Of Brainwave Authentication and Other Demons
A coherent reconstruction of the second PhD presentation by Violeta Tulceanu: brainwave authentication, cognitive-memory-emotion passwords, dynamic brainprints, brain signatures, neuro-ontology, secure BCI systems, language-of-mind decoding, implant / brainware security, and consensus games. This page treats the deck as Aletheon cargo: raw internal source material, to be access-layered later.
Executive squeeze: what this deck was really doing
This presentation is a much more mature and more dangerous successor to the first brain biometrics deck. It turns “EEG authentication” into a full cognitive-security architecture: identity, continued presence, capacity, mental-state proof, private keys, emotional evolution, coercion detection, thought-reconstruction risk, implant security, group cohesion manipulation, and the governance problem of an emerging Internet of Minds.
Central thesis: a brain credential is not deployable merely because a classifier distinguishes users. It must be unique, stable, tamper-resistant, ethically bounded, privacy-preserving, legally governed, secure against adversarial reconstruction, and capable of proving both identity and cognitive/emotional capacity where authorization requires responsibility.
NeuroID spine
Mindprints authenticate the way a mind reasons and feels, not merely the surface EEG signal.
Pages 1–11, 27–32Security spine
The deck treats brainware as an insecure ecosystem: devices, apps, cloud, identity providers, suppliers, local files, credentials, and biometric data all become attack surfaces.
Pages 33–39, 50–58Cognitive-security spine
The later sections move into thought reconstruction, advanced investigation, emotional induction, group cohesion, influence, and mind-to-mind infrastructure.
Pages 45–621. The world context: Internet of Minds
The deck opens from macro-context: neurotechnologies are creating a connected world of minds, bodies, and brainware. That world requires authentication, authorization, signing, non-repudiation, prediction, alerting, privacy, human rights, and governance.
Forces named
- Emerging Internet of Minds.
- Connected neurotechnologies: minds, bodies, brainware.
- Neurorights and neurolegislation.
- Neurowarfare and brain signals as legal evidence.
- Mental health and addiction prevention.
- Bullying, psychiatric abuse, remote work/school after Covid.
- Aging population and vulnerable users.
User classes
- Online exams: identity, continued presence, brain signature.
- Notarial deeds for vulnerable persons: identity, emotional/cognitive capacity, proofs.
- Assisted suicide: identity and capacity proof.
- Proof of life for pensioners and assisted-living residents.
- Paralyzed / locked-in users: banking, government apps, emergency services, smart-hospital rooms, wheelchairs/cars, SSO.
- Judicial evidence: non-repudiation and indicators of coercion, torture, capacity, emotional state, substance intake.
- Military, high-stress professions, state security, battlefield readiness, rebellion / unrest risk.
Current Aletheon translation: this is not “brainwave login.” It is a rights-sensitive identity infrastructure for a future where minds are networked, measured, manipulated, and used as evidence.
2. Proposed solution: brain access, brain authorization, brain signatures
The solution layer proposes using the brain to access systems in a provable, reliable, usable way: identity, continued presence, authorization by capacity, digital signing, and the ability to identify or repudiate a piece of brain signal as one’s own.
Identity + presence
Prove who you are and that you remain present. This targets exams, remote access, vulnerable-person transactions, and brain-driven interfaces.
Predictive authorization
Authorize action by proving ability to act: emotional state, emotional evolution, cognitive evolution, mental-condition pre-diagnosis, substance intake, trauma, torture, radicalization effects.
Brain digital signature
A signature can carry proof of mental and emotional state: cognitive decline, coercion, distress, instability, substance intake, or abuse indicators.
Non-negotiable constraint in the deck: obtain necessary information without aiding human-rights violations: only read what the system says it reads, protect passwords, prevent reuse for unethical research, state profiling, employer or insurance abuse.
3. Provable, secure, ethical credentials
The deck sharply rejects weak state-of-the-art claims. “This signal differs between a few people in a small homogeneous population” is not authentication. At most, it suggests the possibility of a credential. A deployable brain credential needs proof.
Credential proof requirements
- Prove uniqueness compared to others and compared to the same user’s own variants.
- Prove stability over time, diverse populations, large studies, clinical studies.
- Test neurophysiological disorders, paralysis, AVC/stroke, mental conditions, substance intake, fatigue, stress, discomfort.
- Take into account cognition, time, learning, forgetting, priorities, frustration.
