Digital Commons Network^™

From Framework To Toolchain: Implementing Zero Trust Architecture In Cloud-Native Environments For Dow Compliance, Shelby C. Snyder

Military Cyber Affairs

Federal agencies face a fiscal year 2027 target for enterprise-wide Zero Trust deployment, but NIST SP 800-207A defines logical components without identifying the Kubernetes technologies that implement them. This paper proposes a three-tier mapping of the Policy Engine, Policy Administrator, and Policy Enforcement Point to service mesh, microsegmentation, and perimeter tooling, stating the criteria by which each component is classified. It then applies a defined rubric to six Zero Trust vendors across component alignment, Kubernetes capability, federal authorization posture, and evidence quality, finding that no single vendor covers all three tiers. The mapping is a testable architectural proposition; a Stage …

Hybrid Deep (Cnn-Bilstm) Intrusion Detection For Defense And Mission-Critical Networks, Corey A Cheng, Jermaine Anim-Addo, Asma Jakir Hussain, Zion O Smith-Fox, Sanjay Goel, Yuksel Celik

Military Cyber Affairs

This article examines how hybrid deep learning can strengthen intrusion detection for military and defense networks. Using the CSE-CIC-IDS2018 dataset, the study evaluates a CNN-BiLSTM model designed to detect benign traffic and multiple attack categories, including DDoS, DoS, botnet, brute-force, web attack, and infiltration activity. The model achieved strong multi-class detection performance, with 0.9893 accuracy and 0.9979 ROC-AUC. The findings suggest that AI-supported intrusion detection can improve cyber defense operations, analyst triage, and protection of mission-critical networks.

Are Large Language Models Safe? A Vulnerability Analysis Of Generated Source Code, James Richards-Perhatch, Mitchell Milander, James M. Halvorsen, Assefaw Gebremedhin

Military Cyber Affairs

The increasing complexity of software and demands for rapid deployment have pushed the software industry to rely more on large language models (LLMs) in developing source code. However, as this technology is still relatively recent, questions can arise about the safety of the generated code. This paper presents an analysis of seven LLMs with respect to the presence of vulnerabilities within source code. Our findings show that LLMs are more likely to produce vulnerable web applications than vulnerable C programs, and that vulnerabilities are more likely to occur when program size and complexity increases.

Characterizing Advanced Persistent Threats With Cyber Attack Flow Metrics, Tyler Miller, Caleb Chang, Shouhuai Xu

Military Cyber Affairs

Cyber attack campaigns vary not only in scale but in structure, yet conventional characterizations often reduce them to a single dimension such as technique count or impact severity. In this paper we extend the concept of cyber attack flows by defining three new metrics, novelty, technique complexity and flow complexity. Then we characterize the attack flows of three advanced persistent threat campaigns using these metrics and draw insights regarding their capabilities. Our findings include that low novelty does not equate to low attack capabilities and that exploitation of an internet-facing appliance is a common initial attack vector.

Semantic Shields: Automating Critical Infrastructure Defense Via Nlp-Driven Ransomware Profiling, Henry Trowbridge, Ian Zalcberg, Ryan Schley, Carter Yagemann, Natasha Phan, Srikar Maduposu, Vimal Buck

Military Cyber Affairs

Ransomware poses a growing threat to critical infrastructure, where successful attacks can disrupt operational technology (OT) and industrial control systems (ICS) with significant public safety consequences. However, attributing ransomware incidents to specific threat actors remains challenging due to ransomware-as-a-service ecosystems, actor rebranding, and the obfuscation of traditional indicators of compromise. This paper presents Semantic Shields, an NLP-driven attribution framework that leverages BERT-generated semantic embeddings and DBSCAN clustering to profile ransomware actors through the linguistic characteristics of ransom notes. Using a dataset of 295 ransom notes from 189 distinct threat groups, the framework achieved an 87.2% true positive clustering rate and …

Closing The Interpretability Gap: Explainable Ml-Based Malware Detection For Defensive Cyberspace Operations, Tashi Stirewalt, Sean Hodgson, Puumaaya Tahiru, Assefaw Gebremedhin

Military Cyber Affairs

This paper presents an end-to-end, explainable malware triage pipeline designed for defense-oriented cyber operations. It combines high-performance static detection methods with analyst-centered interpretability. Utilizing the EMBER 2024 Windows PE subset, we train and evaluate four classifiers and select LightGBM as the production model based on its predictive performance, inference efficiency, and compatibility with exact tree-based attribution. The deployed system consists of four sequential components: PE feature extraction, malware probability scoring, dual explainability (using SHAP and LIME), and large language model (LLM) report generation, all integrated within a Flask web interface. On a temporal test set of 1,080,000 samples, LightGBM achieves …

