Improving Ethics Surrounding Collegiate-Level Hacking Education: Recommended Implementation Plan & Affiliation With Peer-Led Initiatives,
2024
University at Albany, SUNY
Improving Ethics Surrounding Collegiate-Level Hacking Education: Recommended Implementation Plan & Affiliation With Peer-Led Initiatives, Shannon Morgan, Dr. Sanjay Goel
Military Cyber Affairs
Cybersecurity has become a pertinent concern, as novel technological innovations create opportunities for threat actors to exfiltrate sensitive data. To meet the demand for professionals in the workforce, universities have ramped up their academic offerings to provide a broad range of cyber-related programs (e.g., cybersecurity, informatics, information technology, digital forensics, computer science, & engineering). As the tactics, techniques, and procedures (TTPs) of hackers evolve, the knowledge and skillset required to be an effective cybersecurity professional have escalated accordingly. Therefore, it is critical to train cyber students both technically and theoretically to actively combat cyber criminals and protect the confidentiality, integrity, …
Using Digital Twins To Protect Biomanufacturing From Cyberattacks,
2024
Washington State University
Using Digital Twins To Protect Biomanufacturing From Cyberattacks, Brenden Fraser-Hevlin, Alec W. Schuler, B. Arda Gozen, Bernard J. Van Wie
Military Cyber Affairs
Understanding of the intersection of cyber vulnerabilities and bioprocess regulation is critical with the rise of artificial intelligence and machine learning in manufacturing. We detail a case study in which we model cyberattacks on network-mediated signals from a novel bioreactor, where it is important to control medium feed rates to maintain cell proliferation. We use a digital twin counterpart reactor to compare glucose and oxygen sensor signals from the bioreactor to predictions from a kinetic growth model, allowing discernment of faulty sensors from hacked signals. Our results demonstrate a successful biomanufacturing cyberattack detection system based on fundamental process control principles.
Characterizing Advanced Persistent Threats Through The Lens Of Cyber Attack Flows,
2024
University of Colorado, Colorado Springs (UCCS)
Characterizing Advanced Persistent Threats Through The Lens Of Cyber Attack Flows, Logan Zeien, Caleb Chang, Ltc Ekzhin Ear, Dr. Shouhuai Xu
Military Cyber Affairs
Effective cyber defense must build upon a deep understanding of real-world cyberattacks to guide the design and deployment of appropriate defensive measures against current and future attacks. In this abridged paper (of which the full paper is available online), we present important concepts for understanding Advanced Persistent Threats (APTs), our methodology to characterize APTs through the lens of attack flows, and a detailed case study of APT28 that demonstrates our method’s viability to draw useful insights. This paper makes three technical contributions. First, we propose a novel method of constructing attack flows to describe APTs. This abstraction allows technical audiences, …
Generative Machine Learning For Cyber Security,
2024
Washington State University
Generative Machine Learning For Cyber Security, James Halvorsen, Dr. Assefaw Gebremedhin
Military Cyber Affairs
Automated approaches to cyber security based on machine learning will be necessary to combat the next generation of cyber-attacks. Current machine learning tools, however, are difficult to develop and deploy due to issues such as data availability and high false positive rates. Generative models can help solve data-related issues by creating high quality synthetic data for training and testing. Furthermore, some generative architectures are multipurpose, and when used for tasks such as intrusion detection, can outperform existing classifier models. This paper demonstrates how the future of cyber security stands to benefit from continued research on generative models.
Machine Learning Security For Tactical Operations,
2024
Virginia Tech
Machine Learning Security For Tactical Operations, Dr. Denaria Fields, Shakiya A. Friend, Andrew Hermansen, Dr. Tugba Erpek, Dr. Yalin E. Sagduyu
Military Cyber Affairs
Deep learning finds rich applications in the tactical domain by learning from diverse data sources and performing difficult tasks to support mission-critical applications. However, deep learning models are susceptible to various attacks and exploits. In this paper, we first discuss application areas of deep learning in the tactical domain. Next, we present adversarial machine learning as an emerging attack vector and discuss the impact of adversarial attacks on the deep learning performance. Finally, we discuss potential defense methods that can be applied against these attacks.
