Cyber security is one of the most important areas in information technology. Due to the expansion of Internet activities, hackers and cyber attackers always try to access sensitive systems and data. To prevent these threats, companies, and organizations that use information technology must use strategies to deal with cyber threats.
One of the new developments in cyber security is using artificial intelligence and deep learning to identify and prevent cyber threats. Using these technologies, threats can be automatically detected, and necessary measures can be taken to prevent them.
Also, security methods in the fields of encryption and security of wireless networks are constantly growing. For example, recent developments in the security of wireless networks include using the WPA3 protocol and 5G technology, which uses stronger encryption.
Besides, the security of Internet of Things (IoT) devices is also considered a very important field in cyber security. With the increase in the use of IoT devices, the need for solutions to increase the security of these devices and prevent the penetration of hackers has increased.
In general, new technologies in the field of cyber security are constantly growing and developing. In the following, we will examine all three areas introduced above.
AI and Deep Learning
The role of artificial intelligence and deep learning in identifying and preventing cyber threats:
Nowadays, using artificial intelligence and deep learning in identifying and preventing cyber threats is of great interest. These technologies can significantly improve cyber security for organizations and users due to their ability to solve complex problems and high accuracy and speed.
For example, deep learning and convolutional neural networks (CNN) can be used to detect cyber threats. These technologies detect strange and unusual patterns in network traffic and identify threats. Also, supervised and unsupervised learning methods can be used to identify threats.
In addition to detection, artificial intelligence, and deep learning can also be used to prevent cyber threats. For example, an intelligent security system that uses neural networks to monitor user behavior and restrict user access or notify the system administrator if the behavior does not match specific patterns that have been taught can be used. inform
Other examples of using artificial intelligence and deep learning in identifying and preventing cyber threats are as follows:
Recognizing patterns in phishing attacks
Phishing attacks are one of the most common cyber attacks. In this method, people try to gain access to sensitive and important user data through fraud and abuse of users’ trust. Attackers usually encourage users to enter their personal information in forms designed by themselves by sending emails with attractive or important titles. These forms, which look like official and original forms, are designed by attackers to steal information.
Of course, phishing attacks may be made using text messages, messages on social networks, or even phone calls. In any case, the main goal of these attacks is to obtain sensitive information such as passwords, usernames, bank card numbers, personal information, and other important information of users.
Using deep learning, it is possible to identify specific patterns used in phishing emails to trick users. Then, with this use of statistical data analysis, it is possible to determine which users are most likely to fuel these attacks more precisely. With such data, preventive measures can be taken, and cyber security can be increased.
Detection of surveillance attacks
Surveillance attacks mean monitoring and viewing data and users without permission or unauthorized access to computer systems. These attacks can be done physically or through malicious software. In these attacks, the main goal is to obtain sensitive and unauthorized information. Typically, surveillance attacks include installing hidden cameras, using spyware, accessing user data through the network, or stealing passwords and usernames.
It is possible to automatically identify whether a person or a group of people is monitoring the network using deep learning and neural networks. In this case, the system can automatically detect attacks and take necessary measures to block his access to the network.
Predicting cyber attacks
Cyber attacks use cyber technology and tools such as computer networks, the Internet, malicious software, and other cyber tools. These attacks can include unauthorized access to data, intrusion into computer networks, theft of sensitive information, destruction and sabotage of systems, DDoS attacks, etc. Some types of cyber attacks are:
– Phishing (Phishing attacks)
– Network intrusion attacks
– Intrusion into computer systems (Computer system intrusion attacks)
– DDoS attacks (Distributed Denial of Service attacks)
– Malicious code (Malware attacks)
– encryption (Encryption attacks)
– Intrusion into devices connected to the Internet of Things (IoT device attacks)
With past data, it is possible to predict what type of attacks may occur accurately. With the help of these forecasts, appropriate preventive measures can be taken to prevent their occurrence. In general, the use of artificial intelligence and deep learning in detecting and preventing cyber threats significantly improves cyber security. These technologies can prevent cyber attacks, reduce possible damages and help protect sensitive information and the security of users and organizations.