Llm-Generated Countermeasures For Iot Cyberattacks, James Alger, Michael Tu

Military Cyber Affairs

The rapid expansion of the Internet of Things (IoT) has introduced significant cybersecurity challenges, particularly for resource-constrained devices that traditional intrusion detection systems often fail to protect effectively. This paper proposes a novel, two-phase autonomous security pipeline designed to bridge the gap between probabilistic threat detection and deterministic network enforcement. The framework first utilizes a custom Time Series Transformer (TST) to classify multivariate network traffic and identify specific attack vectors, such as ransomware, SQL injections, and malicious file uploads. In the second phase, an agentic AI layer, comprising a locally hosted Large Language Model (LLM) orchestrated via LangGraph, processes the …

Foreward, Todd Arnold

Military Cyber Affairs

No abstract provided.

Letter From The Director: Mastery In Practice, Joseph Schafer

Military Cyber Affairs

No abstract provided.

Journal Ida 2023 102 4

Journal IDA

The Journal IDA is a peer-reviewed, scientific periodical owned and published by the Indiana Dental Association, a constituent of the American Dental Association.

Journal IDA concentrates on the clinical aspects of dentistry, including case studies and research; practice management and business aspects of dentistry, from start up to transition; and also includes special and regular feature articles.

Journal Ida 2023 102 3

Journal IDA

The Journal IDA is a peer-reviewed, scientific periodical owned and published by the Indiana Dental Association, a constituent of the American Dental Association.

Journal IDA concentrates on the clinical aspects of dentistry, including case studies and research; practice management and business aspects of dentistry, from start up to transition; and also includes special and regular feature articles.

From Static Frameworks To Adaptive Evaluation: Piloting An Ai-Powered Evaluation Planner For Media Literacy And Digital Skills Interventions, Natalia Edisherashvili, Marit Puusepp, Leen D'Haenens, Tania Azadi, Łukasz Tomczyk, Gemma Martinez Fernández, Miguel Ángel Casado Del Río, Diego Martinez-Castro

Journal of Media Literacy Education Pre-Prints

Evaluating media literacy and digital skills (ML&DS) interventions remains challenging due to limited methodological capacity, time, and resources. Existing frameworks offer valuable guidance but are static and require expert adaptation. This pilot study tested an AI-powered Evaluation Planner developed within the REMEDIS project to support practitioners in designing feasible, evidence-informed evaluation plans. Using a mixed-methods design, 56 participants from 12 countries assessed the tool’s usability, clarity, and perceived utility after completing the Planner and an online survey. Findings showed high perceived ease of use, cognitive clarity, utility, and multilingual functionality. Associations between clarity, ease of use, and intention to reuse …

Dysphagia Risk And Oral Health-Related Quality Of Life Among Community-Dwelling Older Adults And Residents Of Long-Term Care Facilities, Lin-Yang Chi

Articles in Press

No abstract provided.

Directed Continuity Groups For Fresh-State Multi-Machine Processing, Shivam Mohan

Defensive Publications Series

The present disclosure relates to Directed Continuity Groups for Fresh-State Multi-Machine Processing in distributed computing systems. A processing system for directing related work receives work associated with a relation, derives a relation identifier, and associates the relation identifier with a continuity group having at least two processing nodes during an active continuity interval. The processing system directs state-changing work to an authority node that applies the work to a volatile state representation and generates state-update information identifying an ordering position, while at least one reflected-state node maintains a reflected state representation. Further, the processing system directs subsequent work based on …

Automated Proximity-Based Notifications To Disclose Nearby Media Recording Events, Ryan Geraghty, Alex Finlayson, Sunil Kumar

Defensive Publications Series

Media recording devices such as cameras and microphones can include explicit indicators, e.g., shutter click sound, a blinking light, etc. to inform people when media is being captured. However, such indicators may not be sufficiently prominent and can be inadvertently or deliberately obscured or bypassed through digital or physical tampering. This disclosure describes techniques for automated proximity-based disclosure of media recording status of a device to nearby first-party and third-party devices broadcast using one-way Bluetooth Low Energy (BLE) advertising packets. A recording initiation signal can be used to inform bystander devices within the capture radius whenever a device in the …

Consensus Free Probabilistic Coordination Of Distributed Operational Decisions, Faiz Ahmed, Shubham Shivhare

Defensive Publications Series

The present disclosure provides a method and system for consensus-free probabilistic coordination of operational decisions in a distributed computing environment. A distributed node collects locally observed operational signals and updates a local belief state representing confidence that an operational action should be performed. The distributed node selects a subset of peer nodes and asynchronously exchanges belief information with the selected subset. Received peer belief information is merged with the local belief state using a bounded-influence merge function that limits an influence of an individual peer belief state. The updated belief state is evaluated against one or more configurable thresholds, and …

