updates, the software (even with AI capabilities) can't perform efficiently.

AI-Enabled Software Can Provide False Confidence

Placing complete confidence in cybersecurity software can lead to relaxed security standards by an organization's executives and employees. If the software isn't optimized to provide proper security standards or isn't updated to prevent modern threats, this confidence can make it easier for threat actors to access the system. When this confidence includes the expectation that software is set up to meet specific compliance requirements, non-compliance fines and penalties can result. 

Cybercriminals Can Use Machine Learning as a Resource

Creating and using malware, ransomware, or other cyberattacks isn't an easy business. Cybercriminals are technologically advanced hackers with the knowledge to adapt to and use, new technology to reach a modified goal. For instance, a threat understands security software can find ways to inundate an organization's network with false alarms to camouflage unusual behavior or use phishing or whaling techniques to access the system through an approved source. 


How the Human Factor Combines with AI and Machine Learning for a Complete Solution

There's no question that AI-enabled software can complete tasks that humans can't and that humans can accomplish goals that AI software can't carry out alone. So, how do businesses and organizations find a complete cybersecurity solution that actually works? The answer is a cybersecurity team that uses a variety of techniques and tools to protect an organization's network at every level. 

The truth is, most organizations and businesses can't afford to hire an entire in-house team dedicated to cybersecurity. Furthermore, an in-house security team is rarely the most economical solution available. Security Operations Center as a Service (SOCaaS) is a security operation center outsourced by an external company to use the most up-to-date technology and cybersecurity techniques to manage your internal security. When human intuition combines with AI, a more comprehensive cybersecurity solution evolves. Here's how the human factor works to make AI-enabled cybersecurity software an asset instead of a singular tool. 

Humans Are the Intelligence Behind Computers, Software, and AI

Humans are the ones who built computers, designed software and provide the intelligence behind AI. Humans are the starting point for all cybersecurity software including AI. The human brain is required to provide advanced programming and renewed knowledge to AI systems. Simply put, machines can't evolve and learn without assistance from humans. 

Successful Cybersecurity Software is Deployed by Security Professionals

When a cybersecurity system is introduced to the network of an organization or business, it should be optimized to understand the goals of the company and data that should be protected. Security professionals prioritize protection systems and introduce policies for the system to follow. AI systems can't generate this initial planning phase without human intervention. 

How cybersecurity software is configured will provide a balanced system that uses a growing knowledge base to address potential threats and stop active attacks.

Developers connect information sources that allow adaptive algorithms without creating additional risks and vulnerabilities. They introduce government security standards to help organizations maintain compliance. They also determine how much of the system should be automated, which has a major impact on false alarms and unnecessary quarantines or other emergency responses. When cybersecurity systems are optimized by experienced security professionals, they adapt to an organization's data systems and normal behavior. 

Successful Security Systems Are Run by Humans

Within any company, IT teams are required to complete a variety of technical tasks each day. Unfortunately, these tasks can't be limited to cybersecurity. An external SOCaaS team works with an internal IT team to keep a successful cybersecurity system running without vulnerabilities. Many companies across all industries, and even government agencies, have experienced the vulnerabilities that can be created through human error. Machine learning can't predict human behavior to help eliminate the vulnerabilities caused within an organization's network. An efficient SOCaaS team helps companies eliminate poor cybersecurity practices to avoid creating internal vulnerabilities that can be exploited by threat actors. 

Humans Monitor and Defend the System

AI-enabled systems are only as smart as the professionals who keep the system up-to-date and intact. Cyber professionals continually educate themselves on changing and growing cybersecurity threats so they can protect the agencies that depend on them. Humans update systems with new knowledge to eliminate advanced and persistent attacks from cybercriminals seeking sensitive data. The growth of technology and growing businesses mean that new devices are continually introduced to the system. Security professionals coordinate these devices to integrate seamlessly into the system without triggering false alarms. The relevance of any AI-enabled security system depends on the information it receives. Cybersecurity professionals adjust logs to provide relevant information and eliminate false reports.

Humans Create and Introduce Updates

A good security system evolves overtime to keep up with advanced and persistent threats from cybercriminals. Without updates and patches, an AI-enhanced system will quickly become outdated. Software developers continually improve programs to eliminate vulnerabilities. Security professionals introduce these updates in a timely fashion to keep systems running properly.

Security Professionals Anticipate Human Behavior

Advanced cybersecurity software uses algorithms to detect known criminal behaviors and deviations from normal behavior within a network. Security experts introduce this information to the system after learning of existing threats. However, detection alone isn't enough to provide a complete cybersecurity solution. Cyber threat hunting is the process of searching for signs of weakness that cybercriminals could exploit. Cyber threat hunting is an activity that can't be completed by artificial intelligence. It's an ongoing investigation of potential and current attacks where humans anticipate an adversary's potential behavior to eliminate risks before serious breaches occur. 