Securing The Void: Assessing The Dynamic Threat Landscape Of Space,
2024
University at Albany
Securing The Void: Assessing The Dynamic Threat Landscape Of Space, Brianna Bace, Dr. Unal Tatar
Military Cyber Affairs
Outer space is a strategic and multifaceted domain that is a crossroads for political, military, and economic interests. From a defense perspective, the U.S. military and intelligence community rely heavily on satellite networks to meet national security objectives and execute military operations and intelligence gathering. This paper examines the evolving threat landscape of the space sector, encompassing natural and man-made perils, emphasizing the rise of cyber threats and the complexity introduced by dual-use technology and commercialization. It also explores the implications for security and resilience, advocating for collaborative efforts among international organizations, governments, and industry to safeguard the space sector.
Examining The Impact Of Customer Rfp Characteristics On Award Compliance,
2024
University of Arkansas, Fayetteville
Examining The Impact Of Customer Rfp Characteristics On Award Compliance, Laasya Ravipati
Data Science Undergraduate Honors Theses
In the context of intermodal transportation, understanding the dynamics of award compliance holds significant importance for operational efficiency and strategic decision-making. Award compliance refers to the percentage of awarded freight volume that is realized, indicating the extent to which contractual agreements are fulfilled. This analysis delves into the intricate relationship between customer characteristics and award compliance, aiming to provide valuable insights into the variability and predictability of compliance rates. By analyzing Request for Pricing (RFP) data and primary awarded freight volumes, the study seeks to address the need for more accurate volume estimations, crucial for sales planning, revenue projections, and …
The Impact Of Using Standard Quality Measures Such As Iso 9001:2015 On Emerging Software Companies Created With Agile Methodologies.,
2024
Harrisburg University of Science and Technology
The Impact Of Using Standard Quality Measures Such As Iso 9001:2015 On Emerging Software Companies Created With Agile Methodologies., Elisa Orillac
Harrisburg University Dissertations and Theses
This qualitative research aimed to analyze the impact of applying quality measure standards, specifically ISO 9001:2015, in emerging software companies that have decided to manage their projects through Agile methodologies. While Agile methodologies are well known for their continuous delivery of software, the quality that results from these projects is not always guaranteed. This research aimed to evaluate what benefits in terms of cost, timely delivery of working software, and production have companies who already applied QMS had. Or, if applying the QMS had a negative result, why was this the case? The hypothesis for the research was that those …
Integrated Organizational Machine Learning For Aviation Flight Data,
2024
Kansas State University
Integrated Organizational Machine Learning For Aviation Flight Data, Michael J. Pritchard, Austin T. Walden, Paul J. Thomas
Journal of Aviation/Aerospace Education & Research
Increased availability of data and computing power has allowed organizations to apply machine learning techniques to various fleet monitoring activities. Additionally, our ability to acquire aircraft data has increased due to the miniaturization of small form factor computing machines. Aircraft data collection processes contain many data features in the form of multivariate time series (continuous, discrete, categorical, etc.) which can be used to train machine learning models. Yet, three major challenges still face many flight organizations: 1) integration and automation of data collection frameworks, 2) data cleanup and preparation, and 3) developing an embedded machine learning framework. Data cleanup and …
Interpersonal Skills In A Sociotechnical System: A Training Gap In Flight Decks,
2024
University of Washington
Interpersonal Skills In A Sociotechnical System: A Training Gap In Flight Decks, Kimberly Perkins, Sourojit Ghosh, Crystal Hall
Journal of Aviation/Aerospace Education & Research
This research analyzed the perceptions of interpersonal skills on established aviation safety models, Crew Resource Management (CRM), and Threat and Error Management (TEM) using feedback from industry pilots. The flight deck is a sociotechnical system where much research has focused on the technical aspect, whereas we spotlight its socio aspect. The aviation industry must invest in training pilots on interpersonal skills to enhance safety through increased efficacy of safety models integrated throughout existing training programs. A 34-question survey was disseminated across both commercial and business aviation pilots (N=822). We explored three research questions regarding pilots’ perceived training on interpersonal skills …
Hyper-Heuristic Approach With K-Means Clustering For Inter-Cell Scheduling,
2024
School of Mathematics and Computer Science, Yan'an University, Yan'an 716000, China
