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- Annual ADFSL Conference on Digital Forensics, Security and Law (70)
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Articles 1 - 30 of 97
Full-Text Articles in Aviation Safety and Security
Sequential Causal Architecture For Multimodal Aviation Accident Prediction, Kaitlyn Cavanaugh, Isaac Morrison
Sequential Causal Architecture For Multimodal Aviation Accident Prediction, Kaitlyn Cavanaugh, Isaac Morrison
Discovery Day - Daytona Beach
Aviation accidents are rarely the result of a single failure but rather from a complex causal chain of latent failures. While traditional data mining models often predict incident occurrence, they frequently overlook the sequential mechanics defined by known accident causation theoretical frameworks like the Swiss Cheese Model and the FAA's HFACS. This project addresses the need for interpretable, reliable, multi-stage forecasting by proposing a Sequential Causal Architecture that transforms theoretical causation models into a structured Directed Acyclic Graph (DAG) for multimodal accident causation chain prediction. Data from the NTSB and DOT is used and connected together in a meaningful way …
Small Uas Detection: Threat Intelligence & Risk Management Project, Tyler Johnson
Small Uas Detection: Threat Intelligence & Risk Management Project, Tyler Johnson
Discovery Day - Daytona Beach
The TRANSPORTATION SECURITY ADMINISTRATION / FEDERAL AIR MARSHAL SUAS DETECTION: THREAT INTELLIGENCE & RISK MANAGEMENT PROJECT addresses the emerging safety and security challenges posed by the rapid growth of small Unmanned Aircraft Systems (sUAS) in complex airspace environments. This study analyzed 92 days of sensor-captured Remote Identification (RID) data collected near Fort Lauderdale-Hollywood International Airport (FLL) to assess operational behaviors, aviation risk, and ground risk associated with drone activity. The primary objective of this research is to identify patterns of unauthorized or hazardous sUAS operations to enhance situational awareness and inform actionable risk-mitigation strategies. The analysis identified 335 flights from …
An Evaluation Of Machine Learning Models' Efficacy In Determining Uav Spoofing Attacks, Nicolas Machado, Jaxon Selzer
An Evaluation Of Machine Learning Models' Efficacy In Determining Uav Spoofing Attacks, Nicolas Machado, Jaxon Selzer
Discovery Day - Daytona Beach
An Evaluation of Machine Learning Models' Efficacy in Determining UAV Spoofing Attacks - The rapid integration of Unmanned Aerial Vehicles (UAVs) into urban airspace has introduced significant cybersecurity concerns, particularly due to vulnerabilities in Automatic Dependent Surveillance–Broadcast (ADS-B), which lacks authentication and encryption. This project addresses the problem of detecting spoofing and data manipulation attacks that can compromise UAV safety and mission reliability. The objective of this work is to evaluate the effectiveness of machine learning–based anomaly detection, specifically Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) networks, as protocol-agnostic solutions for identifying anomalous UAV behavior. To achieve this, …
A System Safety Approach To Assuring Artificial Intelligence Enabled Functions In Civil Aviation, Evan Bear, Quinn Galen
A System Safety Approach To Assuring Artificial Intelligence Enabled Functions In Civil Aviation, Evan Bear, Quinn Galen
Discovery Day - Daytona Beach
Artificial intelligence and machine learning techniques are increasingly proposed for use in safety-critical civil aviation functions including perception decision support and pilot assistance. Existing aviation safety and certification standards such as ARP4754A and DO-178C were developed under assumptions of determinism explicit requirements and complete behavioral specification which do not directly apply to learning-enabled systems. This mismatch has created uncertainty regarding how artificial intelligence enabled avionics can be safely assured and certified. This paper presents a system safety approach for assuring artificial intelligence enabled functions within existing aviation certification frameworks. In this approach safety assurance is based on explicitly identifying the …
Meeting The Moment With Ai-Employer Informed Education, Brent Terwilliger, John Faraca
Meeting The Moment With Ai-Employer Informed Education, Brent Terwilliger, John Faraca
