Engineering Commons^™

Large-Scale Experimental Study On The Impact Of Air Cleaning & Ventilation On Indoor Air Quality And Student Illness-Related Absenteeism, Daud Nosham

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

This large-scale randomized experimental field study investigated the effect of portable air purifiers (PAPs) on classroom’s air quality and student’s illness related absenteeism. PAPs were installed in 317 classrooms from various school districts located in Eastern Nebraska. The classrooms were randomly assigned into four conditions: three treatment conditions (T1, T2 & T3) and one control condition (device without any filter). T1 was equipped with HEPA filters, T2 added Activated Carbon (AC) layer to HEPA, and T3 further integrated Germicidal Ultraviolet (GUV) alongside HEPA and AC filters. The measured variables were carbon dioxide (CO2), fine particles (PN2.5) and coarse particles (PNcoarse), …

Application Of Natural Language Processing And Machine Learning For Analyzing Mining Accident Reports And Automating The Process Of Root Cause Analysis, Siddhartha Agarwal, Y. P. Chugh, Atul Singh, Vikram Sakinala, Ayan Mukherjee, Balbir Prasad, Cihan Dagli, Yuhao Zou

Engineering Management and Systems Engineering Faculty Research & Creative Works

Coal mining accidents are a major concern worldwide, necessitating effective safety measures and comprehensive analysis to prevent future accidents. Our proposed solution is the first attempt for Indian mines, inspired by the potential of Natural Language Processing (NLP) that can read and analyze vast repositories of accident records in seconds. In combination with machine learning (ML), NLP algorithms can extract unstructured text by eliminating manual data entry errors, reading poorly scanned reports, and understanding multiple versions of the event and cluster documents based on types that would otherwise take months to collate. In the case of accident records, it can …

Effects Of Wc Additions On The Phase Formation Of (Hf,Nb,Ta,Ti,Zr)C-(Hf,Nb,Ta,Ti,Zr)B2 High Entropy Dual Phase Ceramics, Rubia Hassan, William G. Fahrenholtz, Gregory E. Hilmas

Materials Science and Engineering Faculty Research & Creative Works

High entropy dual phase (Hf,Nb,Ta,Ti,Zr)C-(Hf,Nb,Ta,Ti,Zr)B2 ultra-high temperature ceramics were produced from powders synthesized by boro-carbothermal reduction. Systematic additions of 2.5 wt%, 5 wt%, and 10 wt% WC were incorporated after powder synthesis. Additions of 2.5 wt% and 5 wt% WC dissolved into the host ceramics, resulting in complete solid solution formation and nearly full densification. In contrast, a secondary monoboride phase evolved for the composition with 10 wt% WC, in addition to the main high entropy carbide and diboride phases. Thermodynamic analysis revealed that WB formation was favorable for WC additions in the presence of metal diborides at the sintering …

Micro/Nanomechanical Properties Of Top-Seeded Melt Grown Ybco Single Crystals Determined Using Depth Sensing Indentation, Ugur Kolemen, Cafer Mert Yesilkanat, Fikret Yilmaz, Fatih Dogan, Orhan Uzun

Materials Science and Engineering Faculty Research & Creative Works

Mechanical properties of the bulk YBa2Cu3O7-x (YBCO) single crystal superconductor, prepared by using the Top Seeded Melt Growth (TSMG) method, were determined. Property measurements were conducted by the nanoindentation method under various loads and the micro indentation method at different temperatures. Hardness (H) and reduced elastic modulus (Er) values were calculated by using the Oliver–Pharr method. According to hf/h max values found from load- displacement curves, there is a sink in behavior around outer rim of the indents that was confirmed by atomic force microscopy (AFM) analysis. Nanoindentation analyses conducted on upper section, middle section and subsection revealed that all …

Effect Of Powder Recycling On Powder Characteristics And Mechanical Properties Of Materials Produced By Laser Powder Bed Fusion (Lpbf): A Review, Mihiretu Ganta, Marta Kurek, Arezoo Emdadi, Tadeusz Łagoda, Marek Pagáč

