8 Types of Network Attacks and Prevention Tools 2021

What are different types of network attacks and prevention for 2021 and Beyond?

Computer networks face numerous threats daily. Cyber-attacks target computer systems, networks, and technology-dependent enterprises.

Malicious codes are used in cyber-attacks to alter organization information in the network and disrupt operations.

Learn: 6 Types of Cyber Attacks & How to Prevent Them From Spoiling

Here are the Top 8 types of network attacks:

  1. Distributed denial of service (DDoS) attack: The main aim of the attack is to terminate service provision over the network. The attack is achieved by loading the network with junk information, which causes it to crash. From the huge traffic, authorized users of the organization will not access the resources they need to ensure service delivery. The attacks are commonly targeted towards the web servers of high performing organizations. The attack does not lead to stealing or losing information, but it delays service delivery, which brings losses to the company. The targeted organizations may include banks, media companies, and the government.
  2. Eavesdropping attack: The attack involves interception of network traffic. The attack is also known as snooping, whereby individuals intercepts the messages transmitted in a network between devices. The communication networks might be between smartphones, laptops or any other digital devices. The main targets in this attack are unsecured networks. The act is not easily detected because it does not disrupt the provision of resources or services. Client and server communication in the network should be secure.  The attack targets both transmitting and receiving devices in the system. The attack can be prevented by knowing all devices that are connected to the network. Organizations should also ensure that they know the software running in all the devices in the system.
  3. Brute-Force and Dictionary Network Attacks: The attacks aim at user accounts by trying to log in to their accounts by obtaining their passwords. It involves systematic checking and trying all possible passwords until an entry is gained. The attacks are mainly contacted through the front door. The acquisition of the credentials through the front door limits the suspicion of unauthorized entry. Brute-force involves repetitive entry of passwords obtained from dictionary software until the right password is retrieved. The process is slow since it starts from single characters to complicated passwords. The brute-force dictionary can make 100 to 1000 attacks every minute; the repetitive process is done until the password to the network is cracked. The attack targets switches, routers, and servers in the network.
  4. Insider threats: Authorized personnel in an organization might be involved in network attacks. Such attacks are not easily defended since the organizations aim at preventing external attacks. Insider attackers are familiar with the organization policies and network infrastructure giving them an upper hand over external attackers. Insider attacks can be made by installing Trojan viruses that aid in stealing sensitive data and information from the network. The attack also helps in denial of service when the attackers overload the system leading to a system crash.
  5. Man-in-the-Middle (MITM) attacks.The term refers to the individual who intercepts the conversation between two communicating devices in a network. The attack is made by acquiring a crucial public message transmission key by the attacker and then retransmit the message, and in the process, interchange the requested key with its key. After obtaining the key, the intruder controls the communication because he must receive the information before sending it to the receiver. The receiver and the sender cannot detect the intruder because there is no disruption. The “man-in-the-middle” modifies the message as he wishes before sending it to the receiver.
  6. Artificial Intelligence-powered attacks: Artificial Intelligence has been the anticipated move in the field of technology. The aspect of machine learning is an element of AI which aims at training the machine to perform tasks on its own. AI technology can be used to hack into systems such as drones and autonomous vehicles. The devices can be used as weapons of destruction. Through AI, network attacks such as identity theft, password cracking and denial of service are made more accessible. The damage caused by AI attacks can be extensive, affecting the country’s power supply system or hospital services.
  7. Phishing attacks: Through phishing, user data such as credit card information and login details are acquired using social engineering.  The attacker poses as trusted personnel and tricks an individual into opening a text message or an email. The message and the emails contain links that freeze the entire system and reveal sensitive information upon clicking. In government agencies, phishing attacks are used as entry platforms for other attacks such as advanced persistent threat (APT). Through APT, employees are used to gaining access to secured data and aid in malware distribution in the organization.
  8. Malware attacks: The attacks involve creating codes that compromise the system without the user’s consent. They are varied, ranging from spyware, ransomware and command and controls. Malware poses a great threat to networks since it spreads and causes damage to information without being detected. Malware attacks have the potential of damaging the entire system because of their persistence and fast spread.

Preventive measures against network attacks

  • Companies need to train and educate their employees using mock phishing. They can also install SPAM filters to identify information from unknown senders.
  • Organizations should install active Anti-malware software in computers and conduct regular scans. The scans aid in the identification and destruction of malware programs in the network.
  • Tackling insider threats requires the organization to train employees on the importance of reading terms and conditions before installing any software. There should be a strict policy against the installation of software from untrusted sources in the organization.
  • In a bid to prevent AI-powered attacks, it is important to distinguish human behaviour from bot behaviour. Through the machine, learning organizations can know how a typical user sits, talk, walk and hold devices. Any attempt to access resources and lack identified user behaviours could be classified as a fraud in the organization from the observation.
  • To prevent DDoS attacks on the network, organizations should buy more bandwidth. More bandwidth will enable the servers to hold the flooding when attacks attempt to attack the network. An organization can also perform load balancing by distributing its servers to different data centres hence building redundancy.

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