Among all the technological changes that are transforming the world of cybersecurity, one of the most revolutionary developments is artificial intelligence (AI). The need for cybersecurity is increasing as we do more of our business and other aspects of our daily lives online. Whether on the individual, organizational, or even national level, failure to properly secure information can be devastating. At best, it is highly embarrassing and can destroy a company’s or government’s reputation. At worst, there can be catastrophic financial and even physical costs. This means that cybersecurity is to be taken seriously, and any tool that can enhance it is a welcome development for cybersecurity experts in their quest to stay one step ahead of cybercriminals. AI can play a number of roles in good cybersecurity, changing the way it operates.
The Traditional Approach
Before the introduction of AI, cybersecurity relied on a number of different approaches, all of which continue to play a part. Signature-based detection systems compare incoming traffic to a database of known threats and malicious code signatures. This was an effective approach against existing threats but did not deal with new threats, allowing the systems to be easily bypassed by cyber criminals. Additionally, it would cause a lot of false positives, as legitimate traffic sharing any similarities with threats would be flagged as a problem. These false positives took time to investigate, taking time and resources away from dealing with the genuine threats.
Rule-based systems set up rules for a network, triggering an alert on any incoming traffic that attempted to break the rules. This is effective in many situations, but it is inflexible and does not adapt well to new threats.
The manual analysis relied on people to investigate logs and alerts. While this is effective, it is also time-consuming and not always adequate for dealing with the sheer number of threats. Additionally, it relies on the expertise of the individual. If the individual with the most expertise was away from the office due to illness or vacation, security was not as tight. Employees often move on – seeking promotion opportunities, new careers, or retiring – and it may take time to find or train someone to the same level of expertise and familiarity with the system.
Are People Still Needed?
One of the common fears about AI is that it will take jobs away from people, causing mass unemployment. On the face of it, this fear seems logical. AI is when computers, not people, carry out activities that previously would have required a human intellect. There are different subsets and levels of AI. Assisted intelligence can utilize data to help carry out tasks, while augmented intelligence creates solutions by combining existing intelligence with new data. However, the most advanced form of AI – autonomous intelligence – does not require human interventions, so is the most revolutionary aspect of AI its potential to do away with human cybersecurity teams?
The short answer to this is no. The longer answer is that, in fact, the opposite is true. Cybersecurity is a growth career with increasing demand for experts. AI is a revolutionary technology, but it is not able to replace humans. Instead, it automates some of their tasks, freeing them up to concentrate on the more complex problems.
With good long-term job prospects and the chance to work with cutting-edge technology and tackle criminals, it is not surprising that cybersecurity is an appealing career choice for tech experts. If you are wondering how to become a Cybersecurity Specialist, a good place to start is to look at courses available. The Masters in Cybersecurity from St. Bonaventure University Online provides a flexible option through 100% online study, including cloud-based labs where students can tackle real cybersecurity challenges. Cybersecurity courses of any level are a good way to keep up to date with the latest technological developments, including AI, and how they are used in cybersecurity.
Identifying An Attack
AI can be used to monitor network traffic, checking for anomalies or irregularities that might suggest an imminent attack. It is able to do this through monitoring a vast amount of time series data, learning what is typical and what constitutes unusual behavior. This allows the cybersecurity team to take appropriate action quickly before an attack can be effective.
If a specific cyber-attack is known about or expected, cybersecurity teams can use AI to set up an alert, allowing the cybersecurity experts to take preemptive action to block an attack before it takes place. AI can also detect new threats by recognizing common features and behavior patterns from its existing knowledge.
The ability to use AI to carry out these tasks is transforming cybersecurity with its ability to provide consistent, around-the-clock monitoring every day of the year against both known and new threats.
Malware Detection
Malware is malicious software that can harm systems, requiring prompt identification and classification to prevent damage. Unlike a signature-based system and traditional anti-virus software that can only identify known malware, AI analyzes files and documents and can identify both known and new malware through its characteristics, behavior, and signatures. It does this by learning the typical features and patterns of malware through training on large datasets and identifying new variants of malware that emerge based on their similarities to known malware. As with other forms of cyber-attack, prompt action will reduce or even prevent damage, and the 24/7 malware detection that AI can provide helps with this.
The endpoints of a network are often the most vulnerable, and AI-powered endpoint security solutions are used there to set up alerts, identify malware, and create the baselines for acceptable network behavior.
Phishing And Fraud
Phishing emails are commonly used to trick individuals into revealing sensitive information, such as financial details, or installing malware on their computer systems. An AI-powered phishing email detection system analyzes patterns to distinguish between a genuine email and a phishing email. Phishing emails often use tricks such as copying a company logo to appear legitimate, and an AI-powered system can spot these details.
Any fraud, whether it is taking financial details or using personal information for the purpose of identity theft, is devastating for individuals and organizations alike. No matter what form the fraud takes, AI analysis of behavior patterns and transactions can help in the identification of fraudulent activity.
Security Logs
Traditionally, logins to a network or part of a network have relied on a rules-based system to detect unauthorized access. But the effectiveness of this is limited, particularly when dealing with new threats, as they rely on knowing the threat signature.
AI can be used on a number of levels. It might simply be used to check biometric data if facial recognition or fingerprint scanning is used to authorize access. But it can also manage more sophisticated monitoring, such as analyzing behavior patterns such as keystroke analysis or mouse movement. This has the added advantage that it can continue to monitor usage even after the initial login, alert for any change in behavior or unusual access requests, as well as activity devices that do not have authorized access.