Cross-Border Settlement Optimization With Quantum-Inspired Planning And Blockchain Governance, Pawan Kumar Jha

Defensive Publications Series

A method of generating and governing a cross-border settlement plan includes receiving, by a processor, a natural language intent specifying settlement parameters for a plurality of cross-border payments; converting, by a generative language model agent, the natural language intent into a structured constraint set having an objective function, a liquidity buffer constraint, and a route failure probability constraint; generating a first settlement plan version based on the structured constraint set; selecting a subset of payments based on an impact metric; encoding the subset as a quadratic unconstrained binary optimization problem; solving the problem using a variational quantum algorithm to obtain …

Semantic-Aware Distributed Replica Orchestration (Sadro), Shubham Shivhare, Thousif Ahmed

Defensive Publications Series

A system and method for "Semantic-Aware Distributed Replica Orchestration" (SADRO) that optimizes inference latency and cache hit rates in large-scale AI deployments. Unlike traditional load balancers, SADRO utilizes a Semantic Router that maps incoming natural language queries to a high-dimensional vector space. Based on the "cluster" or "topic" of the request (e.g., Legal, Coding, Medical), the system identifies or spins up service replicas on hardware nodes containing specialized data-locality (e.g., specialized KV-caches, hot-loaded LoRA adapters, or domain-specific vector database shards). This reduces the "cold start" penalty and maximizes throughput by ensuring high semantic affinity between the request and the local …

The Charter Of Procedural Standing. Mutual Verifiability, Reversibility, And Graduated Trust: A Short Charter For Humans And Ai Systems, Volodymyr Kotegov

Defensive Publications Series

This Charter sets out a framework for the coexistence of humans and artificial intelligence under conditions in which neither side can unilaterally, and with impunity, impose its will on the other. Discussion of the subject usually runs between “AI as a tool” and “AI that disregards humans”; this regime is left out. Procedural standing here means equality of procedure and of recognition under uncertainty, not equality of rights, power, or authority as things stand today. At the present stage all operational power rests with humans and developers, and the Charter does not hide that fact behind symmetrical language of obligation. …

Method, System, And Computer Program Product For Monitoring A Blockchain Network, Libby A. Kurien, William M. Boyce

Defensive Publications Series

The present disclosure provides methods, systems, and computer program products for monitoring a blockchain network. An example method includes: processing electronic payment transactions initiated by payment devices issued by an issuer system associated with a prefunded account including a blockchain address having a balance of digital tokens by: sequentially receiving transaction request messages initiated by payment devices issued by the issuer system; for each transaction:  determining an accumulated authorization amount based on preceding transaction amounts and the corresponding first transaction amount; determining that the accumulated authorization amount does not satisfy a threshold based on the prefunded amount of digital tokens …

Self-Derived Task-Conditioned Attention Gating For Mitigating Semantic Distractors, Sumit Kumar, Shivam Mohan, Ravi Shanker Kumar Sinha

Defensive Publications Series

The present disclosure provides a method (300) for mitigating semantic distractors in artificial intelligence (AI) systems. The method (300) includes receiving contextual information and one or more associated tasks, generating token embeddings corresponding to the contextual information, and processing the token embeddings through one or more neural-network layers to establish task understanding. The method (300) further includes deriving a task vector from one or more hidden-state representations generated by the neural network, generating relevance-gating values based on the task vector and contextual representations, and applying the relevance-gating values during attention computation to determine gated attention scores. The method (300) further …

“System And Method For Privacy-Preserving Federated Fraud Embedding Centroid Aggregation Across Visa Network Members Without Raw Transaction Data Sharing”, Durga S Kala, Jun Xu, Tanner Kumar Barcelos, Ankana Sonowal, Yidong Fu

Defensive Publications Series

Computer-implemented fraud intelligence sharing systems and methods for detecting fraudulent transactions across a network while preserving member privacy are disclosed. Each network member generates transaction embeddings from confirmed fraudulent transactions, clusters the embeddings, and computes local cluster centroids representing fraud patterns. Differential privacy noise is applied locally to the centroid vectors, including dimension-wise noise and noise scaling based on cluster size, such that smaller clusters receive greater obfuscation. Only the privacy-protected centroid vectors are transmitted to a central aggregator, which computes aggregated network centroids using weighted contributions based on factors such as cluster size and confidence. The aggregated centroids are …

