In this cathartic situation where organizational digital security perimeters are breached on a daily basis, the combination of AI and cybersecurity is the method to reinforce the infrastructure. Let’s learn about it in detail!
Cybersecurity has always been a concern of the digital world since the value of data was recognized. Whether to steal financial data or to lock the data for ransom, hackers have evolved and pushed walls created by cybersecurity further ahead. As the attackers kept getting smarter, businesses dealing with data kept getting anxious.
In fact in the year 2022, in the U.S. alone, around 461 cybercrime incidents were witnessed in organizations that led to compromised data as per a Statista report. These attacks were carried out via different hacking techniques such as phishing, smearing, BEC (business email compromise), etc.
It is often witnessed that these attacks are carried out on industries that are the pulse of a nation. For instance, healthcare, finance, banking, etc. are industries that involve tons of money and sensitive data. Intrusions to these industries can break the lifeline of a country.
With hackers becoming smarter, organizations have also started to reinforce themselves by using AI in cybersecurity. AI in today’s world is omnipresent. It is applied on a large scale in almost every industry to improve its efficiency and efficacy. This is why tools like the best ethical hacking tools, AI cybersecurity apps, and more became the new normal.
With this article, our aim is to assess some common threats to organizations, organizational challenges to implement AI, and spaces where artificial intelligence in cybersecurity can help, therefore, let’s start exploring the topic.
Cybersecurity is the practice of protecting computer systems against external intrusion and multiple other security threats. There are several types of attacks that are carried out on computer systems with different intents.
Some of the intents are mentioned below:
With the list above we have barely scratched the surface. However, every attacker has their own intent. There are attackers who do it for the money, there have been attacks with the intent of cyberwarfare between countries, some for raising their voice & opinion regarding an issue (Anonymous Now), and some simply for the notoriety of the act.
With the list below, we are trying to get you an idea of the different types of cybersecurity threats that an organization has to deal with.
Let’s start with the list.
This is the type of cybersecurity attack in which the intruder relays itself in between two people communicating directly, thereby, making it a man-in-the-middle attack.
There are several techniques using which this cybersecurity attack is performed which are:
Organizations are stacked with numerous confidential information bound by non-disclosure agreements. Network intrusion can be done by an attacker for stealing valuable information or gaining illegitimate access to the network. This thereby would put the organization at risk. There are multiple ways these attacks are carried out such as:
Almost every large organization uses an internal network masked by a VPN (virtual private network) to keep its activities encrypted. This enables them to keep their network safe from external intrusion. However the majority of the time, cybersecurity attacks are escalated because of internal redundancies.
Any insider with a simple Pendrive, or an employee visit to a website with a malicious virus can compromise the security. In fact, it doesn’t have to be an employee, a contractor, a third-party partner, or anyone that has access to the network can compromise it.
The attack is carried out by creating a traffic jam of requests. A server can handle only a particular amount of traffic in a certain time span. To further explain, the traffic is catered on a website on the client side when a request is sent to the server for gaining access to the information. In a DDoS or distributed denial of service attack, the attacker spams the organization’s server to make it incapable of processing any request from its actual users.
Malwares are one of the most common threats available one might encounter while surfing the web. A malware is an executable file that is capable of providing unauthorized access to your computer or network. These malware are commonly found on websites, and once clicked on, they get automatically installed on your computer. This is one of the most commonly used techniques by black hat hackers to gain access to a computer.
Organizations are well aware of the redundancies and threats of the internet. This is the reason in many organizations, it is not allowed to open all websites, use external thumb drives, or use the company resources from an external network. This is the reason companies often employ hierarchy-based access to their users. However, there are times when these rules and regulations are violated thereby leading to external attacks.
Some of the common policies that are laid out in organizations are:
A brute force attack is carried on over a system when the attacker tries to intrude on a system by trying out a series of passwords. In this type of attack, the attacker tries all possible passwords from the dictionary in combination with numbers using tools. This is time-consuming, however, there have been incidents where attackers have infiltrated a system using this type of attack.