The Role of WPA3 Protocol and 5G Technology in Encryption
As we said before, encryption and security of wireless networks are of special importance, and new technologies are being developed to provide security in these areas.
WPA3
This technology is an encryption protocol for wireless networks introduced by the Wi-Fi Alliance. This technology has several security features that increase the security of wireless networks. For example, WPA3 uses 192-bit encryption, which provides more security than the 128-bit encryption in WPA2. Also, WPA3 prevents replay attacks and prevents the transmission of information in plaintext format.
In addition, WPA3 uses a new feature called Simultaneous Authentication of Equals (SAE). This feature, also called “Dragonfly,” uses a secure authentication method and makes it possible to limit attacks such as Dictionary Attack and Brute Force.
Overall, WPA3 improves the security of wireless networks by providing advanced security features. Compared to its predecessor, WPA2, this technology has more security and features, such as protecting public and private keys, protecting users’ privacy, and making connecting to wireless networks easier.
5G
5G is the fifth-generation mobile phone produced and released by various companies in 2019. This generation of mobile phones claims faster data transfer, improved security, increased processing power, screen and camera quality, and battery life.
Also, with the expansion of 5G networks, more powerful encryption is used than in previous generations. This technology attracts many users due to its features and capabilities, such as better and more stable connection, higher speed, and reduced delay. However, because the number of devices connected to the network is much higher in 5G networks, it is very important to pay attention to the security of these networks. For this reason, stronger encryption and security protocols protect user information in these networks.
Solutions to increase the security of IoT devices
Internet of Things or IoT (Internet of Things) refers to electronic devices connected to the Internet that can communicate with each other and other computer systems and share information. These devices include smart watches, smart home devices, smart cars, smart medical equipment, etc.
IoT allows users to use various services and facilities in a more convenient way using devices that are connected to the Internet. Control and management of home devices, health status tracking, car status control, and the like are from this category.
Although IoT provides many possibilities for users, there are also concerns about security and privacy. For example, IoT devices may have security weaknesses, and hackers may gain access to sensitive user information. To avoid this problem, it is recommended that users use security solutions, which we will describe below.
1- Device software update
Updating the software of IoT devices is very important. This action improves the security of the device and prevents vulnerability and new threats.
2- Using strong encryption
Using strong encryption for IoT device communications can prevent unauthorized access to information.
3- Using two-factor encryption
Two-factor authentication (2FA) is a two-step authentication method in which, in addition to a password, another factor, such as a code sent to a mobile phone or a fingerprint, is also required to enter a user account. This additional security method protects the user account against attacks such as Brute Force and Dictionary Attacks.
Using two-factor encryption can increase the security of IoT devices. In this method, to enter the device, instead of a username and password, it is necessary to verify the identity using two factors, such as fingerprints or visual or audio tokens.
4- Use of firewall
A firewall is software or hardware designed to protect a computer network from attacks and unauthorized access. As an entry and exit point for network traffic, a firewall improves the protection of network systems by applying security rules and settings, including blocking unnecessary ports, restricting access to specific services, and preventing communication with suspicious servers.
A firewall acts as a firewall for network systems that tries to block attacks and allow authorized traffic to target systems. Using a firewall for IoT devices can prevent users from unauthorized access.
5- Using detection and prevention of attacks
Attack Detection and Prevention Solutions include methods and tools to identify and prevent attacks on computer systems and communication networks. These methods usually include a combination of hardware and software methods that, working together, can prevent various attacks such as DDoS attacks, intrusion attacks, database intrusion attacks, and the like. These solutions usually use different algorithms, such as machine learning algorithms, behavioral analysis, pattern analysis, and protocol analysis. These solutions can use various methods such as filtering traffic, blocking suspicious IPs, using firewalls, and creating warning messages.
Using attack detection and prevention strategies such as threat detection, behavioral analysis, and network traffic monitoring can prevent attacks on IoT devices. In general, increasing the security of IoT devices is very important, and all available solutions should be used to prevent threats.