Open AccessAdaptive System to Improve Decision Making for Protecting Data Conveyed over WLAN
Author(s) -
Abdulkareem Merhej Radhi
Publication year - 2019
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.a1936.109119
Subject(s) - computer science , network packet , hacker , encryption , computer security , wireless network , computer network , wireless , data security , wi fi , data transmission , data mining , risk analysis (engineering) , telecommunications , medicine
In the past two decades, the rapid growth of demand for wireless data communications has become evident due to the unreliability of wired data communications, which has become inadequate due to high costs and management monitoring of its security problems. Furthermore, such data may be intercepted when transmitted via wire connections with a negative attack and its contents changed with illegal modification. Therefore, due to these circumstances, there is an urgent need to protect data and achieve a wireless local area network (WLAN) for transmission. Data protection is therefore required through the design and implementation of a rigid algorithm that reduces the risk of hacking into wireless networks and prevents hackers from finding inevitable vulnerabilities in the data protection system. This research paper introduces a new technology to protect data from potential risks and provides a new “type” of encryption algorithms that minimizes these risks. This technology relies on the adoption of renewable rules proposed as production bases based on ambiguous logic to accomplish the construction of an intelligent data analysis system and move forward with appropriate protection decisions. The targeted packets for the local area network were captured and analyzed using open source software “WIRESHARK”. Unsupervised learning classifier was used to monitor the network and detect the malicious intruders. The flow data have been collected and features are extracted and analyzed to examine the transmitted packets which were classified and ranked to have a specific cluster. Minimizing and comprising risk taking in consideration the imprecise data which was achieved via fuzzy rules. The results were discussed and concluded that potential risks could be minimized by the production rules that control the proposed data for the transferred encryption system. MATLAB 2014 toolkit based on a laptop with an Intel I3 processor and 4GB RAM was used.