Hyper-Heuristic Approach With K-Means Clustering For Inter-Cell Scheduling, Yanlin Zhao, Yunna Tian
Journal of System Simulation
Abstract: According to the actual production situation of China's manufacturing industry, a hyperheuristic algorithm based on K-means clustering is proposed for inter-cell scheduling problem of flexible job-shop. K-means clustering is applied to group entities with similar attributes into the corresponding work cluster decision blocks, and the ant colony algorithm is used to select heuristic rules for each decision block. The optimal scheduling solutions are generated by using corresponding heuristic rules for scheduling of entities in each decision block. Computational results show that, the computational granularity is properly increased by the form of decision blocks, and the computational efficiency of the …
Distributed Energy Management Strategy Of Microgrid Based On Master-Slave Game,
2024
School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China
Distributed Energy Management Strategy Of Microgrid Based On Master-Slave Game, Miaomiao Ma, Hao Wang, Lipeng Dong, Xiangjie Liu
Journal of System Simulation
Abstract: Under the operation mode of power market, based on two-layer master-slave game, a distributed energy management strategy for the microgrid is proposed to tackle the conflict between the overall optimal operation of renewable microgrid and the maximum profit of each investor. To fully consider the balance between energy supply and demand, the concept of power trading agent is introduced, and an integrated demand response strategy based on consumer satisfaction and adjustable load is proposed on the user side. Considering the initiative and decision-making ability of power supply and load, the decision-making game model is established with power trading agent …
Optimization Of Urban Traffic Microsimulation Model For Carbon Emission Reduction,
2024
Beijing City Interface Technology Co., Ltd., Beijing 100045, China; School of Civil and Transportation Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, China
Optimization Of Urban Traffic Microsimulation Model For Carbon Emission Reduction, Bo Liu, Jianxin Lin, Yini Liu, Dong Zhang
Journal of System Simulation
Abstract: To assess the environmental benefits of transportation management or control strategies, a method to effectively integrate the micro-traffic simulation model and the micro-vehicle emission model is proposed. VISSIM platform is used to build a case micro traffic simulation model. K-means clustering method is used to divide the driving behavior into 4 types based on the acceleration and deceleration characteristics of different speed intervals of the trajectory data, and the global parameters of the simulation model are calibrated based on the driving characteristics, which quantitatively describe the total sensitivity of the parameters and the sensitivity of the interactions between the …
Modeling And Analysis Of Hybrid Traffic Flow Considering Actual Behavior Of Platoon,
2024
Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming 650500, China
Modeling And Analysis Of Hybrid Traffic Flow Considering Actual Behavior Of Platoon, Xi Wang, Xiujian Yang, Xiaohan Jia, Shenyi Wang
Journal of System Simulation
Abstract: To explore the effect of actual behavior of autonomous vehicular platoon on traffic flow, aiming at the hybrid traffic flow mixed with predecessor following(PF) platoon which is modeled according to the actual control strategy, a hybrid traffic flow model is established based on cellular automata(CA) modeling method. Simulation analysis shows that the effect of platoon characteristics such as time headway, market penetration, platoon size, and control gains on hybrid traffic flow presents coupling and nonlinear properties. The spatiotemporal behavior of hybrid traffic flow with different platoon characteristics is generally much different. Reducing time headway or increasing platoon market penetration …
Dynamic Path Planning For Mobile Robot Based On Rrt* And Dynamic Window Approach,
2024
Nanjing University of Information Science &Technology, Nanjing 210000, China
Dynamic Path Planning For Mobile Robot Based On Rrt* And Dynamic Window Approach, Rui Zhang, Li Zhou, Zhengyang Liu
Journal of System Simulation
Abstract: A dynamic path planning method combining RRT* and dynamic window approach(DWA) is proposed to realize the obstacle avoidance of mobile robot in complex environment of dynamic obstacles. Improved RRT* algorithm is used to generate the global optimal safe path based on the known environment information. By eliminating the dangerous nodes generated by RRT* algorithm, the security of global path is ensured. Greedy algorithm is used to remove the redundant nodes in the path to reduce the length of global path. DWA is used to track along the global optimal path planned by the improved RRT* algorithm. When static obstacles …
Collaborative Navigation Method For 5g Cluster Uav Based On Configuration Optimization,
2024
State Grid Jiangsu Electric Power Co., Ltd., Nanjing 210024, China
Collaborative Navigation Method For 5g Cluster Uav Based On Configuration Optimization, Chao Gao, Zheng Huang, Xuan Zhao, Hongxing Wang, Tao Long
