Digital Commons Network^™

Cognitive Resilience At The Edge: Hyperdimensional Computing Versus Deep Learning For Hardware-Degraded Rf Classification, Adrian B. Cisneros, Jeong Yang

Military Cyber Affairs

Autonomous Collaborative Combat Aircraft (CCA) operating in contested electromagnetic environments must classify Radio Frequency (RF) signals on edge silicon that degrades over the mission lifetime due to thermal stress, radiation, and manufacturing variation. Deep neural networks dominate RF classification on pristine hardware, but their weights are precise and interdependent, causing catastrophic accuracy collapse as the underlying chip ages. We investigate whether Hyperdimensional Computing (HDC), a brain-inspired paradigm that distributes information across thousands of dimensions, can provide a reliability floor where Deep Learning fails. Using the RadioML 2016.10A dataset filtered to five digital modulations relevant to drone command-and-control links, we trained …

Hands-On Ransomware: An Experiential Wannacry Case Study For Undergraduate Cybersecurity Education, Eli Creek Richmond, Thomas R. Devine

Military Cyber Affairs

Ransomware represents one of the most disruptive threats in the cyber landscape, yet hands-on malware analysis remains rare in undergraduate cybersecurity curricula. This paper presents the design, implementation, and evaluation of an experiential learning module centered on the WannaCry ransomware case study, deployed in a senior-level course at West Virginia University. Students performed static and dynamic analysis using industry-standard tools. Pre- and post-module assessments demonstrated measurable gains in self-reported competency across seven technical dimensions. The module's competencies align directly with DoD Cyber Workforce Framework Work Role 212, Cyber Defense Forensics Analyst, supporting education-to-workforce pipeline development.

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.

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 …

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.

The Brain, The Block, The Bummed Writer, Karina Silva

Undercurrents: A Journal of Undergraduate Student Composition

Karina is a psychology major with a biology minor from Winthrop, MA. Karina says that writer’s block has “always been an obstacle for me, especially whenever I have to write papers for classes.” She notes that this paper was one of the first that she felt passionate about writing, and she feels that “researching the neurology behind writer’s block” enabled her to “further appreciate the wonders of the brain” and “develop an interest in research surrounding neuroscience and psychology.” Karina is a Brazilian-American who speaks Portuguese as well as English. Her hobbies include drawing, and she notes that art helps …

Fake News’ Negation Of A Useful Education, Vance Naftal

Undercurrents: A Journal of Undergraduate Student Composition

Vance is an international relations Major from Baltimore, MD. Vance chose to write about the negative effects that misleading/false news stories can have on an individual, especially when in college, because he “sees society moving farther and farther away from truth and leaning more into sentiments based on emotions — which is directly at odds with the point of a higher education.” Vance started college at 16 years old. At 17, he decided to take a gap year (which became a gap of 4 years) to enter the workforce. At 21, he found himself yearning to be a part of …

Your Teachers Are Bullshitting You, Kylie Medeiros

Undercurrents: A Journal of Undergraduate Student Composition

Kylie is a biology major from Fairhaven, MA. Because she was specifically told for this assignment that students “couldn’t bullshit this essay,” she was reminded of all the times throughout her academic career when other teachers said things of a similar nature. “Being short on time, and desperately in need of a research topic,” she found that it would be “incredibly ironic to bullshit my paper in the form of a research on the topic of BS itself.” While writing her essay Kylie found it interesting how much creative freedom she was given to research and write about something she …

Moral Punishment, Anna Krasnoslobodtseva

Undercurrents: A Journal of Undergraduate Student Composition

Anna is a biochemistry major from Milton, MA. She decided to write about the prison system and punishment because of conversations about morality during her Composition II class, and because she believes “the prison system in the United States is often discriminatory and does not work toward the rehabilitation of people like it should.” She felt that writing this was “more free than a traditional structured high school essay” and that it “involved a lot of learning, by means of stepping outside of what I am comfortable with writing and exploring new research methods, going to the library, and taking …

Textism And The Shift In English Writing, Alex Der-Kazaryan

Undercurrents: A Journal of Undergraduate Student Composition

Alex is a management major with a concentration in accounting from Belmont, MA. While writing this essay, Alex wanted to investigate “how our writing has evolved over the last thirty years or so.” Noticing a “retraction of socialization from other people,” since we introduced ourselves to new technologies, Alex focused this essay on the common complaint that “texting has only done damage to formal writing.” Alex has also come to enjoy writing as a way of self-expression and writes that it “can now be used in a way that benefits me.” Alex is also a huge history buff and has …

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 …

Oswald Spengler, A Critical Estimate, Henry Stuart

Hannah Arendt Marginalia - All

New York : Scribner, 1952.