Have you ever seen a message regarding password strength being low? Well, organizations prefer that their employees use complex passwords and change them regularly. In fact in some organizations, it is a regular practice. The reason is that employees often end up keeping passwords that are easy for them to remember and don’t change them forever. This makes them vulnerable to social engineering attacks as well as brute force attacks. Therefore having weak credentials can lead to external intrusion.
There have been security breaches in the past that further strengthen the argument for using AI and cybersecurity. Below are some examples of attacks that were carried out on large organizations.
On the day of January 17th, 2023, Microsoft Azure got attacked. It was a server-side request forgery (SSRF) attack that affected numerous Microsoft services. Services such as Azure API Management, Azure functions, Azure machine learning, and Azure digital twins. The attack could have had a significant impact if the organization didn’t take swift action. This led to easy mitigation after the incident took place.
Kubernetes is an open-source service for containerization. It allows organizations to deploy their softwares with scalability and overall management. The service was affected by Kinsing malware that affected the clusters of Kubernetes exploiting two paths i.e. vulnerable images and Postgres Service misconfiguration. The intention behind the attack was crypto mining and generating revenue from it. To resolve it, all the affected services were deleted.
This attack happened on 4th December 2023. This happened when the data collection sale started for the 200 million Twitter user account information. It is estimated that the breach compromised around 59 GB of encrypted RAR data. It was a targeted phishing attack that compromised the vulnerable APIs allowing the perpetrators to scrape data from the user accounts.
The combination of cybersecurity and AI is an imminent need. There have already existed multiple ways to secure your privacy. However, we can stress the argument that attackers are already using AI technology to make their intrusions much more effective. There have been several cybersecurity tools existed, however, it's high time that organizations should do the same to reinforce their security infrastructure. However with much more force and on a much wider scale.
Note: Want to check out the best AI development companies, here’s the list!
Below, we have mentioned some reason that further supports the argument of integrating artificial intelligence and cybersecurity:
Data within premises is siloed in different siloes such as human resources, finance, and multiple other operations. Despite having multiple tools and policies in place, there are still instances of external intrusion.
The simple reason behind this is the amount of data generated that is simply incomprehensible. Adding to it, the lack of investment to reinforce the internal process using AI and cybersecurity further increases the gaps in the redundancies.
The core reason behind the level of globalization achieved in the past decade is access to the Internet for more than 50% of the global population. However, it also opened floodgates for many more internet-based attacks such as DDoS, phishing, malware, MAC spoofing, masquerading, etc. This, thereby, led to increased cyber attacks on large organizations. In fact, a study by Comparitech shows that more than 4.7 million people became victims of phishing in the year 2022.
With the amount of data generated today, it is almost impossible for humans to keep a check at every data point & transaction. This further pushes the need of having AI in cybersecurity.
The cost of establishing a system for storage and analytics is one thing. However post an intrusion, the cost of getting the data back, and making the systems operational back again is much wider. In fact, in some cases, it is estimated to be 5x to 7x times more expensive.
The majority of the internet is full of websites that have unregulated content. This is excluding the dark web, otherwise, the entire system would become incomprehensible because websites on the dark web exist beyond the realm of unindexed websites.
On the WWW (world wide web), Malware is one of the biggest threats. A simple click to any unregulated website by the employee and the entire system might get compromised.
With the increasing number of intrusions, the amount of security as a response has also increased. One aspect of it is the enhanced security measures that are taken in the form of encryption to protect data. Some of the encryptions such as RSA, AES, Blowfish, Twofish, etc. are difficult to comprehend for regular users.
A report by Precedence Research suggest that the cybersecurity market was evaluated at $17.4 billion. Adding to it, this market is further expected to hit $102.78 billion by 2032. It clearly states that the number of intrusion are bound to increase in future as per th trend. These numbers indirectly project the anxiety that has possessed the cybersecurity industry. Thus, the dependency on technologies like AI is boosting rapidly to improve cybersecurity standards.
