Research
Mobile Adhoc Networks and Networking – An Overview of Existing Intrusion Prevention Techniques and Predictive Intrusion Prevention.
Intrusion Prevention in computer networking refers to the set of techniques and technologies used to detect and prevent unauthorized access, malicious activities, and attacks on a network. It involves actively monitoring network traffic, identifying potential threats or anomalies, and taking action to mitigate or block those threats. In the realms of Mobile Adhoc Networks and general computer networking, substantial work has pointed to the gaps experienced with respect to proactively identifying and mitigating risks and network malicious behaviours and attacks. Further research was conducted to establish the current state of contemporary intrusion detection, prediction and prevention techniques and their effectiveness to pro-actively identify and mitigate network attacks and malicious activity. However, it was found that the techniques utilized were very few or required futher accuracy improvements and for the identified effective techniques, they required substantial amount of data processing power and a robust network architecture to support its implementation. The work of this paper, introduces the integration of the MANET Risk Scoring methodology based on Axiom theory into the realm of general networking. All in an effort to increase the efficiency and accuracy of existing predictive intrusion prevention systems such as next generation Firewalls in corporate networks.
Mobile Adhoc Networks and Networking – Integrating Risk Profiles into Intrusion Prevention Systems to Improve Predictive Intrusion Prevention
Intrusion Prevention in computer networking refers to the set of techniques and technologies used to detect and prevent unauthorized access, malicious activities, and attacks on a network. It involves actively monitoring network traffic, identifying potential threats or anomalies, and taking action to mitigate or block those threats. In the realms of Mobile Adhoc Networks and computer networking, substantial work has pointed to the gaps experienced with respect to proactively identifying and mitigating risks and network malicious behaviours and attacks. This paper seeks to highlight the existing intrusion detection and prevention techniques currently being utilized in MANETS and general computer networking and how the introduction of the novel Risk Profile approach based on Axiom theory can be utilized or integrated to improve the accuracy of existing models of Intrusion Detection and Prevention systems. With a dual purposed aim of bolstering public confidence in utilizing MANETs and improving the security posture of networks which depend heavily on Security controls to protect their information and assets.
Mobile Adhoc Network Risk Profiles-An overview of Existing Network Traffic Datasets to determine Ideal Axiom Criteria
A Mobile Adhoc networks also known as MANET or Wireless Adhoc Network is a network that usually has aroutable networking environment on top of a Link Layer ad hoc network. It consist of a set of mobile nodes connected wirelessly in a self-configured, self-healing network without having a fixed infrastructure. Recent studies and fieldwork have pointed in the direction of making MANETS a publicly viable option in the event of another world event/crisis such as the recent COVID-19 pandemic. As opposed to their traditional military and emergency uses, this has become a focal point due to the evident strain that was observed on mainstream Internet Service Providers as substantial adjustments had to be made to facilitate a new ’working-from-home’ public. A primary aspect that must be considered before public adoption is addressing the issue of MANET risk and Security which leads into identifying and classifying risks associated with MANETS. This paper seeks to analyze the various existing fields and meta-data within various networking datasets, protocols as well as scenarios and subsequently establish what aspects of existing network traffic can be classified into axioms (Risk Classifying arguments) to determine Risk Profiles of MANETS. The paper also seeks to determine and propose the ideal data fields within Network traffic for classifying Risk Profiles.
