In the year 2k16 the Artificial Intelligence has huge progress in different technologies such as motorcycle industries(they have introduced a self-driving car), Language translation and some top tech companies like Cisco(security) and big data..etc. In the same year, there was a lot of malware attacks have been spreading around the world such as ransomware and botnets are the popular malware attacks.
According to the Malwarebytes State of Malware report, say’s that cybercriminals have been enlarging their thoughts and finding different loopholes to pass malware around the world with help of transparent runtime randomization and through electronic-mail..etc. In recent times, how to use machine learning has been playing an important role in securing the data for the different organizations that are facing security threats.
The main goal of machine learning in cybersecurity is to build an algorithm that allows the computer to safeguard or fight against cyber attacks.
Let’s know what is Machine Learning & Cyber Security
The process of executing any type of task such as analyzing data, collecting the data and processing the data without the help of human intelligence is known as Machine Learning.
Cybersecurity can be defined as the set of techniques that are used to protect the network of an organization and protect the damage from unauthorized network access.
If we use machine learning in cybersecurity, It helps to analyze the previous malware attacks data and creates or develops the algorithm from protecting the cyber attacks. In this approach, it can automatically enable a malware defender which has its own ability to defend with the help of Machine Learning. Artificial Intelligence and Machine Learning have a huge expectation in every industry the present worth of them is approximately 6 billion USD and can reach 47 billion USD by 2k20(the data is said by Information Data Corporation(IDC) ).
Working Of Machine Learning With Cyber Security
Let’s understand how machine learning works with cybersecurity, The fuel for machine learning is Data. If we consider the email spam finder algorithm, generally the work spam defender is to collect the spam emails and block them and allow other mails normally to the inbox. In the same way machine learning check the verified spam mail with the conforming to the law or to rules(legitimate) email by this, it verifies what type of message the user gets(Normal message or harmful message). The technique which is used to verify I .e.spam mail with legitimate is also known as classification which is the important technique in machine learning.
Cybersecurity Threats Prevented By Machine Learning
Here are a few cybersecurity threats that can be prevented by machine learning. Let discuss in detail each of them below.
There are different types of malware, Were ransomware is the subtopic of malware which tends to lock the victim’s data by the process called encryption and the attackers will demand amount to the victim for decrypting the data, the amount which is demanded by the attackers using virtual currency such as Bitcoin and Cryptocurrency, By virtual currency cybercriminals identity can’t be found. It can be spread with the help of infected software, malware email attachments, and infected hardware.
A deep learning algorithm should analyze the previously occurred ransomware attack information and properly trained, from this it can easily detect the ransomware attacks. In the training process, a deep learning algorithm requires a large number of infected ransom files, as well as a large number of clean files by this system, become smarter. When the system becomes smarter by the algorithm the task is to find the key features from each file in the data set and then they are differentiated according to their data training sets. After this whenever the ransomware attacks the system it takes help with the trained algorithm and checks the security policy before it encrypts the computer. By this ransomware can be protected using machine learning. There is a company called Acronis that uses machine learning for defending cyber attacks.
The system which is connected to the internet such as smartphones, personal computers(PCs), Internet of Things(IoT)..etc. All groups can be infected and controlled by the common malware without the owner’s knowledge which can be said as botnets. This is mainly transferred by third-party applications or software.
In recent times botnets are used by cyber attackers for threatening the top organizations, To defend bots new methods are introduced for defending. Machine learning has proven that they have the best defending methods against the botnets.
To defend botnets, Machine Learning is used. Here are the techniques used to defend botnets.
- Supervised Learning (SL)
- Unsupervised Learning (UL)
The majority of the customers use supervised learning, In this, we have two variables(x,y) one is for input(x) and another one is for output(y). When we map this both with the function called h it may the same value or different one, If we get any new results it can be given to the output variable y. Here mapping functions help, in this algorithm learns from the datasets. Supervised Learning process are two types they are
In Unsupervised Learning there will be only one variable called x which is for input there will be no output variable. Here all the data are unlabeled and the algorithm learns from the essential structure with the help of input data.
Webshell is a small code written in any language which supports web server such as PHP, Python, and perl…etc. When a web shell code is uploaded to the webserver it takes over all accessibility from the machine administrator which means the cyber attacker can read the entire database. The Cyber Attackers use web shell on the E-commerce website to steal the credit and debit ca5rd numbers from the online payment customers.
Now let’s look at how machine learning helps defend web shell, If we take any e-commerce shopping cart by this machine learning helps to detect the web shell by training its previous datasets I .e.malware behavior and normal behavior. The Machine learning algorithm identifies appropriate Webshell and disallows them before it infected to the webserver. By this machine learning helps from cyber attackers.
Now day’s protection of data is very difficult because of cybercriminals, In recent time number of malware are introduced and spreading them all over the world. To defend against the malware experts have introduced machine learning with cybersecurity which increases the security level. In this article, We learn how machine learning defended against dangers malware attacks such as ransomware, web shell and much more. If you have any queries regarding the topic let me know in the comment box below.