Journal of System Simulation
Abstract: The existing range based cooperative navigation methods for clustered UAVs generally ignore the impact of space configuration on positioning and energy determination, which makes it difficult to obtain the accurate navigation and positioning results. In view of this, a collaborative navigation method is proposed for 5G clustered UAVs based on spatial configuration optimization. The relative ranging error model of UAVs based on 5G signals in complex environments is constructed, and the optimization strategy for collaborative navigation nodes is established based on the minimum geometric division of precision(GDOP) criterion to achieve the real-time optimization of collaborative navigation spatial configuration; A …
Incremental Image Dehazing Algorithm Based On Multiple Transfer Attention,
2024
Zhengzhou Hengda Intelligent Control Technology Company Limited, Zhengzhou 450000, China
Incremental Image Dehazing Algorithm Based On Multiple Transfer Attention, Jinyang Wei, Keping Wang, Yi Yang, Shumin Fei
Journal of System Simulation
Abstract: In order to improve the processing ability of the depth-neural network dehazing algorithm to the supplementary data set, and to make the network differently process the image features of different importance to improve the dehazing ability of the network, an incremental dehazing algorithm based on multiple migration of attention is proposed. The teacher's attention generation network in the form of Encoder-Decoder extracts the multiple attention of labels and haze, which is used it as the label of the characteristic migration media network to constrain the network training to form the migration media attention as close as possible to the …
Path Planning Rapid Algorithm Based On Modified Rrt* For Unmanned Surface Vessel,
2024
Naval Submarine Academy, Qingdao 266199, China; Pilot National Laboratory for Marine Science and Technology, Qingdao 266237, China; Qingdao Institute of collaborative innovation, Qingdao 266071, China
Path Planning Rapid Algorithm Based On Modified Rrt* For Unmanned Surface Vessel, Zhaozhen Jiang, Wenlong Wang, Wenqi Sun
Journal of System Simulation
Abstract: Aiming at the weak purposiveness of rapidly exploring random tree algorithm in USV path planning, a modified rapid algorithm is proposed. The artificial potential field method is improved and the force analysis in four directions is added to comprehensively calculate the resultant force on USV. The calculation method of steering angle is redefined to avoid entering the local optimal trap and can reach the target point smoothly to obtain an initial path. The initial path is used to set the random point sampling area of rapidly exploring random tree algorithm. By reducing the probability of random points generated in …
Research On Cross-Domain Unmanned Swarm Cooperative Anti-Submarine Search Method,
2024
Air traffic control and navigation college, Air Force Engineering University, Xi'an 710051, China; Shaanxi Province Lab. of Meta-synthesis for Electronic & Information System, Xi'an 710051, China
Research On Cross-Domain Unmanned Swarm Cooperative Anti-Submarine Search Method, Ning Wang, Xiaolong Liang, Jiaqiang Zhang, Yueqi Hou, Aiwu Yang
Journal of System Simulation
Abstract: For the maritime ASW search, a cross-domain unmanned swarm cooperative search method is proposed in which USVs are used as the communication relay of UAVs. The digital grid map is used to characterize the mission area and the kinematic model of cross-domain platform is constructed. The cooperative method of cross-domain unmanned systems is proposed, and the distributed information fusion mechanism of unmanned systems is designed. The search objective function for heterogeneous platforms is designed to guide the unmanned systems to make real-time decisions in search task. The simulation results show that the proposed method can be effective to the …
Simulation Verification And Decision-Making Key Technologies Of Unmanned Swarm Game Confrontation: A Survey,
2024
Air Traffic Control and Navigation College, Air Force Engineering University, Xi'an 710051, China; Shaanxi Key Laboratory of Meta-Synthesis for Electronic and Information System, Xi'an 710051, China
Simulation Verification And Decision-Making Key Technologies Of Unmanned Swarm Game Confrontation: A Survey, Xiaolong Liang, Aiwu Yang, Jiaqiang Zhang, Yueqi Hou, Ning Wang, Xiao Huang, Junbin Gong
Journal of System Simulation
Abstract: Unmanned swarm game confrontation is a new combat mode and plays a crucial role in intelligent warfare. Its core is the autonomous generation of a series of game confrontation decision sequences to "empower" the swarm. The progress of system simulation verification for the unmanned swarm game confrontation is analyzed. The key technologies of the autonomous decision-making are discussed from three aspects, technology based on expert systems and game theory, technology based on swarm intelligence and optimization theory, and technology based on neural networks and reinforcement learning. The key technology research conducted by the author's team on the autonomous decisionmaking …
