The future of Antivirus: Machine Learning and Artificial Intelligencelilla
The future of antivirus software goes hand in hand with the significant growth in the number of types of online threats. Online dangers are increasing by the day, and manufacturers of Antivirus software and other cybersecurity solutions are working non-stop to counter and prevent this growth. Since the digitisation of the world, this is a cat and mouse game where both rogue and cybersecurity parties try to stay ahead of the other. The ‘old’ antivirus solutions relied on recognising existing threats, and then identifying and removing these threats via scans on your device. The result: an overlapping period of sometimes months in which the danger first had to be recognised by the manufacturer, then a solution had to be tinkered with, the end user had to update the antivirus software, and then a scan would recognise and remove the infected files. With the conclusion that things were behind the times. Fortunately, today we are a lot further along in actively recognising and resolving online threats and active hacking attempts, but where the rogue parties continue to evolve, the cybersecurity side needs to evolve as well. In this article, we look at where we as humanity are now in terms of Antivirus software and cybersecurity, and its future. We also cover what you can do as an end user or small business to cost-effectively and efficiently secure your devices against the most common online threats.
How is machine learning used in cybersecurity?
Machine learning can be applied in cybersecurity to improve processes involved in detecting and resolving attacks of any kind. The main difference between Machine Learning and Artificial Intelligence is that AI incorporates human intelligence and behavior to systems/machines. Machine Learning, on the other hand, is using past data and experience to automate the analytical building of models.
One of the biggest benefits of using machine learning in cybersecurity is the ability to automate time consuming and repetitive tasks. These could be, for example, malware analysis, vulnerability assessments or network log analysis. Many cybersecurity apps use machine learning to identify and act when there is an attack. Should similar “events” be detected, the machine learning model will deal with them automatically. Machine learning is also often used in spam detection and phishing prevention. The algorithm can not only identify phishing techniques but also can predict potentially harmful URLs, email headers etc. Machine learning can also apply behavioral analysis which is used to predict attack patterns based on analysis of adversary behavior.
How is artificial intelligence used in cybersecurity?
It is no secret that the use and development of Artificial Intelligence is leaping at a bizarrely fast pace, and this is good news for cybersecurity. As mentioned earlier, smarter and more dangerous online threats are emerging every moment, and the cat-and-mouse game between cybersecurity and rogue threats becomes increasingly unfair when cybersecurity parties have to humanely keep up and counter the dangers. Artificial Intelligence helps with this and is already being used by most antivirus solutions. And this is just as well, because with the old way of Antivirus software, it is an unfair fight against the rapidly developing online dangers. Through AI, antivirus software can process and manage massive amounts of data and self-classify as dangerous, or potentially dangerous. Based on these analyses, Artificial Intelligence can create its own hazard models and predict and prevent potential attacks. This obviously helps enormously in the 24/7 war between rogue parties and anti-virus software. Especially for end users and small businesses, an AI-based antivirus programme will be enough to counter the most obvious dangers and operate safely. Below, we discuss some top-of-the-line AI-based antivirus programmes.
What antivirus software uses artificial intelligence?
Artificial Intelligence in cybersecurity and antivirus detection is not a futuristic idea anymore. More and more companies apply modern technologies to their already established methods. In this paragraph you can read more about the top AI-powered antivirus software.
One of the best-known brands in cybersecurity is Avast. It has the most well-known antivirus program on the market, and it has been getting better for years. Avast leverages both AI and machine learning technologies. One product from the business that employs AI and machine learning to shield customers from current cyber threats is Avast Antivirus. Their advanced artificial intelligence (AI) system automatically gathers and extracts data from every user in the user base. Then, the products are immediately updated with new versions after discovering a new malware sample. Another feature is Avast’s CyberCapture which relies on machine learning technologies. This can identify any suspicious file that you want to open and send it to the cloud where it gets analyzed. This way, Avast can offer essential and real-time security for your devices.
One of the best antivirus solutions in the market nowadays is Bitdefender. This AI-powered antivirus software is both effective and simple to use. With the integrated AI, Bitdefender can free up space on your system and can improve the performance of your device. Moreover, you can benefit from parental control and excellent VPN. Bitdefender’s AI enhances the ransomware protection, system optimization, and the detection of harmful websites.
Windows Defender’s flawless integration with OneDrive, is what separates this software from the rest antivirus programs. Users can utilize this to ensure they can still access personal files even if a virus locks them by copying them through Windows Defender into OneDrive. The Windows Defender Security Center is only one of the security solutions Microsoft is improving with AI. Windows Defender offers fundamental defense against a range of cyber dangers, including viruses, ransomware, Trojans, and more. Moreover, it can automatically detect any other antivirus programs that might be installed, making it simple to uninstall previous scanners.