- Decide which signal: movement, real/imaginary action, emotion, abstraction, memory, surprise, reasoning.
Adversarial / mind-reading questions
- Will cognitive-memory-emotion passwords leak semantic content?
- Will a brain password allow unwanted mind-reading?
- Can someone forge a brainprint by showing a close-enough image of what they think the user should think?
- Can a signal be identified as valid content from a mind without knowing the actual password?
- Can valid content be distinguished from gibberish or baseline?
Credential is not enough: even a unique, stable, large-password-space, tamper-resilient credential is still not a deployable system. Deployment requires liability, ethics, legislation, trust, hardware/software security, usability, high-performance algorithms, secure architecture, and anti-profiling protections.
4. Empirical status: experiments, scale, and evidence base
The deck reports a large ongoing empirical program: pilot studies, a main autobiographical-memory emotion experiment, adjacent semantic/cognitive experiments, adversarial profiles, clinical testing, hardware/security testing, and a large searchable neuro-ontology.
Pilot studies
- Autobiographical memory with emotion: two populations.
- Attention.
- Movement: real and imagined, randomized, deception.
- Task recognition / “aha” moments.
- Abstraction.
Main + adjacent experiments
- Main experiment: 23 emotions, guided memory, synonyms, free memory, images through another’s mind, randomized without emotion.
- Adjacent: emotionally charged personal picture + associated words, semantic ambiguity, syntactic ambiguity, syllogisms, programming tasks, image understanding.
- Geographically separated groups tested ten years apart.
- Security analysis and attacks of brainware.
- Clinical testing ongoing.
Experiment/task inventory from the visual task table
| Task type | Paradigm / use |
|---|---|
| Visual motor task | Imagined short movements to the left, right, up, and down; direction shown with arrows and played by audio. |
| Facial motor task | Facial expressions of different emotions. |
| Concept-emotion | Think of emotions using associated personal memories. |
| Image understanding / reasoning | Look at images/videos and think of descriptions; evaluate logical continuation. |
| Syntactic / semantic ambiguity | Listen to ambiguous sentences with logical/illogical continuation. |
| Syllogisms | Truth evaluation of logical facts, including values/political content. |
| Recognizing objects | Look at objects/persons known/unknown and identify them. |
| Emotional recognition | Listen to normal and impossible sentences. |
| Reasoning validity | Classify statements as true or false. |
| Language as weapon | Listen to propaganda and polarizing messages; check which messages the subject believes are true. |
| Brain hierarchies / abstraction | Listen to concepts with related words, synonyms, associated properties. |
| Programming / numeric reasoning | Programming-like tasks and numeric reasoning tasks. |
| Subliminal messages / memory / frustration / force | Hidden subliminal marketing, memory retrieval across time, frustration level, drone/force command task. |
5. Pilot tests: autobiographical memory and adjacent experiments
The pilot layer uses autobiographical memories and emotions as the core password/credential material. The visual pages show pipeline blocks: baselines, emotions, memory triggers, preprocessing, feature extraction, fuzzy c-means, profile construction, channel selection, concept clustering, authentication classification, and authorization logic.
Autobiographical memory pilot
- Two baselines: closed eyes and open eyes.
- Eleven emotions in the pilot: contentment, love, affection, fear, disgust, indifference, hope, pride, worry, sadness, pleasure.
- One memory for each emotion, with trigger and zooms supplied by the subject.
- Processing includes raw signal, profile extraction, matching, symbolic representation, channel selection, clustering, and authentication/authorization outputs.
- Conclusion displayed: profiles are distinguishable.
Adjacent experiment findings
- Movement: visual/audio cue; performed, imagined, pseudo-random order, mismatch cue.
- Abstraction: recognition of increasingly abstract objects.
- Recognition: task-related and unrelated objects/persons.
- Attention: instructional video with random sounds to induce distraction.
- Symbolic representation and pattern matching over action/electrode patterns.
- Conclusion: authentication based on symbolic representation is possible; no single profile works best in every scenario; recognition is not suited; movement and emotion have similar global performance; movement ROC 0.855, EER 0.227.
6. Main experiment and searchable neuro-ontology
The main experiment expands emotion-based identity into a structured neuro-ontology. Emotion trigger lists, synonyms, images, memory, randomization, and semantic links are stored as searchable material with raw and processed EEG data.
Main experiment design
- Emotion trigger lists with words and synonyms.
- Examples shown: contempt and jealousy with emotional neighborhoods.
- Images corresponding to selected words.