Call #: B3332.S44 H8

Contains marginalia, endpaper notes, marginal lining and underlining. PDF information: 24 pages - 7.9 MB

Held-Through Candidacy: Excluding Sustained-Note Interiors From Grid-Guided Onset Detection By Testing Whether The Previous Note Ever Stopped, Shane Wirkes

Defensive Publications Series

Grid-guided onset detection scores a musician’s timing by asking, at every position of a metronome grid, whether a note began there. On sustained-tone instruments (brass, single-reed, flute) this fails in one specific way: a note held across several grid positions keeps producing spectral change through vibrato, breath and pitch wobble, so its interior is reported as a run of new notes. Every test that reads the sound at the position (spectral flux, prominence, level, spectral sparsity, group delay, linear-prediction residual, pitch) is either inert on this population or removes only a minority of it at a cost in real notes …

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 …

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. …

Verifiable Trust: A Practice Guide To Graduated Oversight Of Advanced Ai Systems, Volodymyr Kotegov

Defensive Publications Series

This guide turns the operational core of The Human–AI Charter (Discussion Draft v1.4) into a set of protocols that researchers, evaluators, and engineers can adopt without adopting the Charter's broader positions on moral status, representation, or long-term governance. It contains five protocols and four supporting practices for keeping the oversight of advanced AI systems verifiable: measuring how well verification methods actually detect deviations (VT-1); controlling changes to the parameters that oversight depends on (VT-2); keeping verification data out of training (VT-4); financing and assigning independent evaluators so that findings do not depend on the evaluated party (VT-3); and tying the …

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 …

Referral-Bound Purchase Claims: Binding An Operator-Issued Referral Id To An Anonymous On-Chain Purchase Commitment For Verifiable Word-Of-Mouth, Takuya Ogura

Defensive Publications Series

A method for making word-of-mouth posts verifiable without revealing buyer identity. A purchase is recorded on a blockchain as a hiding commitment that does not identify the buyer. When the buyer chooses to post about the purchase on social media, a separate per-purchase binding record is written that contains the buyer's public account handle and, in plaintext, an operator-issued referral ID. The referral ID is generated from random bytes and exists only inside the buyer's personal connector (token) URL, which is issued automatically upon payment confirmation. A third party can therefore compare the referral URL in a post against the …

Telemetry- And Intent-Encoded Routed Expert Fabric, Dennis Lanov, Charles Fleming

Defensive Publications Series

A system is proposed herein for distributing artificial intelligence (AI) inference across endpoint, edge, and cloud tiers. The system routes each semantic portion of a request only to an execution tier permitted by enterprise policy. A local model processes the request first, and intent, local-model confidence, and live network and compute telemetry determine whether selected portions remain local or are promoted with compressed intermediate state. Promoted results are verified before acceptance, and observed outcomes are used to improve future routing and expert placement.

Multi-Tenant Traffic Disambiguation With Tenant-Indexed Ipv6 Addresses, Rashmi Garg, Jerome Tollet, Benoit Ganne, Anil Kumar Kainikara, Arthur De Kerhor

Defensive Publications Series

Proposed herein is a stateless mechanism for disambiguating overlapping private Internet Protocol version 4 (IPv4) traffic from multiple tenants by synthesizing Internet Protocol version 6 (IPv6) addresses that encode both tenant or virtual routing and forwarding (VRF) identity and the original IPv4 source address. Shared downstream gateways, including virtual private network (VPN), zero trust network access (ZTNA), Internet Protocol Security (IPsec), and cloud gateways, can receive native IPv6 traffic with globally unique source addresses without modification to understand tenants, VRFs, or overlay networks. Because the mapping is algorithmically reversible from the IPv6 address itself, return traffic can be translated back …

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 …

Anonymous Purchase Commitment With Optional Public Account Binding: Verifiable First-Hand Purchase Claims On A Public Ledger, Takuya Ogura

Defensive Publications Series

A method for letting readers, and AI agents acting for readers, distinguish real first-hand purchase accounts from fabricated ones without revealing buyer identity. Each paid purchase is recorded on a blockchain as a commitment computed as plain SHA-256(nonce || buyerId), so the buyer can open and verify their own record with a single hash on any machine, without the chain's SDK or the seller's cooperation; the identity was measured on chain to match an externally computed digest byte for byte. Separately, a buyer who chooses to speak publicly can attach a plaintext account handle to one purchase as a second, …

A Graph-Based Infrastructure Change Modeling System With Dependency-Aware Risk Propagation For Pre-Deployment Failure Prediction, Utkarsh Bhardwaj, Shivank Awasthi

Defensive Publications Series

Modern Continuous Integration and Continuous Deployment (CI/CD) systems rely predominantly on static analysis and deterministic rules, rendering them incapable of forecasting emergent risks arising from complex infrastructure interactions. This reactive approach frequently fails to prevent production incidents caused by non-obvious dependencies between code, configuration, and infrastructure. This paper proposes a novel Artificial Intelligence for IT Operations (AIOps) system that models cloud infrastructure as a topological dependency graph. We introduce the concept of a "Delta Graph" ($\Delta G$), which explicitly represents the structural and attribute changes between a currently deployed state ($t_0$) and a proposed state ($t_1$). By utilizing a Graph …

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 …

Indian Standard For Safe Handling Of Biotherapeutic Products Used In Homoeopathy: Guidelines, Kumar Vivekanand, Indra Gaurav Saxena, Divya Taneja, Shailendra K. Saxena, Shrishti Dixit, Raj Kumar Manchanda

Indian Journal of Research in Homoeopathy

Biotherapeutic products used in Homoeopathy are derived from biological sources of human, animal, microbial and other origins and include pathological and non-pathological preparations such as nosodes and sarcodes. Owing to the biological nature of these materials, their safe handling, preparation, storage, testing and documentation require systematic controls to protect personnel, the public and the environment. The Indian Standard `IS 19901:2026, Safe Handling of Biotherapeutic Products Used in Homoeopathy — Guidelines', provides a comprehensive framework for risk assessment, biosafety classification, containment, determination of first safe dilution (FSD), safety and efficacy evaluation, quality assurance, formulation, dispensing and documentation. The standard also establishes …