Artificial Intelligence (AI) is the ability of a computer-controlled robot or digital computer to carry out duties that intelligent humans would otherwise do. Artificial intelligence is usually used when developing projects and systems associated with humans’ intellectual processes and capabilities. These could be things like discovering meaning, reasoning, or learning from a past experience.
Since digital computers were developed in the 40s, computers have been completing complicated tasks with excellent proficiency. However, even with advancing memory capacity and processing speeds in computers, developers have not been able to create computers that rival human flexibility in tasks that require knowledge.
On the flip side, some programs have been able to attain the performance levels of human professionals and experts in given tasks. It is where artificial intelligence is found, and these could be handwriting recognition, computer search engines, or medical diagnosis.
What is Intelligence?
It is funny how the simplest human behavior is regarded as intelligence while complicated insect behavior is never seen as intelligence. Why is this? Look at the digger wasp behavior. After this female wasp gets home with food, she will first drop it on the threshold and check whether intruders are in the burrow. Until she is sure, it is clear when she will bring the food inside. The problem arises when the food is slightly displaced from the entrance while she is inside. She will have to repeat the entire procedure as long as she does not find the food exactly where she left it. Intelligence is the ability to get used to new circumstances. In this case, the wasp cannot be considered intelligent.
Human intelligence is not measured using only one-character trait but a combination of diverse abilities. Research in AI focuses on various intelligence components such as learning, problem-solving, reasoning, language, and perception.
Understanding AI Basics
As mentioned earlier, AI is the technology that can learn, understand, and act based on derived and acquired information. Artificial intelligence works in three diverse ways today:
- Augmented intelligence – is relatively new and enables organizations and individuals to perform tasks they wouldn’t be able to.
- Assisted intelligence – is used widely by many today, and it improves what organizations and people are already doing.
- Autonomous intelligence – is a technology being developed for the future and will have machines acting independently. An example is self-driving vehicles made by Tesla.
AI possesses domain-specific knowledge, some bit of human intelligence, technical mechanisms to gain knowledge, and ways to use that acquired knowledge. Expert systems, machine learning, deep learning, and neural networks are subsets of AI technology.
Applying AI to Cybersecurity
Artificial intelligence technology help prioritize threats and detect zero-day malware. The technology also takes automated remediation actions to curb these issues.
Cybersecurity experts face an unprecedented threat environment with a shortage of qualified staff, high attacks numbers, and increased sophistication from the levels of attacks.
For most cybersecurity managers and professionals, the silver bullet for handling cybercriminal threats is via artificial intelligence. AI technology promises to allow your cybersecurity teams to take care of more threats that may be a bit complicated even with few staff involved.
A survey by a global law firm dealing with technology, Pillsbury, in 2021 indicates that almost half of executives (49%) believe that AI is the best weapon for nation-state cyber attacks. Most of these managers are banking on that. The company predicts that cyber-security-related AI spending will rise by 24% yearly and reach a $46 billion market value by 2027.
Machine learning is widespread in cybersecurity today. Its application includes anomaly detection algorithms to counter malicious user behavior or traffic, classification algorithms for spam detection, and correlation algorithms. These algorithms connect signals emanating from disparate systems. Any cybersecurity product or tool that uses these cases uses machine learning techniques.
Experts acknowledge that machine learning and AI are already showing what they can do to identify threats and zero-day malware and take automated actions to curb security issues.
Zero-day Malware
Cyber attackers are becoming more and more efficient in attacks. They are creating updated and upgraded versions of malware that can bypass signature-based detection. Just last year, in 2021, AV-Test Institute discovered over 1.3 billion malware and other unwanted applications.
A report in July 2021 by Ernst & Young shows that 77% of global managers discovered a surge in disruptive attacks in 2021 compared to 59% in 2020.
Machine learning and AI-powered systems can assess malware on inherent characteristics, not signatures. A good example is if the software is made to encrypt several files at once quickly, that is suspicious. If the software hides from observation, that is also a sign that it is not legitimate software.
An AI system will assess such issues and characteristics, among others, and calculate the risk of a previously-unseen software. Experts say AI can tag malware that may not appear like malware samples you may have come across. That results in increased security in cybercrime.
The Deep Instinct director of cybersecurity advocacy, Chuck Everette, says that the signature-based technology, Legacy, can stop 30% to 60% of cyber threats. According to him, machine learning will enhance this effectiveness to about 92%.
More employees are working from home today since the pandemic set in. That has raised a question on endpoint security since companies could be more vulnerable today than ever.
Ransomware has been increasing for the longest time, and 2021 recorded the highest number of cases. Eight out of all the ransomware attacks happened where users unwillingly clicked on malicious files that had malware. That is where AI comes in, as it will help detect these unknown or unseen malware attacks before infiltrating the system.