Publications
As artificial intelligence transforms aviation, aerospace, and autonomy-related sectors, higher education must adapt to meet evolving workforce demands. This session shares emerging findings from a nationwide study led by Embry-Riddle Aeronautical University, focused on employer perceptions of AI adoption, responsible use, and workforce preparedness in domains including uncrewed systems, space systems, robotics, and advanced air mobility. Based on a structured survey and follow-up interviews, the presentation explores how organizations are using AI tools, from generative platforms to enterprise systems, and defining effective and inappropriate use in operational contexts. Participants will gain insight into critical concerns (e.g., data privacy, compliance, security, …
Aircraft Bird Strike Risk Prediction Using Machine Learning And Analytic Hierarchy Process, Jason Anthony Powell
Aircraft Bird Strike Risk Prediction Using Machine Learning And Analytic Hierarchy Process, Jason Anthony Powell
Doctoral Dissertations and Master's Theses
To address the limitations of Next Generation Radar-based bird strike forecasting, this study modeled 12 spatiotemporal weather features from the National Oceanic and Atmospheric Administration alongside bird strike risk using Long Short-Term Memory Recurrent Neural Network (LSTM-RNN), XGBoost regression tree, and Bayesian network algorithms. Five years of bird strike data from four geographically diverse airfields served as the target risk variable, categorized as low, moderate, or severe based on Department of the Air Force risk models. The ensemble model, which combines the LSTM-RNN and XGBoost regression algorithms, yielded the most accurate forecasts, achieving 80% to 93% accuracy across all airfields, …
Beyond The Blue Skies: A Comprehensive Guide For Risk Assessment In Aviation, Leila Halawi, Mark Miller, Sam Holley
Beyond The Blue Skies: A Comprehensive Guide For Risk Assessment In Aviation, Leila Halawi, Mark Miller, Sam Holley
Publications
Risk assessment in aviation is a critical process that safeguards the safety and reliability of operations. Aviation operations encompass inherent risks, from mechanical failures to human errors and environmental factors. The significance of these risks may be severe, leading to accidents, injuries, and loss of life. Recognizing and mitigating risks is supreme in this dynamic environment, where emerging technologies and innovation constantly reshape this industry. This chapter includes an in-depth explanation of risk management and analysis, leading to the core elements of risk assessment specifically for aviation operations. We will describe the process and explore some of the applications and …
Smart Airports: Artificial Intelligence–Enabled Internet Of Things Networks Using Blockchain Technology, Edwin Ongola
Smart Airports: Artificial Intelligence–Enabled Internet Of Things Networks Using Blockchain Technology, Edwin Ongola
Journal of Aviation Technology and Engineering
This article provides a perspective on how an internet of heterogeneous self-service airport terminal systems can be used for data collection, which is stored on a private or consortium blockchain depending on the ownership or operations of an airport or both. Such a setup would help to increase efficiency, reduce costs, and improve traveler experience at airport terminals. Moreover, it would allow airports to gather data directly from passengers as opposed to waiting to receive the same data from airlines. Subsequently, this data, now on a blockchain system, becomes a data source for other applications such as machine learning. In …
Using Natural Language Processing To Identify Mental Health Indicators In Aviation Voluntary Safety Reports, Michael Sawyer, Katherine Berry, Amelia Kinsella, R Jordan Hinson, Edward Bynum
Using Natural Language Processing To Identify Mental Health Indicators In Aviation Voluntary Safety Reports, Michael Sawyer, Katherine Berry, Amelia Kinsella, R Jordan Hinson, Edward Bynum
National Training Aircraft Symposium (NTAS)