What antivirus software uses machine learning?
Machine Learning is a subfield of AI that uses algorithms focused on data to generate adaptable models that can solve a variety of complex tasks. Next to AI technologies, more and more companies are incorporating Machine Learning to create more intelligent systems. In the following, you can read more about the leading antivirus programs with Machine Learning features.
ESET Smart Security
Eset’s Smart Security antivirus program utilizes two types of Advanced Machine Learning techniques. Within the cloud there is a high-powered detection engine and a lightweight version on the endpoint. The program detects and eliminates all kinds of digital threats, including viruses, ransomware, rootkits, worms, and spyware. Based on the diagnostic tools you can get a broad overview of the complete system. Through the all-round analysis the Advanced Machine Learning can offer excellent virus detection rates.
Norton 360 is arguably the most feature-rich antivirus program, has great malware detection rates, and provides effective real-time protection. Both Machine learning and AI underlie Norton’s security, which has excellent virus detection rates. It helps to protect your devices against viruses, malware, ransomware, and spyware. In addition, Norton has amazing extra features including a VPN, password manager, and tools to prevent identity theft.
Antivirus heuristics vs machine learning
Antivirus Heuristics and Machine Learning are both methods used in the field of cybersecurity to identify and mitigate threats such as viruses, malware, and other harmful software. They do, however, use different approaches to completing this task.
Antivirus Heuristics is a method for detecting possible threats that use predefined rules and signatures. The rules are built into the antivirus software and are based on recognized patterns of malicious behavior. When a file or program is scanned, the antivirus checks for these recognized patterns of behavior and flags the file as a potential danger if it finds a match. While heuristics can be effective in detecting recognized threats, they can also overlook new and developing threats that do not match the pre-defined patterns.
Machine Learning, on the other hand, is an artificial intelligence method that allows computers to learn from data and improve their performance over time. In the context of cybersecurity, machine learning algorithms can analyze massive volumes of data to identify patterns of behavior that are associated with malicious software. Unlike Antivirus Heuristics, Machine Learning does not rely on predefined rules, and it can adapt to new and emerging threats.
To summarize, Antivirus Heuristics detects possible threats using predefined rules and signatures, whereas Machine Learning uses algorithms that can analyze massive volumes of data to discover patterns of malicious behavior. While both methods have their strengths and weaknesses, machine learning is considered to be more effective at detecting new and emerging threats.
Artificial Intelligence vs Machine Learning
Artificial Intelligence (AI) and Machine Learning (ML) are closely related fields, but they are not the same thing. Here are some of the key differences:
1. Scope: Artificial Intelligence (AI) is a broad field that includes all approaches to develop machines that can perform tasks that typically require human intelligence, such as interpreting natural language, recognizing images, and making decisions. Machine Learning (ML), on the other hand, is an AI subset that focuses on training algorithms to learn from data and improve their performance over time.
2. Approach: Artificial Intelligence (AI) approaches problems by developing rules and algorithms that allow machines to perform specific tasks. On the other hand, Machine Learning (ML), approaches problems by training algorithms to identify patterns in data and make predictions or judgments based on that data.
3. Learning: In Ai, machines are preprogrammed with rules and algorithms that allow them to perform specific tasks. In contrast, in ML, machines learn from data without being explicitly programmed.
4. Flexibility: AI systems are often highly specialized and designed for specific tasks, while ML algorithms are more flexible and may be used for a variety of tasks.
5. Human Intervention: AI systems often require significant human intervention in their design and execution, while ML algorithms may learn and improve with minimal human involvement once they have been trained.
To summarize, Artificial Intelligence (AI) is a broad field that includes many different approaches, including Machine Learning (ML). Machine Learning is a specific subset of Artificial Intelligence that focuses on training algorithms to make predictions or judgments using data. While there is considerable overlap between the two areas, they have distinct approaches and applications.
What is signature-based detection?
Signature-based detection, as the name suggests, is a detection software that identifies and catches threats by their malicious code also called “signature”. One such code is uniquely specific to a certain virus which makes it possible to connect that code to the threat. The official definition of signature-based detection is: a method of identifying malware in which a specific piece of malware is linked to a unique identifier, typically a unique string of code or the hash of known dangerous code.
The step by step process of a signature-based detection in an antivirus is:
● Identify the malware
● Add the malware pattern to the database
● Updating of the antivirus scanner to include the pattern
● Next time the antivirus finds this pattern in a piece of software, it is detected as malware
Signature-based detection should not be confused with anomaly-based detection. Anomaly-based detection searches for and detects anomalies in network behavior changes which then triggers an alert. The main purpose of signature-based detection is to focus on threat detection and not changes.
What is the future of antivirus protection and cybersecurity?