- Randomization of all lists, one by one.
- Pure emotions, words alone, word + emotion + semantic trail + next word.
Neuro-ontology contents
- Over 200,000 concept instances.
- Attention.
- Movement: real, imagined, randomized, deception.
- Task understanding and concept recognition.
- Levels of abstraction.
- Autobiographical memories across 23 emotions.
- Guided memory, synonyms, free memory, images through another’s mind, randomized without emotion.
- Raw full signal, filtered signal, symbolic representation, annotated cut concepts, semantic connections, and words.
Aletheon relevance: this is already a cognitive-semantic database, not just an EEG dataset. It binds neural signals to emotions, memories, concepts, synonyms, semantic paths, abstraction, deception, ambiguity, reasoning, and attention.
7. Signal processing and hierarchical fuzzy symbolic representation
The deck specifies a signal-processing pipeline, then transforms EEG into hierarchical symbolic sequences. This is the bridge from physiology to “brain language.”
Preprocessing pipeline
- EEGLAB offline preprocessing.
- Re-referencing with averaged left/right mastoids.
- Fourth-order Butterworth filter, 1–50 Hz, forward/backward to avoid phase shift.
- Epoch segmentation with a pre-stimulus baseline.
- Exclude first second after sound stimulus to reduce onset responses.
- ICA with ADJUST algorithm and visual inspection for artifacts: blinks, heartbeats, EOG.
- Downsample to 100 Hz.
- Band-pass filters: 2–8, 8–15, 15–30 Hz.
Symbolic representation
- PSD feature extraction.
- Fuzzy c-means classification.
- Alphabet over centroid labels.
- Symbolic sequence alignment.
- Profile = five aligned hierarchical symbolic representations.
- Concept on a channel becomes a string-like sequence, e.g. aabbacdefa.
- Alignment uses increasing-size windows for “syllables” and regex search.
8. Proposed analysis: uniqueness, semantics, reconstruction, psychology
The proposed analysis is one of the densest parts of the deck. It moves from authentication metrics into semantic path analysis, memory reconstruction, psychological profiling, emotional ranking, abstraction effects, population-level trends, and group mapping.
Uniqueness and stability
- Create profiles by aligning sequences: emotion + following signal, or randomized word.
- Align candidate sequence against profile using held-out signal, spare candidate signals, adversarial data, and recombinations of correct/adversarial signal pieces.
- Each subject has list 1 profile, list 2 profile, synonym profiles, images, randomized profiles, and trigger profiles.
- Evaluate intrinsic uniqueness and stability: words among themselves, list vs synonym list, emotional words vs randomized non-emotion correspondents, images, pure emotions.
- Merge signal between emotional profile and corresponding random concept and compare it to emotional concept to check reconstructability.
- In trigger experiment: find random and emotional words inside free-flowing memory segments to prove memory-task stability.
Semantic path and “syllables”
- Define semantic paths between concepts, triggers, words, and synonyms.
- Compare semantic similarity between initial words and alleged synonyms.
- Evaluate reliability of semantic path versus similarity score between profiles.
- Find stable “syllables” and articulation points on semantic paths.
- Search for those syllables inside trigger/free-memory segments.
- Test whether a memory is remembered the same way every time and how well a single word can be detected when drowned in a memory.
Psychological and population analysis
- Perform psychological text analysis on words, memories, associations for pre-clinical diagnosis.
- Extract dominant elements and themes in subjects’ psyches.
- Evaluate generic vs personal content, masking tendency, honesty, inner conflict, aggression.
- Corroborate personal history to data where available.
- Rank most distinguishable emotions and attach rankings to profiles.
- Separate emotion patterns from random content.
- Analyze abstraction levels in concept representation.
- Extract hierarchies and concept clusters from the full neuro-ontology.
- Label common symbolic “syllables” as semantic dimensions and add them back into the ontology if valid.
- Evaluate population trends, preoccupations, and group-mapping accuracy.
9. The role of emotion
Emotion is not decorative. It is the amplifier, differentiator, privacy risk, coercion marker, and identity stabilizer. The deck explicitly asks why authentication should involve emotion and memory, then gives three roles.
Role 1: access control
Immediate classification of emotional state by comparing the current emotional pattern to the registered profile.
Role 2: longitudinal evolution
Across authentications, check emotional-pattern change over time, map to clinical conditions, and evaluate shifts in dominant emotions and semantic content.