Materials Science and Engineering Faculty Research & Creative Works

As the Laser powder bed fusion (LPBF) process advances toward industrial-scale production, the sustainability of metal powder feedstocks has become a focal point of research. The powder recycling approach, while environmentally and economically favorable, results in a series of physicochemical variations that could compromise the part quality. The resulting variation in powder characteristics with powder recycling could affect the powder layer density and melt pool dynamics, resulting in defect formation and hindering the structural integrity of LPBFed parts. These alterations pose significant constraints to mechanical performance, particularly in fatigue-sensitive applications where even minor imperfections can substantially reduce service life. The …

Variable-Temperature Plasmonic High-Entropy Carbides, Simon Divilov, Sean D. Griesemer, Robert C. Koennecker, Michael J. Ammendola, Adam C. Zettel, Hagen Eckert, Jeffrey R. Shallenberger, Xiomara Campilongo, William G. Fahrenholtz, Arrigo Calzolari, Douglas E. Wolfe, Stefano Curtarolo

Materials Science and Engineering Faculty Research & Creative Works

Effective thermal management at variable and extreme temperatures face limitations for the development of novel energy and aerospace applications. Plasmonic approaches, shown to be capable of tailoring black-body emission, could be effective if materials with high-temperature and tunable plasmonic resonance were available. Here, we report a synergy between experimental and theoretical results proving that many high-entropy transition metal carbides, consisting of four or more metals at equal molar ratio, have plasmonic resonance at room, high (>1000∘C) and variable temperatures. We also found that these high-entropy carbides can be tuned and show considerable plasmonic thermal cycling stability. This paradigm-shift approach …

A Precipitation-Hardened High-Entropy Alloy With Excellent Mechanical Properties Additively Manufactured By In-Situ Alloying, Matthew Luebbe, Shahryar Mooraj, Jonathan Poplawsky, Hans Pommerenke, Wen Chen, Haiming Wen

Materials Science and Engineering Faculty Research & Creative Works

Studies on precipitation-hardened high-entropy alloys (PHEAs) have demonstrated high strength, good ductility, and thermal stability, making them excellent candidates for high-temperature structural applications such as nuclear reactors. However, many complex parts for those applications would need to be produced via additive manufacturing (AM), whose rapid cooling rates and multiple heating cycles could change the microstructure of the chosen alloys and accordingly their mechanical properties. A PHEA, (Fe0.3Ni0.3Mn0.3Cr0.1)88Ti4Al8, which was developed and produced via conventional manufacturing in our previous work with high strength but low ductility, was chosen to test the effects of AM on the microstructure and mechanical properties. Scanning …

Experimental Determination Of Tnt Equivalence Values For Binary Energetic Materials, Gracie May M. James, Rachel L. Bauer, Emily M. Johnson, Catherine E. Johnson

Mining Engineering Faculty Research & Creative Works

TNT equivalency quantifies the impact of energetic materials relative to TNT, aiding in safety guidelines and performance evaluations. Despite widespread use in industry, military, and research, many binary energetics lack published TNT equivalence values. This study experimentally determines TNT equivalency values for Helix, Texpak, Rimfire, Tannerite, and Kinepak using three tests: (1) plate dent, (2) reaction velocity and (3) air blast. Each test evaluates distinct aspects of energetic performance, addressing both close-in destructive power and downstream effects. Helix produced TNT equivalence values from 0.64 to 1.10, comparable to TNT, while Kinepak had lower values (0.18 to 0.58) indicating limited brisance, …

Data Driven Design Of Ultra High Performance Concrete Prospects And Application, Bryan K. Aylas-Paredes, Taihao Han, Advaith Neithalath, Jie Huang, Ashutosh Goel, Aditya Kumar, Narayanan Neithalath

Electrical and Computer Engineering Faculty Research & Creative Works

Ultra-high-performance concrete (UHPC) is a specialized class of cementitious composites that is increasingly used in various applications, including bridge decks, connections between precast components, piers, columns, overlays, and the repair and strengthening of bridge elements. The mechanical and durability properties of UHPC are significantly influenced by factors such as low water-to-binder ratios, the inclusion of supplementary cementitious materials (SCMs), and fiber reinforcement. Machine learning (ML) has been employed to predict the performance of UHPC and optimize its mixture designs by using various raw materials. This study first provides a comprehensive review of ML applications in UHPC, focusing on predicting workability, …

Design And Testing Of A Vr Escape Room Game For Philippine Martial Law History, Eric Cesar Vidal, Jr., Johanna Marion R. Torres, Jesus Alvaro Pato, Kenneth King L. Ko

Department of Information Systems & Computer Science Faculty Publications

This paper presents a Virtual Reality Educational Escape Room game where players learn about the highly divisive Martial Law period in Philippine history. We describe the game’s general design and the results of a user test to evaluate the game in terms of VR presence, immersion, and overall usability.

