Predicting Attack Surface Effects on Attack Vectors in an Open Congested Network Transmission Session by Machine Learning

<p>This paper examined the impact of a network attack on a congested transmission session. The research is motivated by the fact that the previous research community has neglected to evaluate security issues related to network congestion environments, and has instead concentrated on resolving congestion issues only. At any point in time, attackers can take advantage of the congestion problem, exploit the attack surface, and inject attack vectors. In order to circumvent this issue, a machine learning algorithm is trained to correlate attack vectors from the attack surface in a network congestion signals environment with the value of decisions over time in order to maximise expected attack vectors from the attack surface. Experimental scenario that dwell on transmission rate overwhelming transmission session, resulting in a standing queue was used. The experiment produced a dataset in which a TCP transmission through bursting transmission were capture. The data was acquired using a variety of experimental scenarios. Nave Bayes, and K-Nearest Neighbours prediction analyses demonstrate strong prediction performance. As a result, this study re-establishes the association between attack surface and vectors with network attack prediction. </p>

DTN Trustworthiness for Permafrost Telemetry IoT Network

The SHETLAND-NET research project aims to build an Internet of Things (IoT) telemetry service in Antarctica to automatize the data collection of permafrost research studies on interconnecting remote wireless sensor networks (WSNs) through near vertical incidence skywave (NVIS) long fat networks (LFN). The proposed architecture presents some properties from challenging networks that require the use of delay tolerant networking (DTN) opportunistic techniques that send the collected data during the night as a bulk data transfer whenever a link comes available. This process might result in network congestion and packet loss. This is a complex architecture that demands a thorough assessment of the solution’s viability and an analysis of the transport protocols in order to find the option which best suits the use case to achieve superior trustworthiness in network congestion situations. A heterogeneous layer-based model is used to measure and improve the trustworthiness of the service. The scenario and different transport protocols are modeled to be compared, and the system’s trustworthiness is assessed through simulations.