Although much of the focus of cybersecurity is to be alert for external threats, there can also be threats from within. Corporate espionage or the planting of a thief inside an organization might sound like the stuff of the movies, but that does not mean it cannot happen in real life. And the threats from within – whether motivated by greed, malice, or incompetence – can be harder to spot than external threats since employees will already have login information and perhaps their biometric data stored, ready to grant them access. They might also have plausible reasons for their access request, making their attempts appear unremarkable to a quick check.
An AI system can monitor the usual activity across the business or organization on both a large scale and the usual activity of individuals. This will raise an alert if there is unusual activity, such as attempts to access data they would not usually access, unusual requests for information, or simply a longer login than is typical or a login at an unusual time. If an alert is raised, further investigations can promptly take place. If there is an insider threat, action can be taken to secure the information and prevent a data breach.
Detect Vulnerabilities
Even if a data breach does not cause significant damage, the fact that it occurred at all can damage an organization’s reputation. Clients do not want to trust their sensitive information to an organization that does not have the highest possible defenses. Detecting vulnerabilities means that an attack can be stopped before it takes place, safeguarding an organization’s reputation.
AI can help with this by learning from datasets with known vulnerabilities and using this knowledge to check new applications and software. It can then apply the necessary updates to address any weaknesses in the system or files. By having this automated vulnerability detection and patching, security checks can be regularly carried out, and security can be kept at a high level.
Automation
One of the most revolutionary aspects of AI in cybersecurity is the way it has allowed the automation of many routine tasks.
This results in a far more effective system that can maintain its efficiency consistently without slowing down for weekends or holidays. This also takes some of the pressure off cybersecurity teams. With AI focusing on so much of the data analysis, cybersecurity experts can concentrate on finding solutions.
Scalability
Business needs change all the time, and one problem with any system, including the cybersecurity system, is that it can take time to catch up regardless of whether there is a need to increase or decrease activity. During that delay, there can be inefficiency and vulnerabilities that need to be addressed. Data today is produced at a phenomenal rate, and many traditional analysis methods have struggled to keep up.
AI is easily scalable, adapting systems to an increase or decrease in demand. It easily handles the amounts of data produced across a variety of digital eco systems, including Internet of Things networks, cloud environments, and interconnected networks. From threat detection to responses, the scalability of AI allows it to act quickly in real time to tackle threats.
Changes In Cybercrime
While AI has revolutionized cybersecurity in many positive ways, it has also brought changes in the worst possible way. Cyber criminals, too, have access to AI and can use this technology to facilitate their crimes.
Criminals may use AI to develop ever more sophisticated forms of malware that can do even greater damage to systems. The automation that can boost the efficiency of organizations can be used by cybercriminals to automate fraud, expanding their reach to target increasing numbers of individuals and organizations.
We may also see AI against AI as cybercriminals use AI to manipulate systems to help bypass the safeguards AI systems have put in place. Tricks such as creating diversions to deflect attention away from the security breach and imitating normal patterns to hide malicious activity may become more commonplace.
AI-generated phishing attacks are often more sophisticated than those that are manually generated. In the past, such attacks were often clumsy, with obvious errors that exposed the scam. However, an AI-generated phishing email may be more indistinguishable from a genuine one and may convince more people to hand over sensitive information.
The solution to this is to encourage more IT experts in cybersecurity to develop technology that is one step ahead of the criminals and that can adapt to these new threats.
Limitations Of AI
While AI is revolutionizing many aspects of cybersecurity, it is important for cybersecurity experts to be aware of its limitations. AI bases its knowledge on existing data and can often identify a new threat based on similarities to previous attacks. However, this does mean that a truly unique threat could escape detection from AI. Such a threat may also need creative solutions, and while AI is remarkable technology, it cannot yet replicate the ‘thinking outside the box’ skill that so many human cybersecurity experts possess.
There is also a risk of bias in AI systems that stems from the data used to train them. This can cause false positives and false negatives in their detection, resulting in unfair accusations or failure to detect a threat. Bias can be mitigated by using diverse and representative data to train AI systems. As an example, if a system is trained using mostly male email users over the age of fifty, it could be seen as a threat to a thirty-year-old woman simply because that would represent an anomaly to the system. AI technology is still in its infancy, and these are problems that will hopefully be ironed out over the next years. However, it is always worth remembering that the AI system is only as good as the data it has experienced.
Incorporating AI into existing cybersecurity systems can be complex and takes time to do well. New AI-powered systems need to be incorporated seamlessly to avoid risking a period of vulnerability that could easily be exploited by cybercriminals. With all the advantages AI can bring to a cybersecurity system, it is a process well worth undertaking, but it is not a process that can be rushed.
Companies and organizations using AI-based cybersecurity systems will also have to deal with public perception of the technology. The development of AI is exciting, but reactions to it are mixed. And for every bit of positive publicity about AI, there is plenty of negative as well. Not everyone will be happy to entrust their sensitive information to an AI system.
The Future Of Cybersecurity
Cybersecurity remains an exciting and rewarding field to enter. In this line of work, you help prevent and tackle crime, keeping people’s information and finances safe. For those willing to gain additional qualifications and training, there are also many promotion opportunities with competitive salaries and high levels of job satisfaction. In cybersecurity work, you get to use cutting-edge technology such as AI in your daily work and will be at the forefront of any further developments that will undoubtedly take place. As cyber criminals continue to develop more sophisticated methods, sometimes using AI themselves, the cybersecurity experts will be on the front line working daily to prevent the criminals from becoming successful. If you are interested in new technology and this is a career path that interests you, why not find out more about your training options? As cannot be stated too frequently, AI complements human cybersecurity experts; it does not replace them. And businesses, organizations, and governments across the world continue to need increasing amounts of skilled, dedicated experts.
