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Cyber Security Data Analysis Essay

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Artificial intelligence for security

Before examining the change in cybersecurity thanks to artificial intelligence systems, it is good to know some data. We are used to connecting artificial intelligence to computer programs such as voice assistants present in computers and mobile devices such as Cortana or Siri, as well as industry 4.0 linked to technologies that support humans in carrying out operations. complex. In reality, the evolution of the sector turns to the protection of computers and data. Malware and viruses can in fact be blocked by artificial bits of intelligence declined in various forms. Defense is one of the main objectives of the experts' new proposals, but clearly, there is a risk that hackers could use the same systems for their attacks. Don't be afraid because hackers and their attempts act as a stimulus and example for an increase in the efficiency of new IT security products.

Internet criminals have access to the dark web, which is a series of websites on which malware and viruses can be purchased. In particular, these are AlphaBay and Hansa. These two portals have recently been closed due to bankruptcy, but there are other pages ready to offer the same service, and above all this news does not stop hackers intent on damaging other people's networks or illegally taking possession of sensitive data. To cope with the danger it is necessary to constantly update your antivirus system, but this does not guarantee 100% against the risks of attack and intrusion into your computer system. In any case, a security patch is installed on your device.

However, among the dangerous programs, there is also ransomware, which seems to be widespread. Much feared for the future are Denial of Service attacks. This justifies the frenetic work of antivirus manufacturers, which in the last year have faced 36% of cases of phishing campaigns, attacks on IT infrastructures 33%, 15% of offensive actions related to the Internet of Things, 14% of ransomware and 1 % attacks came through botnets. These are the main threats, but while the reports on the cyber situation are published, cybercriminals are ready to break into the computers of others with new techniques. This is why the last frontier of cybersecurity consists of artificial intelligence.


In the field of cyber security, machine learning, deep learning, and artificial intelligence are certainly not new terms, on the contrary, they have become commonplace. For many years, the engines of heuristic analysis and recognition of the patterns of action of the systems have been working with these technologies to increase protection and provide an innovative defense capable of adapting to the many threats that animate the world of the web and the IT world in general. In this context, there is an example of an effective system active in protection. This is a next-generation help called Watson for Security and made by IBM. The tool allows human analysts to have a platform to work on while keeping various threats away.

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In reality, the product does not take care of monitoring systems and the network but can be activated by the user for specific predefined events. The program carries out an in-depth analysis of all available data providing the user with a complete report on the activities and on what happened within the analyzed system. In this case, you have all the information, but it is up to the person to draw conclusions and decide what actions to take. It's not the only cybersecurity article to leverage artificial intelligence, but it's different than other programs like Darktrace, which still use AI. In this case, the traffic from which the normal flows are learned is analyzed. Artificial intelligence comes into play to find anomalies within all the data collected and examined. It proves to be an excellent ally when software downloaded from the internet is automatically installed and these come into operation by performing suspicious operations. Very useful in the field of data protection of companies, subject to industrial espionage attacks.

Artificial intelligence, in the field of IT security, is not only concerned with identifying threats and investigating activities within the network but also works through prevention, avoiding unauthorized intrusions by protecting sensitive data contained in devices. The AI ​​acts by memorizing the behavior of users on the web, the way they type passwords and the information exchanged so as to have a picture of the situation and implement the necessary measures to ensure security. The software is capable of verifying whether whoever is visiting a website is a person or a robot and then examines the way in which the mouse buttons are clicked, the speed of movement, the duration of the clicks, and how much it allows to monitor the visitors of the web pages. In this way, information programs aimed at fraudulent use are avoided. Furthermore, thanks to this working method, visitors and users of sites and databases can be recognized not so much by the passwords entered but by their behavior. In fact, their movements are studied to create profiles and identify the person who is operating.

The definitions

Before proceeding with the analysis of the functionalities that artificial intelligence makes available to IT security, it is good to remember the most important definitions, so as to understand the different elements and their role. Intelligent software applied to cybersecurity makes it possible to understand the threat landscape, perceive and analyze the dangers, and decide the actions to be taken to protect and eradicate viruses and malware of various kinds. What are the buzzwords to know? Here they are:

  • artificial intelligence: the combined terms are applied to any technique capable of imitating human intelligence, that is, with rules of logic and implication and with internal decision-making processes. The expression was coined by John McCarthy in 1956 even though there was already an operational definition of the genre, written by Alan Turing in 1950 in an article that explained how a machine capable of passing the Turing Test to make man communicate with other people and other computers. A terminal unable to distinguish between human and computer passes the test. AI also works with machine learning and deep learning;
  • machine learning: it is a subset of artificial intelligence that includes complex statistical techniques aimed at improving performance with the use of experience to carry out one's duties. The ML can be supervised or not, but in the first case a precise cataloging of the functions is necessary, while in the second case a behavior model must be set up so that the software can have a reference;
  • Deep learning: it is a subset of machine learning that includes algorithms useful for the software to train in carrying out the activities for which it was designed. For example, recognizing images, voices or identifying certain information by examining a large amount of data;
  • Internet of things: is a network of physical objects including a technology created to allow them to communicate, perceive, and interact with internal systems and with the external environment. The author of the terms is Kevin Ashton, who in 1999 used them to describe the physical world connected to the internet.

The intelligence of machines 'artificial intelligence is used in many contexts, but in the context of the internet it is used in particular by giants, Google is the lead, interested in controlling the network and the processes that take place within it as much as possible. Obviously, this allows an improvement in the performance of the machines and an increase in the offer to users, but the security aspect should not be neglected because the growth of the web inevitably leads to illicit attempts to take possession of information. Data collection is essential to be able to control the virtual and real world and therefore to offer people products and services that are more tailored to the needs of potential customers, but this activity lends itself to various uses and for this reason, the web is increasingly attractive to malicious people.

The application of artificial intelligence is certainly about the collection and processing of images, words, and behaviors. For this reason, deep learning is needed, which allows us to arrive at predictive scenarios. With regard to IT security, the focus is on behavioral analysis, relating a specific state with information on possible threats. Taking into consideration the technologies related to artificial intelligence and its subsets, we can say that we have the advanced tools necessary to deal with Big Data coming from the various objects connected to the network. It should be emphasized that most of the data are normal, while the dangers lurk in a small amount of information, but for this reason, every single pass of data must be analyzed to detect cyber threats. If you used a metaphor you could say that tracking down a potential cyber hazard is like finding a needle in a haystack, however, with AI you are guaranteed to explore all data systematically. Further assurance comes from the use of DeepInstict algorithms and neural networks because they instinctively protect valuable information. In fact, artificial intelligence is able to act using a human and animal peculiarity: instinct. It can do this thanks to appropriate programming with decision-making algorithms.

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Cyber Security Data Analysis Essay. (2023, October 27). Edubirdie. Retrieved February 24, 2024, from
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