1
Faculty of Artificial Intelligence, Egyptian Russian University (ERU), Cairo, Egypt
(mahmoud.zaher@eru.edu.eg)
2
Faculty of Computers and Information, Sadat Academy for Management Sciences, Cairo, Egypt & French University in Cairo, Egypt
(nabil.omr@sadatacademy.edu.eg)
Abstract :
A wireless sensor network, also known as a WSN, is made up of thousands of minuscule sensor nodes that are connected to one another in order to monitor, track, and organize data collected in an unattended environment in the most prominent location. Due to its one-of-a-kind qualities, it has, the wireless sensor network is gaining traction in a variety of sectors and put to use in a wide range of applications, including surveillance, healthcare, and industry. These networks exposed to a variety of security flaws and major threats because of their dynamic design and deployment in an unsupervised environment. Cybercriminals prey on individuals who utilize the internet as well as organizations in order to get sensitive information. The hackers were able to access critical data on the company's systems, such as login information, credit card details, and bank account numbers. Phishing attacks are a sort of cyberattack in which hackers trick internet users into believing their websites are authentic in order to collect the users' private information. The purpose of these attacks is to steal this information. Malware assaults begin with the covert installation of malicious software on corporate servers or user PCs via the use of the internet. The attackers then continue to steal every piece of information that kept on the targeted server or computer. Malware used in an ever-increasing number of attacks these days. An incursion into a network is a kind of attack in which the perpetrator seeks to take possession of all of the network's resources. Approaches based on heuristic analysis and visual resemblance used, regardless of whether they are blacklisted or whitelisted.
Keywords :
Cyber-Attacks; Intrusion Detection System; HTTP Sites; Attackers.
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| Style | # |
|---|---|
| MLA | Mahmoud A. Zaher, Nabil M. Eldakhly. "Cyber Attack Detection in Wireless Adhoc Network using Artificial Intelligence." International Journal of Wireless and Ad Hoc Communication, Vol. 6, No. 2, 2023 ,PP. 18-33 (Doi : https://doi.org/10.54216/IJWAC.060202) |
| APA | Mahmoud A. Zaher, Nabil M. Eldakhly. (2023). Cyber Attack Detection in Wireless Adhoc Network using Artificial Intelligence. Journal of International Journal of Wireless and Ad Hoc Communication, 6 ( 2 ), 18-33 (Doi : https://doi.org/10.54216/IJWAC.060202) |
| Chicago | Mahmoud A. Zaher, Nabil M. Eldakhly. "Cyber Attack Detection in Wireless Adhoc Network using Artificial Intelligence." Journal of International Journal of Wireless and Ad Hoc Communication, 6 no. 2 (2023): 18-33 (Doi : https://doi.org/10.54216/IJWAC.060202) |
| Harvard | Mahmoud A. Zaher, Nabil M. Eldakhly. (2023). Cyber Attack Detection in Wireless Adhoc Network using Artificial Intelligence. Journal of International Journal of Wireless and Ad Hoc Communication, 6 ( 2 ), 18-33 (Doi : https://doi.org/10.54216/IJWAC.060202) |
| Vancouver | Mahmoud A. Zaher, Nabil M. Eldakhly. Cyber Attack Detection in Wireless Adhoc Network using Artificial Intelligence. Journal of International Journal of Wireless and Ad Hoc Communication, (2023); 6 ( 2 ): 18-33 (Doi : https://doi.org/10.54216/IJWAC.060202) |
| IEEE | Mahmoud A. Zaher, Nabil M. Eldakhly, Cyber Attack Detection in Wireless Adhoc Network using Artificial Intelligence, Journal of International Journal of Wireless and Ad Hoc Communication, Vol. 6 , No. 2 , (2023) : 18-33 (Doi : https://doi.org/10.54216/IJWAC.060202) |