User Evaluation Of A Virtual Patient For Philippine Medical Education, Ma. Mercedes T. Rodrigo, Samantha Castaneda, James Alvir Maclin V. Alaan, Paolo Santino P. Caoile

Department of Information Systems & Computer Science Faculty Publications

Caladrius is a virtual patient system designed for use in Philippine medical schools. It responds to the need for medical interview training, for greater variety in teaching-learning strategies, and for culturally appropriate technologies. It has two versions: a text-only version whose interface is similar to a chat interface, and an audio version that accepts speech input and responds with speech output. In a prior test of Caladrius, users requested improved audio response time and the inclusion of different patient personalities. A subsequent version of Caladrius was created to comply with these requests. As much of the lag was attributable to …

Extreme Bandgap Recessed-Gate Metal Oxide Semiconductor Heterostructure Field Effect Transistors With Drain Current 0.28 A Mm−1 And Threshold Voltage −1.5 V, Abdullah Al Mamun Mazumder, Abdullah Mamun, Kenneth Stephenson, Kamal Hussain, Tariq Jamil, Grigory Simin, Asif Khan

Faculty Publications

Herein, the first demonstration of hybrid high-k oxide (ZrO2-Al2O3) incorporation into extreme bandgap (EBG) Al_0.87Ga_0.13N/Al_0.64Ga_0.36N metal-oxide-semiconductor heterostructure field-effect transistors (MOSHFETs) is presented, with both planar and recessed-gate designs on the same AlN/sapphire template with a state-of-the-art low contact resistance of 1.4 Ω mm (contact resistivity, ρc ≈ 5.7 × 10−6 Ω cm2). The recessed-gate MOSHFETs achieve a threshold voltage shift of ΔVTH = 5.8 V, highlighting improved channel control. Static output measurements reveal a peak drain current (IDS) of 340 mA mm⁻¹ for the planar …

An Audio Data-Driven Roadway Digital Twin And Its Underlying Framework For A Digitized Transportation Construction Environment, Anisha Deria, Pedro J. Chacon Dominguez, Yong-Cheol Lee, Jin W. Choi

Michigan Tech Publications

The increasing need to build and maintain transportation systems has led project managers to manage multiple projects simultaneously. Roadway projects often entail several miles of job site, making it difficult to keep track of progress and maintenance activities. To improve the situation, this study proposes an audio data-driven roadway digital twin framework for real-time and remote monitoring of construction projects. The latent characteristics of a digital twin required for establishing a digitized work environment were investigated. As a primary method of seamlessly linking virtual and physical environments, audio data classified and analyzed by deep neural network (DNN) has been employed …

Data-Driven Evaluation Of Sustainable Waste-To-Energy Pathways For Intelligent Urban Systems, Izech Brian O. Edwin, King Harold A. Recto

Electronics, Computer, and Communications Engineering Faculty Publications

The handling of municipal solid waste (MSW) in swiftly urbanizing Philippine cities poses intricate energy and governance challenges. In Baguio City, reliance on landfills has reached critical levels due to diminishing capacity, rising transport costs, and opposition to trash transfers by nearby LGUs. Although shaped by unique topographical and governance constraints, Baguio’s situation reflects issues faced by other rapidly growing Philippine cities; therefore, analyzing it offers insights for national MSW decision-making. This study applies a triple bottom line (TBL) framework to assess three management scenarios: (1) Status Quo, where all MSW is landfilled with no energy recovery; (2) Landfill with …

Engineering Risk And Indigenous Resilience Toward Intelligent Decision Support For Mining In Ancestral Lands, Izech Brian O. Edwin, King Harold A. Recto

Electronics, Computer, and Communications Engineering Faculty Publications

Mining within ancestral territories reveals an ongoing conflict between technical viability and Indigenous consent. This collaborative study, conducted by an engineering scholar and a policy researcher of Indigenous heritage in Benguet among the Ibaloi and Kankanaey peoples, investigates how risk transparency and policy alignment can bridge existing divides, while formulating principles applicable to other Indigenous mining contexts. The study provides an initial evaluation of the feasibility of a proposed large-scale mining operation within a risk-informed, data-driven governance framework. Three elements of engineering risk were assessed utilizing literature-derived and proxy parameters: (1) Land degradation is indicated by a Soil Productivity Index …