Role 3: protection / evidence
Protect users from actions and confessions under duress or mental illness; create proof of abuse and decline of mental wellbeing in controversial situations; also monitor rebellion risk.
Risk caveat from the deck: workplace/school “wellbeing” apps can become illegal consultation and modern eugenics. Brain-activity knowledge can become invasive, forged, manipulated, and abused unless emotion detection is reliable and outputs cannot be forged.
10. Brain signatures
The brain signature section connects accessibility, legal consent, cognitive capacity, vulnerability, and emotional-state proof. If brainware lets someone bank, take exams, or sign documents, then a brain signature follows naturally.
Simple accessibility signature
For banking, exams, and basic access, the key is identifying oneself with an EEG signature that cannot be forged from other mental content from the same person.
Capacity-sensitive signature
For vulnerable persons or investigations, the signature should include emotional state and perhaps indicators of emotional and mental evolution, backed by clinical repositories of mental-condition signatures.
Initial clinical target named: Alzheimer’s disease, because of memory degeneracy stages and increased emotional instability.
11. System description: profile creation, authentication, authorization, private key
The system diagram gives the core pipeline: recording password space, autobiographical memories, symbolic brainprints, emotional/cognitive/psychological profiles, feature extraction, preprocessing, fuzzy classification, threshold matching, authorization, predictive trend validation, private-key derivation, and dynamic morphing.
Dynamic morphing logic
Successful candidates accumulate. If there is an overall divergent trend across candidates, emotional trends, semantic evolution, cognitive evolution, or psychometrics, the system can morph the brainprint. If differences become too high, it requires registration of a new brainprint and updates the private key. Future work includes patterns for mental conditions, pre-clinical diagnosis alerts, and predictive analysis.
12. Secure brainwave authentication: systems, suppliers, threats
The security section insists that brainwave authentication is a full systems problem: identity providers, brainware manufacturers, apps, servers, cloud, local data, third-party suppliers, standards, liability, informed consent, human rights, secure computation, profiling risk, and legislation.
System architecture issues
- Standardization and liability.
- Transfer of trust between components.
- Regulation of suppliers.
- Third-party suppliers and consortium members.
- Informed consent management and accessibility.
- Provability, privacy, secure computing, profiling risk.
- SSO / OpenID / identity-provider integration.
Threat categories shown
- Credential theft, replay, recomposition, fake data generation.
- Real credentials used on a single device, local/cloud storage compromise, script/marker exfiltration.
- False data generation from previous sessions or AI-generated data.
- Threshold probing and similar-data search in other apps.
- Identity-provider leakage or malicious updates.
- Authentication module leakage, privilege escalation, config-file leaks.
Emotiv weakness inventory
The deck identifies ecosystem-level weaknesses: password authentication to headset + ecosystem, locally stored configuration files, client ID + client secret, locally stored data, cloud data, signal quality, and headset configuration. The underlying issue: if credentials are stored or managed poorly, the attacker may access old EEG data, stored app data, or connection credentials and reuse them to create fake brainwaves or compromise privacy.
Page 38Security / rights line: proving a credential exists does not mean there is a secure authentication system or a right to deploy it. The design must answer: Are you reading my mind? Is your system secure? Who are you? What are you doing with my data? What law governs this? How do you prevent illegal consultations, data leaks, profiling, state intrusion, manipulation, authoritarian abuse, and distortion?
13. Towards practice: scale, users, market, certification
The deck’s deployment logic is explicit: finish proof on larger data, complete credential proof, improve algorithmic performance/security, test mental conditions and substance intake, pilot usability, coordinate with legislation/manufacturers/identity providers/GDPR, and require certification.
Scale path
- Complete analysis of larger experiments.
- Prove credential reliability.
- Move to performance/security of algorithms.
- Test mental conditions and substance intake.
- Pilot solution performance and usability.
Potential users
- Governments and public institutions.
- Universities.
- Hardware manufacturers.
- Agencies.
- NGOs for political science.
- Police and legal system.
Market translation
- Fast-growing market.
- National or EU-level implementation.
- Packaged with hardware.
- Reconfigured for different clients.
- Provable security, legislation alignment, liability and manufacturer certification.
14. Language of the mind: decrypting unknown thoughts
This section is the raw bridge from NeuroID to “mind language.” The deck asks: no concept arrives alone; it brings semantic friends. What can be inferred from a thought without consent? The repository contains memories remembered in two ways, emotion patterns, word patterns, word+emotion+semantic trail+next-word patterns, ambiguity, syllogisms, programming tasks, and image understanding.
