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

Blockchain-Enabled Authenticated Key Agreement Scheme For Mobile Vehicles-Assisted Precision Agricultural Iot Networks, Anusha Vangala, Ashok Kumar Das, Ankush Mitra, Sajal K. Das, Youngho Park

Computer Science Faculty Research & Creative Works

Precision Farming Has a Positive Potential in the Agricultural Industry Regarding Water Conservation, Increased Productivity, Better Development of Rural Areas, and Increased Income. Blockchain Technology is a Better Alternative for Storing and Sharing Farm Data as It is Reliable, Transparent, Immutable, and Decentralized. Remote Monitoring of an Agricultural Field Requires Security Systems to Ensure that Any Sensitive Information is Exchanged Only among Authenticated Entities in the Network. to This End, We Design an Efficient Blockchain-Enabled Authenticated Key Agreement Scheme for Mobile Vehicles-Assisted Precision Agricultural Internet of Things (IoT) Networks Called AgroMobiBlock. the Limited Existing Work on Authentication in Agricultural Networks …

Security Of Internet Of Things (Iot) Using Federated Learning And Deep Learning — Recent Advancements, Issues And Prospects, Vinay Gugueoth, Sunitha Safavat, Sachin Shetty

Electrical & Computer Engineering Faculty Publications

There is a great demand for an efficient security framework which can secure IoT systems from potential adversarial attacks. However, it is challenging to design a suitable security model for IoT considering the dynamic and distributed nature of IoT. This motivates the researchers to focus more on investigating the role of machine learning (ML) in the designing of security models. A brief analysis of different ML algorithms for IoT security is discussed along with the advantages and limitations of ML algorithms. Existing studies state that ML algorithms suffer from the problem of high computational overhead and risk of privacy leakage. …