Investigating The Efficiency Of Ingan P-N-P-N Homojunction Solar Cells, Moath Alhejji, Mohammad Alavijeh, Jacob Kupernik, Mirsaeid Sarollahi, Abbas Jammali, Seyed Taghavi, Reem Alhelais, Md Hel Uddin Maruf, Morgan Ware

Electrical Engineering and Computer Science Faculty Publications and Presentations

This research investigates the development of a novel p-n-p-n homostructure solar cell, through semiconductor simulations using the Nextnano software. InGaN was used as a model system in order to achieve a bandgap with optimized efficiency for a p-n homojunction solar cell. By increasing the uniform doping concentration from 1.5*10(16) cm(-3) to 1.5*10(17) cm(-3), the open circuit voltage (V-oc) increased while the short-circuit current density (J(sc)) decreased, as expected in simple p-n junctions. The p-n-p-n structure achieved a peak efficiency of 32.91% at a doping level of 6.5*10(16) cm(-3), a similar to 7% improvement over a conventional p-n junction's 25.31% efficiency …

Porous Triboelectric Nanogenerator For Load Sensing Of Total Knee Replacement, Elham Mahmoudi, Adam Garry Redgrift, Emre Salman, Milutin Stanacevic, Ryan Willing, Shahrzad Towfighian

Mechanical Engineering Faculty Scholarship

This study addresses the critical need for self-powered, durable pressure sensors in Total Knee Replacement (TKR) implants to enable the collection of post-operative information. The scope of this research encompasses the design, development, and testing of a triboelectric nanogenerator (TENG) integrated into an instrumented knee implant for energy harvesting and pressure sensing. The authors’ unique approach involves utilizing a porous silicone rubber as a dielectric material. This allows the TENG to withstand forces up to 2000 N and generate a maximum power output of 18 μW. Theoretical modeling combined with experimental validation provides deeper insight into the fundamental operating principles. …

Bridging Cybersecurity Practice And Law: A Hands-On, Scenario-Based Curriculum Using The Nice Framework To Foster Skill Development, Colman Mcguan, Aadithyan Vijaya Raghavan, Komala M. Mandapati, Chansu Yu, Brian Ray, Debbie Jackson, Sathish Kumar

Electrical and Computer Engineering Faculty Publications

In an increasingly interconnected world, cybersecurity professionals play a pivotal role in safeguarding organizations from cyber threats. To secure their cyberspace, organizations are forced to adopt a cybersecurity framework such as the NIST National Initiative for Cybersecurity Education Workforce Framework for Cybersecurity (NICE Framework). Although these frameworks are a good starting point for businesses and offer critical information to identify, prevent, and respond to cyber incidents, they can be difficult to navigate and implement, particularly for small-medium businesses (SMBs). To help overcome this issue, this paper identifies the most frequent attack vectors to SMBs (Objective 1) and proposes a practical …

Learning To Accelerate Tightening Of Convex Relaxations Of The Ac Optimal Power Flow Problem, Faith Cengil, Harsha Nagarajan, Russell Bent, Sandra Eksioglu, Burak Eksioglu

Industrial Engineering Faculty Publications and Presentations

We propose a novel machine learning (ML)-based approach to significantly reduce the run times of the optimality-based bound tightening (OBBT) algorithm for strengthening the convex relaxations of the non-convex Alternating Current Optimal Power Flow (AC-OPF) problem. While OBBT can yield near-global solutions via tight convex relaxations, its runtime remains a critical bottleneck on large-scale power grids. Our key contribution is a dynamic policy that selects smaller subsets of voltage magnitude and phase-angle difference variables for sequential bound tightening at every iteration of the OBBT algorithm. This ensures that the bound-tightening process remains adaptive, thereby circumventing the stalling in the optimality …

Realization Of Deterministic Quantum Circuits For Non-Deterministic Or Incompletely Specified Quantum State Machines, Manjith Kumar, Marek Perkowski