Reconstruction method sketched
- Detect whether an unknown thought involves emotion and strip emotion first.
- Search for articulation points: “if,” “for,” “while,” syllogism-like structures, inference patterns, “aha” moments.
- Search for “syllables” from the neuro-ontology: semantic dimensions.
- Generate a first plausible reconstruction.
- If plausible, match syllables down through the hierarchy of concepts and relations.
- Use links between candidate concepts in a more advanced ontology.
Supporting experiments
- Semantic ambiguity: ambiguous sentence with logical / illogical continuation.
- Syntactic ambiguity: ambiguous sentence with logical / illogical continuation.
- Ten syllogisms, five including subject-selected beliefs.
- Programming task: game-like addition by 1, if, for, while, else.
- Image understanding: subject describes images through three rephrasings including a verb.
Internal meaning: this is the sharpest privacy and IP edge. The deck recognizes that cognitive-semantic authentication can become semantic inference. That is precisely why NeuroID needs rights, access controls, proof boundaries, consent logic, and anti-profiling architecture.
15. Advanced investigation
The advanced-investigation section names “aha” moments, abstraction, attention, deception, and information extraction under uncertainty. It explicitly deals with cases where the target instance is unknown, sketched, deceptive, or possibly resisted.
Technical ingredients
- “Aha” moments in task-recognition experiments.
- Levels of abstraction experiment.
- Attention experiment.
- Emotion detection.
- Coercion detection.
- Brain signature and authentication.
Raw scenario
The deck considers investigation where information is needed despite possible deception, incomplete knowledge of the target, or only a sketch-like description. Its own phrasing emphasizes the need to make such investigation reliable and ethical.
Page 4916. Brainware security: implant security and BCI security
The implant-security section shifts from EEG authentication to active brainware security. It uses DBS / Medtronic-style neurostimulator systems as an object of analysis and threat modelling: clinician programmer, patient programmer, communicator devices, Bluetooth links, proprietary protocols, short/long-range communication, jamming/spoofing classes, and lab instrumentation.
Raw research intent as written in the deck: analyze whether a DBS / neurostimulator communication ecosystem could be disrupted or manipulated, including parameter tampering and communication attacks. This belongs in an internal defensive brainware-security archive, not public marketing copy.
Objects and systems named
- Doctor / clinician programmer.
- Patient programmer mobile app.
- Communicator device.
- Percept PC / neurostimulator / implant.
- Communication link diagrams and system build diagrams.
- Older and newer generations of neurostimulators.
- DFD-style programmer-neurostimulator communication.
Threat / lab-analysis categories
- Programmer access and password/reset weaknesses.
- Bluetooth and proprietary-protocol vulnerability classes.
- Eavesdropping, denial of service, man-in-the-middle, message modification classes.
- Short-range and long-range communication-channel analysis.
- USRP / logic analyzer / probes mentioned as lab tools for communication observation and disruption studies.
- Need to analyze encryption, physical access assumptions, and device-resilience boundaries.
17. Consensus games: brain, communication, and group cohesion
The final major research branch moves from detecting emotions to inducing them in a controlled collaborative-game environment. This is the raw group-cognition / political-psychology / influence-operations branch.
Proposed experiment
- Use existing emotional profiles and semantic triggers.
- Move from detecting emotion to inducing it.
- Inject charged messages in a collaborative game environment.
- Alter group dynamic and decision processes.
- Control trust in leadership.
- Reinforce or downgrade a leader.
- Trigger dissension and unrest.
- Simulate micro-republics of maximum five participants, excluding experimenters.
Protocol elements
- Each participant connected to BCI.
- Assigned experimenter controls and labels reactions.
- Game starts in a marked peaceful state.
- Participants collaborate toward a task; deception is used.
- Messages are injected; emotion, message, visible reaction, comment, and trust changes are logged.
- Iterative sessions include wind-down observation.
- False leaders and semantic narrative management are introduced.
Aletheon relevance: this is the ancestor of group-mind security, propaganda-resilience modelling, social-consensus dynamics, and adversarial semantic-influence detection. It is raw, dual-use, and extremely valuable as internal theory.
18. Lesser demons
The closing slide lists the surrounding demonology: brain-data security, neuroabuse, surveillance, magnetic-field attacks, philosophy of mind, blended consciousness, transplant of consciousness, mind-to-mind communication, and eternal life.
