Computer Engineering Commons^™

Security Datasets For Network Research, Bruce Hartpence, Bill Stackpole, Daryl Johnson

Data

This document describes the content of the security traffic datasets included in this collection and the conditions under which the packets were collected. These datasets were assembled from 2023 onward. There will be periodic updates or additions to the dataset collection. The current collection includes a variety of nmap intense scans, an Address Resolution Protocol Man in the Middle (ARP MITM) attack, an Internet Control Message Protocol (ICMP) Redirect MITM and an active directory enumeration attack.

When referencing these datasets, please use the following DOI: 10.57673/gccis-qj60

Towards Reliable Multi-Path Routing : An Integrated Cooperation Model For Drones, Ibtihel Baddari, Abdelhak Mesbah, Maohamed Amine Riahla

Emirates Journal for Engineering Research

Ad-hoc networks have evolved into a vital wireless communication component by offering an adaptable infrastructure suitable for various scenarios in our increasingly interconnected and mobile world. However, this adaptability also exposes these networks to security challenges, given their dynamic nature, where nodes frequently join and leave. This dynamism is advantageous but presents resource constraints and vulnerability to malicious nodes, impacting data transmission reliability and security.

In this context, this article explores the development of a secure routing protocol for Ad-hoc networks based on a cooperation reinforcement model to reduce the degradation of routing performance. We leverage the reputation of nodes …

Proposed Mitigation Framework For The Internet Of Insecure Things, Mahmoud M. Elgindy, Sally M. Elghamrawy, Ali I. El-Desouky

Mansoura Engineering Journal

Intrusion detection systems IDS are increasingly utilizing machine learning methods. IDSs are important tools for ensuring the security of network data and resources. The Internet of Things (IoT) is an expanding network of intelligent machines and sensors. However, they are vulnerable to attackers because of the ubiquitous and extensive IoT networks. Datasets from intrusion detection systems (IDS) have been analyzed deep learning methods such as Bidirectional long-short term memory (BiLSTM). This research presents an BiLSTM intrusion detection framework with Principal Component Analysis PCA (PCA-LSTM-IDS). The PCA-LSTM-IDS is comprised of two layers: extracting layer which using PCA, and the anomaly BiLSTM …

Multifaceted Cybersecurity Analysis: Reconnaissance, Exploitation And Mitigation In A Controlled Network Environment, Austin Coontz

Williams Honors College, Honors Research Projects

This report details a network penetration test in a simulated environment using GNS3, focusing on the configuration of routers, switches, and hosts. The project successfully identified and exploited network vulnerabilities, including FTP access, misconfigured sudo permissions, and SMB protocol weaknesses. The penetration testing process utilized tools like fping and nmap for reconnaissance and vulnerability scanning, revealing the importance of device configurations in network security. The project concluded with mitigation strategies, emphasizing the need for secure access, robust password policies, and security controls. The experience underscored the significance of continuous learning and adaptation in the ever-evolving field of cybersecurity. The project …