Electrical and Computer Engineering Faculty Publications and Presentations

In classical logic design, there are machine learning methods based on converting a set of input-output traces to non-deterministic automata that are then converted to deterministic automata and synthesized using logic gates. This approach has not yet been extended to quantum automata. In this paper, we present a method to convert a set of input-output traces to a non-deterministic automaton, which is then converted to an incompletely specified multi-output Boolean function. The existing logic synthesis approaches for designing quantum circuits are insufficient to handle incompletely specified functions. So, we present a novel algorithm to synthesize logic functions with don’t cares …

Bim-To-Brick: Using Graph Modeling For Iot/Bms And Spatial Semantic Data Interoperability Within Digital Data Models Of Buildings, Filippo Vittori, Fu Chuan Tan, Laura Anna Pisello, Adrian Chong, Cristina Piselli, Clayton Miller

Research Collection College of Integrative Studies

The holistic management of a building requires data from heterogeneous sources such as building management systems (BMS), Internet-of-Things (IoT) sensor networks, and building information models (BIM), all aimed at environmental well-being. Data interoperability is a key component to eliminate silos of information, and using semantic web technologies like the BRICK schema, an effort to standardize semantic descriptions of the physical, logical, and virtual assets in buildings and the relationships between them, is a suitable approach. However, current data integration processes can involve significant manual interventions. This paper presents a methodology to automatically collect, assemble, and integrate information from a building …

Cross-Domain Disaggregation Of Electricity For Heating In All-Electric School Buildings – Learning From School Buildings With District Heating, Synne Krekling Lien, Ada Canaydin, Clayton Miller, Chun Fu, Hussain Kazmi, Jayaprakash Rajasekharan

Research Collection College of Integrative Studies

Electric heating is widespread in Norwegian buildings and significantly contributes to peak loads in the electricity grid. Non-residential buildings are typically heated either by district heating or a combination of electrical heating appliances. Despite its widespread use, most buildings lack sub-meters for electric heating. As a result, the true potential for energy efficiency and load flexibility from heating appliances in buildings remains unknown. Non-intrusive load monitoring and disaggregation techniques offer alternatives to sub-metering by using data-driven methods to extract electricity use for appliances from time-series data. However, little research has been conducted on disaggregating electrical heating loads from low-resolution data, …

Wearable Triboelectric Nanogenerators Based Sensors For Human Cardiovascular Monitoring: Progress And Perspectives, Mashrufa Akther, Andrea K. Quezada, Md. Arafat Hossain, Julia I. Salas, Md. Mahmud Alam, Mohammed Jasim Uddin

Mechanical Engineering Faculty Publications

Cardiovascular conditions remain the leading cause of death worldwide, driving a critical need for non-invasive, continuous, and dependable health monitoring results. Triboelectric nanogenerators have emerged as a groundbreaking technology enabling self-powered wearable sensors that convert natural biomechanical energy, such as heartbeat, pulse wave, and body motion, into electrical signals. The paper reviews the recent progress and development in TENG-based wearable sensors for cardiovascular monitoring, with a focus on monitoring particular and clinical healthcare. The working principles, advanced materials, structural designs, and integration with wireless data transmission, machine literacy, and bio-signal processing technologies are explored in this article. Operations, including heart …

Favorability Mapping For Hydrothermal Power Resource Assessments Of The Great Basin, Usa, Stanley P. Mordensky, Erick R. Burns, John Lipor, Jacob Deangelo

Electrical and Computer Engineering Faculty Publications and Presentations

Highlights

• • The new approach to predict hydrothermal resource favorability for the U.S. Great Basin is a synthesis of modern data-driven machine learning improvements from the last several years and predicts 85 % of power-producing systems with operating power plants in the most favorable 10 % of the total area with over half of the power-producing systems (10 of the 19 exposed power-producing systems and 5 of the 9 hidden power-producing systems) in the 99th percentile.
• • The new hydrothermal favorability map predicts both hidden and exposed power-producing hydrothermal systems equally well.
• • The new hydrothermal favorability map preferentially predicts …

Piezoelectric Energy Harvesting From Roadways: Challenges, Advances, And Future Directions, Heba Mohamed Gaber, Mohamed Abdel-Raheem