With time, not only AI, but plenty of other cybersecurity methods have come into existence as well. To name a few, two-factor authentication, biometrics, captcha login, PINs, Photo ID, proximity scans, and more. Tech giants like Apple, Google, and OnePlus have also increased their dependency on AI and ML technologies to make their smart devices safer and better prepared against possible cyberattacks.
A Statista report suggests over 5.18 billion internet users in the year 2023. In fact, Broadbandsearch.net shares an incredible figure on its website’s article. As per that around 332.2 billion emails are being sent and received daily in the year 2023. This figure was 306 billion in the year 2020.
With these kinds of figures, it is impossible for human beings to monitor every transaction that happens on the internet. This is keeping in mind that the stat regarding emails is barely a scratch on the way the internet is used on a daily basis.
To stay abreast of this issue, AI and cybersecurity was introduced. Using AI has been revolutionizing in multiple fields including cyber security. It keeps a check on the transactions carried out on the internet in real-time, strengthens overall security architecture, and most importantly augments humans with reinforced capability to detect incoming threats.
Below are the following ways cybersecurity and artificial intelligence is used:
The primary usage of cybersecurity and AI is in the realm of analyzing data. AI in cybersecurity can analyze tonnes of data that humans cannot do manually. This includes incoming traffic, different logs generated by internet transactions, user behavior, and identification of malicious activities.
Machine learning algorithms have the capability to process this data and detect anomalies, identify possible threats, and even predict new attacks based on historical data. With AI and cybersecurity, a lot can be done with limited manual intervention.
A lot can be established by simply assessing the behavior of the user on the internet. Artificial intelligence in cybersecurity has the potential to set a baseline for normal behavior.
Beyond that, if anything happens, data related to it can be collected. To assess the online behavior of a user, the AI monitor users, devices, and networks. This approach also works wonders in the case of threats that are persistent and can be from within the premises.
Just like AI can provide automated responses to customers, AI in cybersecurity can give an automated and immediate response to certain cyber threats. It can block suspicious IP addresses, quarantine machines that are infected, respond to several attacks without any manual intervention, and reduce response time to minimize damage.
Upgrading the authentication process for users is another facet of AI and cybersecurity. For instance, AI can introduce facial recognition, voice recognition, and other behavioral biometrics for improving the authentication process. This makes it even more difficult for illegitimate users to gain access even if they have a certain amount of personal user data (of authorized personnel).
Phishing attacks are primarily carried out by sending a user an email or message from any other medium such as SMS, Whatsapp, etc. Along with this message, there is a fake login page that looks identical to a trusted platform.
Once the user login to that page, all that personal data is sent to the attacker. AI and cybersecurity can examine multiple attributes such as the address of the sender, the content of the message, and other links embedded. This helps the artificial intelligence in cybersecurity model to understand whether an attempt is being made or not.
This is amongst the most common use case for using artificial intelligence and cybersecurity together. With AI-based based antivirus tools and anti-malware solutions, the system is capable of detecting malware signatures and heuristics. In fact, cybersecurity and artificial intelligence can enable the capability to detect malware simply by detecting the behavior of files and their characteristics.
AI and cybersecurity has the capability to make assessments on multiple levels. This is true with organizational networks and systems. AI tools for cybersecurity can make assessments to identify potential vulnerabilities in those networks and systems. They can help you prioritize the need to mitigate a specific issue and guide the security team to focus on critical issues.
An organization comprises multiple logs, transactions, events, etc. that need to have an automated threat detection system capable of automatically responding. With artificial intelligence and cybersecurity, this is possible.
The majority of employees make their organization a target simply by using poor passwords. AI and cybersecurity can assist in generating strong passwords by assisting users. It can help create robust keys and monitor passwords used by employees. Adding to it, it can even figure out suspicious login attempts.
The most common way of phishing is by sending spam. In fact in 2022, as suggested in an article by Data Prot around 56.5% of emails were spam. These spams often look trustworthy but take the user to a fake page and get their login credentials. With AI in place, it is possible to regularly filter out spam, thereby, lowering the risks of spam.