Voluntary Safety Reporting Programs (VSRPs) are a critical tool in the aviation industry for monitoring safety issues observed by the frontline workforce. While VSRPs primarily focus on operational safety, report narratives often describe factors such as fatigue, workload, culture, staffing, and health, directly or indirectly impacting mental health. These reports can provide individual and organizational insights into aviation personnel's physical and psychological well-being. This poster introduces the AVIation Analytic Neural network for Safety events (AVIAN-S) model as a potential tool to extract and monitor these insights. AVIAN-S is a novel machine-learning model that leverages natural language processing (NLP) to analyze …
Fostering Trust In Artificial Intelligence In Commercial Aviation: An Exploratory Study, Leila Halawi, Mark Miller, Sam Holley
Fostering Trust In Artificial Intelligence In Commercial Aviation: An Exploratory Study, Leila Halawi, Mark Miller, Sam Holley
Publications
Artificial intelligence (AI) is a transformative force, compelling industries to adapt their operations, management systems, and workforce capabilities. The aviation sector finds itself at the forefront of this transformation, confronted with the imperative to navigate the complex dynamics of trust amidst AI's integration. Through a comprehensive survey involving 310 professionals from across the US commercial aviation sector, the research aims to shed light on the trust construct. The exploratory study provides critical insights for strategic AI adoption within the industry. A crosstabulation explored how employee trust in AI for decision-making differed across various demographic groups. In addition, a onesample T-test …
Virtual Reality & Pilot Training: Existing Technologies, Challenges & Opportunities, Tim Marron, Niall Dungan, Brian Mac Namee, Anna Donnla O'Hagan
Virtual Reality & Pilot Training: Existing Technologies, Challenges & Opportunities, Tim Marron, Niall Dungan, Brian Mac Namee, Anna Donnla O'Hagan
Journal of Aviation/Aerospace Education & Research
The introduction of virtual reality (VR) to flying training has recently gained much attention, with numerous VR companies, such as Loft Dynamics and VRpilot, looking to enhance the training process. Such a considerable change to how pilots are trained is a subject that warrants careful consideration. Examining the effect that VR has on learning in other areas gives us an idea of how VR can be suitably applied to flying training. Some of the benefits offered by VR include increased safety, decreased costs, and increased environmental sustainability. Nevertheless, some challenges ahead for developers to consider are negative transfer of learning, …
Railroad Condition Monitoring Using Distributed Acoustic Sensing And Deep Learning Techniques, Md Arifur Rahman
Railroad Condition Monitoring Using Distributed Acoustic Sensing And Deep Learning Techniques, Md Arifur Rahman
College of Graduate Studies: Theses & Dissertations
Proper condition monitoring has been a major issue among railroad administrations since it might cause catastrophic dilemmas that lead to fatalities or damage to the infrastructure. Although various aspects of train safety have been conducted by scholars, in-motion monitoring detection of defect occurrence, cause, and severity is still a big concern. Hence extensive studies are still required to enhance the accuracy of inspection methods for railroad condition monitoring (CM). Distributed acoustic sensing (DAS) has been recognized as a promising method because of its sensing capabilities over long distances and for massive structures. As DAS produces large datasets, algorithms for precise …
The Evolution Of Ai On The Commercial Flight Deck: Finding Balance Between Efficiency And Safety While Maintaining The Integrity Of Operator Trust, Mark Miller, Sam Holley, Leila Halawi
The Evolution Of Ai On The Commercial Flight Deck: Finding Balance Between Efficiency And Safety While Maintaining The Integrity Of Operator Trust, Mark Miller, Sam Holley, Leila Halawi
Publications
As artificial intelligence (AI) seeks to improve modern society, the commercial aviation industry offers a significant opportunity. Although many parts of commercial aviation including maintenance, the ramp, and air traffic control show promise to integrate AI, the highly computerized digital flight deck (DFD) could be challenging. The researchers seek to understand what role AI could provide going forward by assessing AI evolution on the commercial flight deck over the past 50 years. A modified SHELL diagram is used to complete a Human Factors (HF) analysis of the early use for AI on the commercial flight deck through introduction of the …
