An Adaptive Auto Incident Response based Security Framework for Wireless Network Systems

Abstract

The growth of wireless network systems is expanding deploying techniques to drive more network
capacity and enabling low device complexity with low energy consumption to improve Quality of
Service also a proper balance between data transmission and data integrity. Market Growth of Wireless
Network System is expected at 62.8 million USD and is likely to grow at a CAGR at 17.5% to
reach a valuation of 95.3 billion USD in 2024. Market grows significantly due to demand for network
infrastructure and advancement in Artificial Intelligence (AI), Machine Learning (ML), and Big
Data Analytics. The economy focuses on developing communication between network devices for
ensuring secure communication using wireless systems. The nodes of network systems have limited
power capacities where some batteries are chargeable or non-rechargeable by influencing the power
of network system we can increase the performance of the wireless network system. These systems
are generally susceptible to failures and attacks so it is necessary to impose stringent countermeasures
on data integrity, data reliability, the transmission of data through network traffic in critical
infrastructure. In this paper, we have proposed a model which is well suited for wireless network
systems and devices to identify, detect, categorize and respond to attacks which in turn will generate
warnings and alarms in case any malicious activity is observed. Implementing and deploying a
model to effectively respond to incidents, selecting response actions for ensuring better protection of
wireless network systems with the help of the AES encryption method. The system also integrates
into generating warning messages and alarms/alerts raising concerns upon detecting or identifying
any kind of intrusion.