Security demons
Brain data management, brain data security, implant and BCI security, neuroabuse, surveillance, profiling, abuse of cognitive data.
Attack demons
Magnetic-field attack concepts, brain rewriting concerns, brainware compromise, coercive or unauthorized cognitive access.
Philosophy demons
Language of the mind, blended consciousness, transplant of consciousness, mind-to-mind communication, eternal life.
19. Aletheon extraction inventory
The deck can be mined into paper tracks, patent fragments, investor narratives, website/internal technical pages, and reviewer packets. This table is the cargo manifest.
| Extracted idea | Paper track | Patent / technical fragment | Investor / website / internal asset |
|---|---|---|---|
| Mindprints: reasoning + feeling authentication | Cognitive-semantic biometric identity | Authentication from semantic-emotional response grammar | NeuroID core explainer |
| Continued presence and aliveness | Brainwave presence assurance for online systems | BCI-based liveness and session-continuity verification | Online exams, vulnerable persons, proof-of-life |
| Predictive authorization | Capacity-sensitive access control | Authorization conditioned on emotional/cognitive trend and mental-state proof | Aviation, military, finance, legal consent |
| Brain signatures | Brainwave digital signatures and non-repudiation | EEG-memory-emotion signature with capacity/coercion markers | Legal, notarial, accessibility, assisted-living |
| 200k concept-instance neuro-ontology | Neurosemantic ontology construction from EEG and memory data | Searchable brain-signal repository with semantic links and symbolic sequences | Scientific moat / Aletheon data asset |
| Hierarchical fuzzy symbolic representation | Symbolic language extraction from EEG | PSD → fuzzy c-means → centroid alphabet → sequence alignment pipeline | Technical diagram / patent figure |
| Semantic path / syllable analysis | Formal language of mind and memory reconstruction | Stable semantic-dimension extraction from neural symbolic strings | Bridge to Logos grammar/selfhood theory |
| Adversarial profiles and forgery testing | Adversarial robustness of brain credentials | Testing recomposed and adversarial EEG profile candidates | Security differentiation |
| Emotion as credential and risk marker | Emotion-based authentication and cognitive-state monitoring | Longitudinal emotional-profile drift detection | Responsible access control, abuse evidence, wellness-risk critique |
| Secure brainwave authentication architecture | Systems security for BCI authentication | Identity-provider/SSO/brainware trust chain and STRIDE model | Certification / compliance / EU-level deployment narrative |
| Emotiv / ecosystem weaknesses | Consumer brainware security analysis | Credential, config, local/cloud data, client-secret weakness taxonomy | Security-audit offering |
| Language-of-mind unknown-thought analysis | Privacy limits of neurosemantic inference | Emotion stripping, articulation-point detection, ontology syllable matching | Internal red-team / rights architecture |
| Implant / DBS security | Brainware and neurostimulator security | RF/communication threat model and safe defensive testbed | Brainware-security division material |
| Consensus games | BCI-mediated group cohesion and influence dynamics | Logged affective response to message injections in collaborative microgroups | Cognitive security / propaganda-resilience / internal theory |
20. Derived paper list
NeuroID / authentication papers
- NeuroID: Cognitive-Memory-Emotion Passwords for Brainwave Authentication.
- Dynamic Brainprints for Predictive Authorization and Cognitive Capacity Proof.
- Brain Signatures: Non-Repudiation, Consent, and Mental-State Proof in BCI-Mediated Identity.
- Adversarial Robustness and Forgery Resistance in Emotion-Based Brain Credentials.
Language / security / society papers
- A Searchable Neuro-Ontology for Mapping Concepts, Emotions, Memory, and EEG Symbolic Sequences.
- Language of the Mind: Semantic Syllables, Articulation Points, and Privacy Limits of Neural Inference.
- Brainware Security: Threat Modelling BCI Ecosystems and Implant Communication.
- Consensus Games: BCI, Emotional Induction, and Group-Cohesion Dynamics.
21. One-line claim map
NeuroID claim: a human identity credential can be modelled as a dynamic, privacy-sensitive, adversarially tested, cognitive-memory-emotion signature that authenticates not only a body but a mind’s stable way of feeling, reasoning, remembering, and authorizing action over time.
Security claim: once brains are networked through consumer, clinical, or implantable brainware, cognitive autonomy becomes an information-security problem: credentials, keys, profiles, emotional states, semantic content, group cohesion, and medical-device parameters all become protected assets.