Timestamp Estimation From Outdoor Scenes, Tawfiq Salem, Jisoo Hwang, Rafael Padilha
Timestamp Estimation From Outdoor Scenes, Tawfiq Salem, Jisoo Hwang, Rafael Padilha
Annual ADFSL Conference on Digital Forensics, Security and Law
The increasing availability of smartphones allowed people to easily capture and share images on the internet. These images are often associated with metadata, including the image capture time (timestamp) and the location where the image was captured (geolocation). The metadata associated with images provides valuable information to better understand scenes and events presented in these images. The timestamp can be manipulated intentionally to provide false information to convey a twisted version of reality. Images with manipulated timestamps are often used as a cover-up for wrongdoing or broadcasting false claims and competing views on the internet. Estimating the time of capture …
Anatomy Of An Internet Hijack And Interception Attack: A Global And Educational Perspective, Ben A. Scott, Michael N. Johnstone, Patryk Szewczyk
Anatomy Of An Internet Hijack And Interception Attack: A Global And Educational Perspective, Ben A. Scott, Michael N. Johnstone, Patryk Szewczyk
Annual ADFSL Conference on Digital Forensics, Security and Law
The Internet’s underlying vulnerable protocol infrastructure is a rich target for cyber crime, cyber espionage and cyber warfare operations. The stability and security of the Internet infrastructure are important to the function of global matters of state, critical infrastructure, global e-commerce and election systems. There are global approaches to tackle Internet security challenges that include governance, law, educational and technical perspectives. This paper reviews a number of approaches to these challenges, the increasingly surgical attacks that target the underlying vulnerable protocol infrastructure of the Internet, and the extant cyber security education curricula; we find the majority of predominant cyber security …
A Lightweight Reliably Quantified Deepfake Detection Approach, Tianyi Wang, Kam Pui Chow
A Lightweight Reliably Quantified Deepfake Detection Approach, Tianyi Wang, Kam Pui Chow
Annual ADFSL Conference on Digital Forensics, Security and Law
Deepfake has brought huge threats to society such that everyone can become a potential victim. Current Deepfake detection approaches have unsatisfactory performance in either accuracy or efficiency. Meanwhile, most models are only evaluated on different benchmark test datasets with different accuracies, which could not imitate the real-life Deepfake unknown population. As Deepfake cases have already been raised and brought challenges at the court, it is disappointed that no existing work has studied the model reliability and attempted to make the detection model act as the evidence at the court. We propose a lightweight Deepfake detection deep learning approach using the …
A Low-Cost Machine Learning Based Network Intrusion Detection System With Data Privacy Preservation, Jyoti Fakirah, Lauhim Mahfuz Zishan, Roshni Mooruth, Michael L. Johnstone, Wencheng Yang
A Low-Cost Machine Learning Based Network Intrusion Detection System With Data Privacy Preservation, Jyoti Fakirah, Lauhim Mahfuz Zishan, Roshni Mooruth, Michael L. Johnstone, Wencheng Yang
Annual ADFSL Conference on Digital Forensics, Security and Law
Network intrusion is a well-studied area of cyber security. Current machine learning-based network intrusion detection systems (NIDSs) monitor network data and the patterns within those data but at the cost of presenting significant issues in terms of privacy violations which may threaten end-user privacy. Therefore, to mitigate risk and preserve a balance between security and privacy, it is imperative to protect user privacy with respect to intrusion data. Moreover, cost is a driver of a machine learning-based NIDS because such systems are increasingly being deployed on resource-limited edge devices. To solve these issues, in this paper we propose a NIDS …
Human-Controlled Fuzzing With Afl, Maxim Grishin, Igor Korkin, Phd
Human-Controlled Fuzzing With Afl, Maxim Grishin, Igor Korkin, Phd
Annual ADFSL Conference on Digital Forensics, Security and Law