Humans Make Decisions During an Incident

AI provides machines with the knowledge to detect possible threats, send out alerts, and even take some actions to prevent malicious activity from moving further into the network. Yet, machine learning doesn't give a computer the capability to make decisions based on facts and intuition about a company or organization's inner workings. We know that AI produces a variety of false alarms because cybersecurity professionals and IT teams see these occurrences in action. Security professionals then use the information to fine-tune systems and improve software, so fewer alarms are triggered. Even the act of raising or lowering alert thresholds must be done with careful human research and human intuition to understand the dangers of making too many changes to the system. 

When a security system sends out an alarm, security professionals immediately get to work to determine whether the alert is indeed a threat and the steps needed to neutralize the dangers as quickly as possible. The work of the cybersecurity team isn't complete when the immediate danger subsides. Instead, measures must be taken to determine why the system was insecure and ensure additional vulnerabilities haven't been created. If a new vulnerability exists, cybersecurity professionals use the information from an attack to create stronger security for all the other organizations, businesses, and agencies they protect. 

Security Professionals Coordinate Multiple AI-Enabled Programs

As technology advances, cybercriminals use more complex and sneaky methods to break down the defenses designed to stop them. Cyberattacks are bigger than ever before, with higher stakes and more agencies becoming a target. Security professionals match these growing threats with the use of combined techniques and the assistance of a variety of software programs to keep up with massive data streams within a network. However, introducing multiple types of software to any system isn't easy. Not only does cybersecurity software need to coordinate with the existing programs designed to complete daily tasks within the organization, but it also has to play nice with other cybersecurity programs for a complete solution. Human learning and creativity are required to create and introduce multiple programs to a network that work together instead of creating additional issues. 

Humans Communicate with Other Humans

Technology is constantly growing and changing. New types of software, technology terms, and cyber threats are consistently introduced to businesses and organizations. Keeping up with the complicated details of today's technology is a major reason for the limited cybersecurity knowledge that exists today. While machine learning and AI-enabled systems help to bridge the technological gap, they can't communicate with people in the same ways that other humans can. 

External security teams use advanced software to detect and eliminate cybersecurity threats. They also communicate and work with internal IT teams that have a deep understanding of the organization's network and the devices used within a facility. A qualified external cybersecurity team can work with IT teams on different levels to provide the amount of support the organization needs and communicate safe cybersecurity practices to enforce the efforts of the cybersecurity system. 

Managed Detection and Response for a Complete Cybersecurity Solution

As a business or organization trying to protect your network from growing cybersecurity threats, it can be difficult to determine the best course of action. Finding capable software doesn't necessarily mean the network will have complete protection without a qualified team to monitor and defend the system. Managed Detection and Response (MDR) offers the best of both worlds with an external cybersecurity team that introduces machine learning and AI-enabled software to your organization's cybersecurity efforts. Still, MDR security providers aren't all the same. Each provider may offer different services and various types of software that can be difficult for businesses to understand. 

When searching for the right MDR provider for your organization, it's important to gather as much information as possible. Researching different companies can provide you with some answers about different vendors and the levels of security they provide. Direct communication with a potential MDR security provider will shed more light on the services that will provide a robust security solution that can change and grow with your business or organization. For more information about choosing a managed detection and response provider for your company, contact us today.


Jason Miller

Jason Miller, Founder and CEO of BitLyft Cybersecurity, has dedicated his 20-year IT career, including co-founding SaaS pioneer Reviora, to removing cybersecurity barriers for mid-sized enterprises. Establishing BitLyft in 2016, Jason set out to unburden security teams with innovative, approachable, and affordable solutions, a vision which has made BitLyft a respected managed detection and response provider. Outside his cybersecurity pursuits, Jason is an avid tree farmer and outdoor enthusiast, planting nearly 300 trees on his ten-acre plot and finding joy in hiking, hunting, and driving his white Tesla Model 3. His diverse passions mirror the balanced blend of expertise, dedication, and joy he brings to BitLyft.

More Reading

two men looking at a screen
How Can User Behavior Analytics Protect Me?
The human element is the hardest to control in cybersecurity. A network can have the best security system in the world, but if users leave the door unlocked, it won’t protect them. Whether it’s...
security engineer in an operations center looking at their computer
SOC-as-a-Service: What You Need to Know
Cybercriminals today have become more advanced and sophisticated than we could’ve ever imagined in the past. They are no longer lone wolves finding exploits in systems and exploiting them for...
man working on a computer
Top SIEM Products for Cybersecurity
When facing a cybersecurity incident, there is nothing more important than managing the event before things get too out of hand and end up costing your organization time, money, or damage to your...