The future of antivirus protection and cybersecurity is likely to be shaped by several emerging technologies and trends. Below, these are the technologies and trends that contribute to the future of antivirus protection and cybersecurity.
1. Artificial Intelligence (AI): The use of AI in cybersecurity is already becoming more widespread, as it can be used to identify and respond to threats more quickly and accurately than traditional approaches.
2. Machine Learning (ML): Machine learning algorithms are used to identify patterns in data that may indicate cyber threats and weaknesses. This can aid in the detection and response to threats in a more timely and accurate manner.
3. Blockchain: The usage of blockchain technology in cybersecurity may become increasingly common as it can provide a safe and decentralized way to store data while preventing unauthorized access.
4. Cloud-Based Security: As more companies move their data and apps to the cloud, cloud-based security solutions are becoming increasingly crucial. This usually comes with tools for monitoring and protecting cloud-based systems and data.
5. Internet of Things (IoT) Security: As the number of connected devices and the IoT grows, new security solutions are required to safeguard these devices from cyber threats.
Ultimately, the future of antivirus protection and cybersecurity is likely to involve a combination of technologies and approaches that are designed to protect against a wide range of threats from the old to the new ones. As cyber attacks become more complex, the demand for more advanced security solutions will only continue to grow.
What growth in online threats can we expect in the upcoming years?
Based on the current trends and historic patterns, it seems high-likely that we will continue to see growth in online threats in the upcoming years. One major area of concern is the growing expertise of cybercriminals and their ability to execute more advanced and targeted attacks. This includes ransomware attacks, which can have a significant impact on businesses and individuals by locking them out of their systems and data until a ransom is paid. Another area of concern is the growing number of Internet of Things (IoT) devices linked to the internet, many of which have inadequate security measures in place. These devices can be easily compromised and used by attackers as a gateway to bigger networks.
Lastly, as more people work from home and rely on digital technology in their everyday lives, we may expect a rise in phishing scams, social engineering assaults, and other sorts of fraud that take advantage of people’s reliance on digital communication.
To reduce these risks, it is important to stay informed about the latest threats and security best practices, use strong passwords, keep software up to date, and utilize security tools such as antivirus software and firewalls. Moreover, businesses should invest in cybersecurity, in cybersecurity awareness training for employees and implement comprehensive security measures to protect their networks and data.
What antivirus software would we recommend to be future-proof?
Bitdefender is one of the top AI-powered antivirus software that offers a combination of simplicity, functionality, effectiveness and quality. The system improves user’s device performance by freeing up space through multiple optimization tools. The VPN Bitdefender offers is a great solution when compared to “standalones”. Some of the best features of Bitdefender are secure payments online and web browsing, system optimisation, advanced protection against ransomware and microphone and webcam protection.
Read more about the top 7 Bitdefender features
Panda Dome is another great antivirus software that uses a cloud-based scanner which plays the role of a separate antivirus scanning engine. The advantage of this is that regular antivirus software usually misses the more advanced threats that this cloud-based technology scans and identifies. An example of the advanced technology Panda Dome uses is the Rescue Kit. With this feature you can “rescue” your affected PC, for example, by creating a so-called “rescue USB drive”. This way you can boot your devices and clean them through the cloud scanner. Panda Dome provides a gaming mode and parental controls, together with tools that clean your devices.
Read more about the top 8 Panda Dome features
Avast’s antivirus software is one of the most prominent cyber security names out there. The reason for this is the constant improvements throughout the years. Avast uses both AI and machine learning to keep users safe from the ever changing cyber threats. One of the main features of Avast is CyberCapture. This feature is based on three machine learning-powered technologies – Malware Similarity Search, MDE, and Evo-Gen. The Malware Similarity Search facilitates the categorization of massive incoming malware samples. MDE is a database that allows parallel access on top of indexed data Lastly, Evo-Gen is an algorithm that searches and finds malware’s generic description in large(r) datasets.
Read more about the different Avast packages here
ESET Smart Security
ESET Smart Security is a great AI-powered antivirus which offers advanced diagnostic tools, firewall, anti-phishing, password and parental controls among others. The advanced diagnostic tools provide a well-rounded overview of your entire system and can be used for creating security reports, for example. ESET’s virus scanner is one of the top performers on the market. The software is compatible with Windows, Android and macOS.
As one of the best known names in the cyber security sphere, Norton 360 provides excellent malware protection and antivirus software which is heavily based on machine learning. The software can identify and detect the latest malware while offering a comprehensive protection from all kinds of threats. You can benefit from multiple security features like webcam protection and password manager, VPN with unlimited data, firewall and secure cloud storage. Depending on your required features, you can choose from multiple packages and prices.
Compare all Norton 360 versions.