Fuzzing techniques are applied to reveal different types of bugs and vulnerabilities. American Fuzzy Lop (AFL) is a free most popular software fuzzer used by many other fuzzing frameworks. AFL supports autonomous mode of operation that uses the previous step output into the next step, as a result fuzzer spends a lot of time analyzing minor code sections. By making fuzzing process more focused and human controlled security expert can save time and find more bugs in less time. We designed a new module that can fuzz only the specified functions. As a result, the chosen ones will be inspected …
The Amorphous Nature Of Hackers: An Exploratory Study, Kento Yasuhara, Daniel Walnycky, Ibrahim Baggili, Ahmed Alhishwan
The Amorphous Nature Of Hackers: An Exploratory Study, Kento Yasuhara, Daniel Walnycky, Ibrahim Baggili, Ahmed Alhishwan
Annual ADFSL Conference on Digital Forensics, Security and Law
In this work, we aim to better understand outsider perspectives of the hacker community through a series of situation based survey questions. By doing this, we hope to gain insight into the overall reputation of hackers from participants in a wide range of technical and non-technical backgrounds. This is important to digital forensics since convicted hackers will be tried by people, each with their own perception of who hackers are. Do cyber crimes and national security issues negatively affect people’s perceptions of hackers? Does hacktivism and information warfare positively affect people’s perception of hackers? Do individual personality factors affect one’s …
Digital Forensics For Mobility As A Service Platform: Analysis Of Uber Application On Iphone And Cloud, Nina Matulis, Umit Karabiyik
Digital Forensics For Mobility As A Service Platform: Analysis Of Uber Application On Iphone And Cloud, Nina Matulis, Umit Karabiyik
Annual ADFSL Conference on Digital Forensics, Security and Law
Uber is a ride-hailing smartphone application (app) that allows users to order a ride in a highly efficient manner. The Uber app provides Mobility as a Service and allows users to easily order a ride in a private car with just a few clicks. Uber stores large amounts of data on both the mobile device the app is being used on, and in the cloud. Examples of this data include geolocation data, date/time, origin/destination addresses, departure/arrival times, and distance. Uber geolocation data has been previously researched to investigate the privacy of the Uber app; however, there is minimal research relating …
Smart Home Forensics: Identifying Ddos Attack Patterns On Iot Devices, Samuel Ho, Hope Greeson, Umit Karabiyik
Smart Home Forensics: Identifying Ddos Attack Patterns On Iot Devices, Samuel Ho, Hope Greeson, Umit Karabiyik
Annual ADFSL Conference on Digital Forensics, Security and Law
Smart homes are becoming more common as more people integrate IoT devices into their home environment. As such, these devices have access to personal data on their homeowners’ networks. One of the advantages of IoT devices is that they are compact. However, this limits the incorporation of security measures in their hardware. Misconfigured IoT devices are commonly the target of malicious attacks. Additionally, distributed denial-of-service attacks are becoming more common due to applications and software that provides users with easy-to-use user interfaces. Since one vulnerable device is all an attacker needs to launch an attack on a network, in regards …
Microsoft Defender Will Be Defended: Memoryranger Prevents Blinding Windows Av, Denis Pogonin, Igor Korkin, Phd
Microsoft Defender Will Be Defended: Memoryranger Prevents Blinding Windows Av, Denis Pogonin, Igor Korkin, Phd
Annual ADFSL Conference on Digital Forensics, Security and Law
Windows OS is facing a huge rise in kernel attacks. An overview of popular techniques that result in loading kernel drivers will be presented. One of the key targets of modern threats is disabling and blinding Microsoft Defender, a default Windows AV. The analysis of recent driver-based attacks will be given, the challenge is to block them. The survey of user- and kernel-level attacks on Microsoft Defender will be given. One of the recently published attackers’ techniques abuses Mandatory Integrity Control (MIC) and Security Reference Monitor (SRM) by modifying Integrity Level and Debug Privileges for the Microsoft Defender via syscalls. …
Detection Of Overlapping Passive Manipulation Techniques In Image Forensics, Gianna S. Lint, Umit Karabiyik