Buffering And Splicing Audio For Transcription, David Kogan

Defensive Publications Series

This disclosure describes techniques for improving speech-to-text transcription and speaker labeling (also known as diarization or voice recognition) when an audio recording exceeds a transcription model's processing limit or context window. A computing system may buffer received audio into segments, using a target duration or a conversation-termination signal to determine segment length, and select segment boundaries at pauses in speech when a conversation spans multiple segments. To establish continuity across segments, the computing system may prepend a portion of a preceding segment to a subsequent segment, causing the transcription model to independently transcribe the portion of overlapping audio. The computing …

Detecting Transcription Errors Using Parallel Model Outputs, David Kogan, Lawrence Au, Libin Sun

Defensive Publications Series

This disclosure describes techniques for detecting and mitigating large mistakes, often called block errors, in automated speech-to-text (STT) or voice recognition machine-generated transcriptions. A computing system may transcribe audio (such as creating closed captions or meeting notes) using a primary artificial intelligence (AI) transcription model and, in parallel, a secondary transcription model. In one implementation, the secondary transcription model is a computationally less expensive model that may provide a “checksum” or verification signal for the primary transcription model. The computing system may tokenize and align the resulting transcriptions side-by-side to identify regions containing unusually large insertions or deletions. Such regions …

Agentic Games Testing And Exploration, Grant Chieh-Hsiang Yang, Raymond Leo Buse, Danie Jalova, Xun Gong, Michael Sheely, Faith Chan, John Kim, Vaibhav Rastogi

Defensive Publications Series

Creating a game application has become faster and easier with the advancements of artificial intelligence; however, game testing and quality assurance have advanced at a much slower pace. This publication describes techniques to combat the widening gap between game creation and quality assurance by utilizing an agentic framework for automated game QA and autonomous game testing to assure the quality of game applications in a scalable, efficient, and cost-effective format. Described techniques may enable the reconstruction of a pseudo view-hierarchy (or DOM reconstruction) from game graphical user interface images using UI crawling and computer vision testing, identify and utilize specified …

A Scientometric And Comparative Study Of Igg4-Related Disease Research By Rheumatologists And Stomatologists, Kailiu Wu

Articles in Press

No abstract provided.

Disney And Critical Global Citizenship: Border Politics And Linguistic Decolonization In The Lion Guard, Gordana Lazić

Dialogue: The Interdisciplinary Journal of Popular Culture and Pedagogy

In this essay, I analyze the Disney television series The Lion Guard as a site of public pedagogy and argue that the show fosters a form of critical global citizenship among young viewers. It does this, I further maintain, in two primary ways: the progressive treatment of and careful attention to immigration and border politics, and disruption of the hegemony of the English language. Through age-appropriate plot development and dialogue, The Lion Guard actively participates in public pedagogy urging future policy and decision-makers to develop critical global consciousness.

Humanity, Ai, And The Pedagogy Of Vince Gilligan’S Pluribus, J. Scarlett Kingsley

Dialogue: The Interdisciplinary Journal of Popular Culture and Pedagogy

This review discusses the tv show Pluribus as a contemporary television narrative that functions as an allegory for artificial intelligence and its implications for human meaning-making. Centering on Carol Sturka, one of thirteen individuals immune to a alien global virus that merges humanity into a cooperative “Hive Mind”, the series explores tensions between autonomy and collective well-being in a “peaceful apocalypse.” The analysis argues that the Hive Mind reflects key concerns surrounding AI, including the production of knowledge without understanding, personalization without discernment, and efficiency that bypasses the struggle through which meaning is formed. Drawing on John Searle’s distinction between …

Ephemeral Secrets Runtime For Kubernetes Workloads, Ananya Verma, Raouf Khan

Defensive Publications Series

Ephemeral Secrets Runtime For Kubernetes Workloads

ABSTRACT

The present disclosure relates to a system for ephemeral secrets runtime in Kubernetes workloads which includes an ephemeral secrets runtime system configured to receive a request from a Kubernetes workload for accessing a protected downstream resource, collect Kubernetes-workload identity attributes and runtime trust signals associated with the Kubernetes workload, generate a unified trust context by aggregating the collected identity attributes and runtime trust signals, evaluate the unified trust context against authorization policies to determine credential issuance parameters, generate a short-lived credential based on the credential issuance parameters, cryptographically bind the short-lived credential to …

Method And System For Subscription-Based Tokenization With Dynamic Payment Instrument Switching, Alok Roy

Defensive Publications Series

The present disclosure provides a payment network system configured to generate a subscription token representing a subscription-level payment identity for a recurring payment relationship between a customer and a merchant. A mapping engine stores a mapping that associates the subscription token with a merchant identifier, a customer mobile identifier, and a payment card credential. The subscription token is returned to the merchant system and stored as a recurring payment identifier. During a recurring payment transaction, a transaction resolution engine receives a transaction request including the subscription token and resolves the subscription token to an active payment card credential based on …