Civil Engineering Faculty Publications

As the global demand for renewable energy intensifies, piezoelectric energy harvesting from roadways has emerged as a promising avenue for sustainable power generation. This systematic literature review analyzes 61 peer-reviewed studies to assess the feasibility, performance, and potential of integrating piezoelectric systems into roadway infrastructure. While technology faces challenges, such as high installation costs, limited energy output, and a scarcity of thorough economic evaluations, findings suggest it holds considerable promise as a supplementary renewable energy source. The review analyzes the operational characteristics and efficiencies of various piezoelectric transducers, identifies key factors influencing system performance, and evaluates recent technological advances. It …

The Equity Implications Of Pecuniary Externalities On An Electric Grid, Charles Sims, Gasser G. Ali, J Scott Holladay, Tim Roberson, Chien-Fei Chen, Islam H. El-Haddad

Civil Engineering Faculty Publications

The adoption of rooftop photovoltaic (PV) systems can create upward pressure on retail electricity rates as utilities are forced to spread their fixed costs of generation and transmission across a smaller customer base. Since high-income households are more likely to purchase PV systems, low-income households may be disproportionately impacted by these rate increases. Using a novel combination of agent-based computational economic modeling and a choice experiment of rooftop solar adoption, we show how this pecuniary externality between low- and high-income customers increases low-income electricity bills by 10% in an area with some of the highest poverty rates in the United …

Advancements In Sinkhole Remediation: Field Data-Driven Sinkhole Grout Volume Prediction Model Via Machine Learning-Based Regression Analysis, Bubryur Kim, Yuvaraj Natarajan, K. R. Sri Preethaa, V. Danushkumar, Ryan Shamet, Jiannan Chen, Rui Xie, Timothy Copeland, Boo Hyun Nam, Jinwoo An

Civil Engineering Faculty Publications

Sinkhole formation poses a significant geohazard in karst regions, where unpredictable subsurface erosion often necessitates costly grouting for stabilization. Accurate estimation of grout volume remains a persistent challenge due to spatial variability, site-specific conditions, and the limitations of traditional empirical methods. This study introduces a novel machine learning-based regression model for grout volume prediction that integrates cone penetration test (CPT)-derived Sinkhole Resistance Ratio (SRR) values, spatial correlations between CPT and grouting points (GPs), and field-recorded grout volumes from six sinkhole sites in Florida. Three data transformation methods, the Proximal Allocation Method (PAM), the Equitable Distribution Method (EDM), and the Threshold-based …

Occurrence Of Per And Polyfluoroalkyl Substances In Rural Wastewater Treatment Plants And Comparison To Large Treatments Plants, Madeleine Rauhauser

Department of Civil and Environmental Engineering: Dissertations, Theses, and Student Research

Per and polyfluoroalkyl substances (PFAS) are a class of compounds defined by their carbon – fluorine bonds, which are incredibly strong. The strength of this bond makes these compounds very useful industrially, they are used as waterproof and grease proof coatings, and as fire retardants. The same thing that makes them useful industrially makes them incredibly recalcitrant in the environment, it is difficult to destroy these compounds. PFAS are also suspected to cause health impacts in people, such as kidney cancer and low birth weights. Wastewater has been commonly identified as a contributor to the amount of PFAS in the …

Further Evaluation Of Speed Tables On Roadway Curves: Simulation And Expeditionary Deployments, Nathan Reineke

Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research

The road network leading up to a United States military base is known as an Entry Control Facility, or ECF. Entry control facilities are used to shield military installations by monitoring vehicles and refusing access to unauthorized vehicles. Passive control devices, including speed tables, are used to disrupt or delay threat vehicles attempting to navigate ECFs at high speeds. The purpose of this research was to recommend optimized configurations of speed tables in combination with roadway curves which allow safe, efficient traversal for authorized vehicles and disruption or delay for threat vehicles.

First, an analytical model of a Tesla Model …

Securing Connected And Autonomous Vehicles, Owana Marzia Moushi

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

A vehicular network is susceptible to various security flaws and attacks. Cryptographic techniques are used in vehicular networks but these alone cannot provide proper security to the network. Identifying various types of attacks is necessary to secure vehicular communication networks. In this dissertation, we focused on detecting various insider attacks in vehicular networks to enhance the security of the network.

Our first contribution in this dissertation is the detection of both binary and multi-class data replay and data replay Sybil attacks in vehicular networks. A publicly available dataset, VeReMi-Extension is used to detect these attacks. This dataset has been reformulated …