Detection Of Overlapping Passive Manipulation Techniques In Image Forensics, Gianna S. Lint, Umit Karabiyik
Annual ADFSL Conference on Digital Forensics, Security and Law
With a growing number of images uploaded daily to social media sites, it is essential to understand if an image can be used to trace its origin. Forensic investigations are focusing on analyzing images that are uploaded to social media sites resulting in an emphasis on building and validating tools. There has been a strong focus on understanding active manipulation or tampering techniques and building tools for analysis. However, research on manipulation is often studied in a vacuum, involving only one technique at a time. Additionally, less focus has been placed on passive manipulation, which can occur by simply uploading …
Soarnet, Deep Learning Thermal Detection For Free Flight, Jake T. Tallman
Soarnet, Deep Learning Thermal Detection For Free Flight, Jake T. Tallman
Master's Theses
Thermals are regions of rising hot air formed on the ground through the warming of the surface by the sun. Thermals are commonly used by birds and glider pilots to extend flight duration, increase cross-country distance, and conserve energy. This kind of powerless flight using natural sources of lift is called soaring. Once a thermal is encountered, the pilot flies in circles to keep within the thermal, so gaining altitude before flying off to the next thermal and towards the destination. A single thermal can net a pilot thousands of feet of elevation gain, however estimating thermal locations is not …
Forensic Analysis Of Spy Applications In Android Devices, Shinelle Hutchinson, Umit Karabiyik
Forensic Analysis Of Spy Applications In Android Devices, Shinelle Hutchinson, Umit Karabiyik
Annual ADFSL Conference on Digital Forensics, Security and Law
Smartphones with Google's Android operating system are becoming more and more popular each year, and with this increased user base, comes increased opportunities to collect more of these users' private data. There have been several instances of malware being made available via the Google Play Store, which is one of the predominant means for users to download applications. One effective way of collecting users' private data is by using Android Spyware. In this paper, we conduct a forensic analysis of a malicious Android spyware application and present our findings. We also highlight what information the application accesses and what it …
Suas: Cybersecurity Threats, Vulnerabilities, And Exploits, Philip Craiger, Gary Kessler, William Rose
Suas: Cybersecurity Threats, Vulnerabilities, And Exploits, Philip Craiger, Gary Kessler, William Rose
National Training Aircraft Symposium (NTAS)
The FAA predicts that purchases of hobbyist small unmanned aerial systems (sUAS) will grow from 1.9 million in 2016 to 4.3 million by 2020, and commercial sUAS to increase from 600,000 in 2016 to 2.7 million by 2020. sUAS, often referred to as 'drones,' are comprised of aeronautical hardware, a CPU, RAM, onboard storage, radio frequency communications, sensors, a camera, and a controller used by the pilot-in-command (PIC). Some have argued that a sUAS is essentially a flying computer. As such, sUAS are sometimes susceptible to many of the types of attacks that are often used on PC-based computers attached …
Contents, Adfsl
Contents, Adfsl
Annual ADFSL Conference on Digital Forensics, Security and Law
No abstract provided.
Front Matter, Adfsl
Front Matter, Adfsl
Annual ADFSL Conference on Digital Forensics, Security and Law
No abstract provided.
Analysis Of Data Erasure Capability On Sshd Drives For Data Recovery, Andrew Blyth
Analysis Of Data Erasure Capability On Sshd Drives For Data Recovery, Andrew Blyth
Annual ADFSL Conference on Digital Forensics, Security and Law
Data Protection and Computer Forensics/Anti-Forensics has now become a critical area of concern for organizations. A key element to this is how data is sanitized at end of life. In this paper we explore Hybrid Solid State Hybrid Drives (SSHD) and the impact that various Computer Forensics and Data Recovery techniques have when performing data erasure upon a SSHD.
Knowledge Expiration In Security Awareness Training, Tianjian Zhang
Knowledge Expiration In Security Awareness Training, Tianjian Zhang
Annual ADFSL Conference on Digital Forensics, Security and Law
No abstract provided.