Identifying and Prioritizing Threats
Daily security alerts bombard cybersecurity analysts, and most are false positives. These experts spend lots of time performing routine duties and do not have sufficient time to work on more significant issues.
Boston College Cyber security professor Etay Maor argues that all vendors should implement ML and AI today. He says that these will handle all sophisticated threats and the massive volume of threats coming in daily.
A Trend Micro Survey released in May 2021 shows that 51% of decision-makers were astonished at the volume of alerts they received. 55% of the respondents said they were unsure whether they could prioritize these threats or even deal with them. The survey respondents said that they spent 27% of their work time analyzing false positives.
According to the Critical Start survey in March, almost half of the respondents turn off their high-volume alerting features when they receive too many alerts.
A Check Point report confirms that more than 900 attacks were realized every week in the last three months of 2021. Compared to the previous year, the attacks on corporate networks shot up by 50% in 2021.
Why we are seeing all these numbers today can be credited to the use of AI in cybersecurity. AI entails extensive pattern analysis, which will easily identify and prioritize threats to the system.
Taking Automated Action
Machine learning and artificial intelligence help automate repetitive tasks. These could be tasks like responding to the massive volume of low-risks notifications.
Low-risk alerts require a fast response, but the risk is generally low, and the system already knows of the threat. For example, if the system detects ransomware on the user’s device, the system will shut down the network connectivity to protect other components from infection.
Intelligence automation takes care of such issues and will help the company deal with a shortage of qualified personnel. Intelligent information will also be used to collect research and more information on security incidents. It will help pool data from different systems and create a quantifiable report for review, saving the company’s routine efforts.
A few years ago, many people were afraid that artificial intelligence would take their jobs, but it seems it is making people’s jobs easier.
In fact, according to a cybersecurity workforce study last year October, there is a global shortage of cybersecurity professionals of about 2.72 million. However, it is a drop from the previous year, when the deficit was 3.12 million. Even with the influx of new talent, there is still more demand for these professionals to assess the risks in organizations using AI.
Benefits of AI for Cybersecurity
Learning more over time
AI technology is intelligent and could enhance its network security as time goes by. The technology uses deep learning and machine learning to understand business network characteristics over time. It will analyze patterns on the specific network and keep them for future reference. The technology will then detect any security incidents or deviations from what it is used to see before responding.
Identifies unknown threats
AI technology can identify threats that human beings will not notice. Hackers are always on the rise, sending millions of attacks on companies, and the unknown threats could have a massive impact on the business.
As cyber attackers look for sophisticated malware attacks, ensure you employ modern solutions such as the use of AI to counter complex threats. AI technology has shown it can effectively detect and prevent unknown threats to a company before things go south.
Better vulnerability management
Managing the company’s vulnerability is critical to keeping cyber attackers away. An average company has many daily threats that need to be detected and prevented before they can cause any harm. Assessing your security measures via AI technology can help better your vulnerability management practices.
AI will help analyze your systems quicker and more effectively than cybersecurity personnel. It will pinpoint the weaknesses in your system and networks and help your firm focus on the essential security tasks.
It handles lots of data
A company’s network holds many activities; even a mid-sized firm will have traffic. Enormous amounts of data are transferred between businesses and customers daily. This data and information will require protection from malicious software and people. Cybersecurity personnel may not be able to assess all that traffic for any possible threats.
That is where AI technology comes in. It will help you detect any threats in the system will all the data being transferred. It will easily detect threats hidden in massive chunks of chaotic traffic.
Reduces Duplicative Processes
Attackers keep changing their tactics to bypass company security features. Basic security practices do not change, which is repetitive for cybersecurity personnel. They could get tired or bored and miss crucial security tasks, exposing the network.
AI technology will handle repetitive security measures and tasks without getting bored or skipping a step, unlike when a human is involved. It will perform all the security tasks and analyze the network for security holes and threats that could be a problem to the system.
Securing Authentication
Many websites today have user accounts where a customer will log in to buy products or services. Some sites will even have contact forms where visitors must fill in sensitive information. Every company should employ extra security layers to protect their customers.
AI technology will secure authentication any time the user wants to log in to their account in your network. With tools such as fingerprint scanners, CAPTCHA, and facial recognition, the system will know whether the log-in attempt is from the right user or not.
Take Away
Today’s business environment and dynamic and changes day in and day out. Maintaining high levels of security should be your top priority as hackers never sleep, trying to devise complex ways to gain access to business networks for personal gains. Make good use of machine learning and AI technology to strengthen your security systems and infrastructure.