AI technologies have self-learning capabilities. This means they are capable of evolving over time with the help of technologies like ML, Deep Learning, Neural Networks, etc. A great example of a similar system is IBM’s cognitive security system, Watson. In fact, there are bundles of services by IBM in the cybersecurity domain i.e. SIEM, SOAR, Advisor, and EDR. Each of these services performs its own unique function such as monitoring log events, protecting of endpoints, blocking ransomware, etc.
AI hacking is as real as AI cybersecurity. Hackers are able to use the effects of AI in cybersecurity to test and predict the success percentage of their attacks. AI is capable of delivering accurate probability of the cyberattacks planned by hackers.
The tactics, techniques, and procedures (TTPs) are a set of activities used by cyber security machine learning experts or hackers to project how defenders in an AI in a cybersecurity system react. Accordingly, they can focus on looking for weaknesses to go around these defending methods used by AI in cybersecurity systems.
Another method that best AI development companies have noticed being used by AI hackers in the past is using AI to guess passwords. To crack website backends, stolen smartphones, social media platforms, etc, machine learning hacking tools that can guess passwords faster have been very helpful. Especially in cases where additional security layers like two-factor authentication are missing, these AI hacking tools turn out to be very useful.
Poisoning AI databases is helpful in manipulating AI data to either hide or corrupt cybersecurity systems. This strategy often includes injecting rogue data in AI databases which either manipulate the way AI functions or it gets tougher for AI systems to recognize patterns of cyberattacks in the process. To inject the rogue data, cyber security machine learning systems are fed with the wrongly labeled data which gets tougher for AI systems to recognize and filter.
The future of AI and cybersecurity is a sophisticated one. At one end where companies will be using AI tech for reinforcing their existing infrastructure, the attackers will be using it to infiltrate complex networks and gain access to encrypted passwords.
This power of AI will be witnessed a lot more because machine learning is capable of making sense of user data available on the internet. It is not hypothetical considering generative tools like ChatGPT are doing the same thing i.e. scraping the internet for user data in order to provide relevant responses to its users.
With cybersecurity and artificial intelligence, companies will be able to reinforce their firewalls and malware detection systems. With neural networks at bay, they will be able to weed out any suspicious activity that happens on the company front. The future of AI in cybersecurity holds a constant tussle between companies reinforcing their structure and intruders trying to figure out new ways to intrude using AI.
It’s about time because cybersecurity and artificial intelligence is going to become a common thread across industries. There will be many more intrusions to come as the technology of AI becomes more prominent and readily available. Hackers have always come up with smarter ways to intrude on company infrastructures. The ideal way to deal with the situation would be to consult white hat hackers and adopt AI throughout the infrastructure. Hiring a hacking firm would let you discover your existing redundancies while AI would enable a defense mechanism that is capable of fighting existing threats and removing any fatal blow to the architecture. The most important aspect of adopting AI in cybersecurity would be that the system would mature with each instance and transaction happening.
The future of cyber security will be more dependent on AI, especially when data is seeing an expansion across industries like automotive, metaverse, education, etc. AI is being used in traditional ways to improve the quality of cybersecurity but tools like top hacking apps are also using the technology to simulate and counter the way hacking attempts work.
In this blog, we gave you some AI in cybersecurity examples to explore its role from the perspective of both sides. We went through some examples of how AI is useful for hackers and we also talked about how AI is helping the cybersecurity industry. So, hopefully, we were helpful in providing you with an insight into the contribution of this technology to the cybersecurity industry.
Now, if you liked this blog, you should also check out our report on leading cybersecurity tips that can be helpful in protecting your privacy better.
Aparna is a growth specialist with handsful knowledge in business development. She values marketing as key a driver for sales, keeping up with the latest in the Mobile App industry. Her getting things done attitude makes her a magnet for the trickiest of tasks. In free times, which are few and far between, you can catch up with her at a game of Fussball.
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