Cybersecurity deals with all the components, tools, methods, and procedures that safeguard all digital resources, network resources, computers infrastructures, and data from cyber threats such as illegitimate access, vandalism, thefts, among many other cybercrimes. Indeed, the world has been witnessing a great revolution in the information technology landscape. The technological revolution has had both positive impacts and negative impacts. On the negative side sits cybersecurity threats.
With 68% of business leaders feeling that cybersecurity threats have been increasing, no organization can be said to be 100% secure. Not with the levels of attacks we are witnessing today. The best thing organizations can do to remain safe is to have adequate cybersecurity measures and conduct regular backups, just in case things go south.
In their eternal quest for sophistication, humans have developed computer systems that perform tasks that would have required human intervention to be completed. Today, we have self-driving cars, smart assistants, human vs. computerized games, proactive healthcare systems, ASIMO, chatbots, AI cybersecurity measures, Boston dynamics, automated financial investing, and many more.
AI has been found to have a significant impact on human life. Because all sectors have been integrating Artificial Intelligence, the cybersecurity landscape has been at the forefront of this great revolution. This article majorly focuses on the application of AI in data security and other cybersecurity elements.
The Integration of Artificial Intelligence in Cybersecurity
Although AI has had a tremendous impact in changing human life, it also has a negative side because it can be used for destructive reasons. For example, we have already witnessed automated hacks that occur without the human hacker needing to be involved. In this regard, some experts now see artificial intelligence as a threat to the well-being of cybersecurity.
However, it is also essential to note that artificial intelligence has taken no sides in cybersecurity matters. Masters in AI and Machine Learning in Rome On the contrary, it is helping the hackers conduct their malicious activities while at the same time helping computer systems safeguard themselves from the hackers. Therefore, let us now look at the impact of artificial intelligence on cybersecurity.
1. AI in Data Centers
Data is one of the most crucial assets of any organization. It needs to be protected at all costs. Before we proceed with the application AI in data security, I need to mention the SSL certificates. The SSL certificate is one of the most vital data security tools every organization should have. Relying on artificial intelligence alone will not be enough to safeguard your data. You must purchase SSL certificate if you value your data.
SSL certificates are not that expensive nowadays. Furthermore, you need a cheap SSL certificate to encrypt your data from intruders. SSL certificates are acquired from trusted certificate providers, and choosing the right SSL certificate is the first step towards protecting your data from data vulnerabilities.
Unlike SSL certificates, AI does not directly protect data from data breaches. However, it can help monitor data centers and prevent vulnerabilities that could leave sensitive data exposed to data breaches. For instance, artificial intelligence monitors critical data centers’ functionalities and threats such as power consumption, internal temperatures, cooling filters, and bandwidth usage. In short, artificial intelligence helps to provide insights into what measures can improve the general safety and well-being of data center infrastructure to safeguard them from data vulnerabilities.
Additionally, enabling AI-based alerts will notify you of hardware failures or critical data center infrastructure failures that could cause cyber threats and data leakages. As a result, you can take corrective measures as soon as possible before the damage becomes severe.
2. Biometric Authentication Factors
One of the most vital developments that have been brought forth by AI is biometric authentication. In the two-step authentication, users will also have to use an extra authentication factor apart from users using their login credentials to log into their accounts. The additional authentication factor should be something an intruder cannot easily access.
Thanks to Artificial Intelligence, the 2FA has become even more effective in securing online accounts against unauthorized access. One of the main milestones covered in technology and AI in particular is the fingerprint ID feature. Although the fingerprint concept has been around for a while, devices that recognize fingerprints have been more recent. As a result, fingerprint technology is becoming more and more dominant. Today, most biometric payments are made to accept fingerprints as the second authentication factor. It is also projected that by 2024, 4.6 billion devices will have fingerprint sensors.
Facial recognition is also another component of biometric authentication that has been used widely. Statista projects a $7 billion market growth in the facial recognition market by 2024. Thanks to AI, we can keep our digital resources secure by using biometric authentication factors.
3. AI in Vulnerability Management
Most businesses, organizations, and individuals have a tough time trying to attend to many cyber vulnerabilities that crop in daily. Unfortunately, conventional vulnerability management methods have not been good because they only respond to an already exploited vulnerability.
One of the most critical applications of AI in cybersecurity has been in the vulnerability management segment. Artificial intelligence and machine learning systems have improved security vulnerability management. For instance, tools such as Event Behavior Analytics blend well with artificial intelligence to analyze and monitor the different behaviors of users on servers. They will also detect and prevent system anomalies that might lead to a potential cyber breach. AI can thus be essential in detecting system vulnerabilities before they develop to pose a security threat to the organization.
4. AI in Threat Detection
Conventional breach detection techniques can only detect breaches that have already occurred. As a result, such methods cannot detect threats that have not been discovered yet. On the contrary, combining artificial intelligence with conventional detection techniques will yield maximum threat detection benefits. This is because AI integrates behavior analysis to analyze data from endpoints and unearth potential vulnerabilities.
5. AI-Based Antivirus Software
Antivirus software is another example of how significant artificial intelligence in cybersecurity is vital.
Unlike the conventional antivirus software that relies on updates to deal with new viruses, AI-based antivirus software uses anomaly detection to monitor program behaviors.
An excellent example of an AI-powered antivirus program is Cylance’s AI-adopted smart antivirus software. This type of software does not require the user to update the virus signatures but relies on continual learning to detect and prevent malicious software from scratch.
6. Artificial Intelligence in the War Against Bots
Bots have been the real culprits behind some of the most devastating data breaches, account takeovers, and bogus account creations. Unfortunately, bot-related threats are usually automated, and it can be hard for you to deal with an automated threat using manual methods.
As Mark Greenwood says, “By looking at behavioral patterns, businesses will get answers to the questions ‘what does an average user journey look like’ and ‘what does a risky, unusual journey look like? From here, we can unpick the intent of their website traffic, getting and staying ahead of the bad bots,” Artificial intelligence and machine learning can be beneficial in dealing with traffic-related vulnerabilities. For example, they will help separate bad bots from good bots, such as search engine crawlers. It is, therefore, essential to integrate AI into cybersecurity strategy to help you fight unsafe bots.
7. Artificial Intelligence in End-Point Security
Remote working is the new norm, and it is here to stay. Virtual Private Networks and antivirus software have had a significant impact on the security of endpoints. However, they often work based on signatures. It means that to safeguard your networks against the latest security threats, you have to update the signatures regularly. This becomes a problem whenever the virus definitions start lagging. In case new malware emerges, VPNs and conventional anti-malware programs won’t be able to avert them.
This is the point where AI comes in. The AI-based endpoint protection takes a different route. It first establishes endpoint behaviors through repeated monitoring. Then, it will flag out anything that seems out of the ordinary. AI-powered endpoint security thus provides a proactive security strategy rather than waiting for signature updates.
Artificial Intelligence plays a very critical role in cybersecurity. IT teams should bolster their defense strategies by integrating AI Cybersecurity strategies. Humans have failed to safeguard networks and digital resources from cyber-attacks, and it is time to integrate AI. Although AI has a flipside where hackers are using it to automate cyber-attacks, It is very effective in driving cybersecurity forward and helping organizations to establish a more effective cybersecurity posture.