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- Introduction
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- We live in a dangerous world, so we need security. The threats we face are real: hostile nations seeking weapons of mass destruction, terrorists who would hurt us, spies stealing our technology, blackmailers encrypting our data for ransom, and scammers using the Internet to rob our grandmothers, to mention only a few of the threats we face.
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- What has made our nation a shining light in the face of such threats has a lot to do with the group intelligence effect. To give an example, when people come to a 4H fair and buy a contest ticket to guess the weight of a pig, it is usually not the agricultural experts who come the closest. Nor is it typically a lucky contestant. Rather, the most accurate value is consistently gotten by averaging all the individual guesses. This is group intelligence.
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- In the US, anyone can express an opinion, and they typically do. Any citizen who is qualified can invest in projects, and even if unqualified, can join in with crowd-funding. We have an active marketplace of ideas, and this has made us strong.
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- As a contrasting example, consider the Soviet Union, where all project investment went through centralized committees, and company management was merely an extension of the state. Or consider East Germany. Authoritarian systems suppress group intelligence, and thus fundamentally fail to benefit from it.
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- As a researcher, I commonly download source code for the Linux operating system and modify it to see if ideas for improving it actually work. I currently have a "subu" security algorithm up on GitHub. I am one of tens of thousands of independent actors adding intelligence to software development. What an irony it is that Android, which is based on Linux, utilizes a closed root system. Yet, can a person even imagine the modern smartphone market without the foundation of Android? Open architectures are the engine of our digital economy.
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- Yet, as explained in this white paper, our current approach to cybersecurity is threatening to dismantle this open ecosystem. We appear to be heading down a path toward a novel type of authoritarianism. In this new system, instead of the state asserting control directly over individuals, they are preparing to assert control over their computers. Instead of suppressing speech directly, the architecture is being shifted to limit who can communicate with whom over the Internet, and to dictate what the nature and utility of that information can be.
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- In my opinion, the dangers we face indeed possess a high probability of spelling the end of the anonymous participant on the Internet. However, this does not have to lead to computer authoritarianism; we can secure our networks while preserving group intelligence.
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- This paper does not provide the complete Reasoning Technology proposal, as the intellectual property is still being worked on, and the deep technical details are better suited for a different venue. Rather, this paper explains the structural trap the industry is currently falling into, and specifically analyzes recent Congressional bills to demonstrate how current legislative efforts are inadvertently accelerating this descent.
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- How experts think about safety
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- Linear risk
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- In this model, each term is a product of the cost and the probability that the cost will be incurred. Then all the terms are summed to get a total expected cost.
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- T = Σ (ti × ci)
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- Here ti is the probability of the event and ci is the cost. As an example, consider that there is a 0.2 probability that a person forgot their password, and it will cost 900 seconds to recover it. (Here 0.2 is 20%, 1 out of 5 times). There is a 0.1 probability that a person made a typo in the user name which results in 45 seconds of time to figure out. There is a 0.3 probability that a person will type the password wrong, costing 15 seconds. There is a 0.05 probability that a person will get the password wrong 3 times and be locked out for a day, and thus a 0.65 chance that they type it correctly, taking 5 seconds to log in.
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- T = 0.2 × 15 + 0.1 × 45 + 0.3 × 15 + 0.05 × 86400 + 0.65 × 3
- T = 4334 seconds
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- Statisticians call this the expected time it will take to log in, though this specific time is not among the actual individual scenarios. After many times of logging in, the average time will tend towards this value. The reason this time result is so high is because, though it is highly improbable, it is overwhelmingly expensive to have 3 wrong attempts.
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- The true dollar expense depends on how much a person's time is worth and how much of the waiting time can be filled with other tasks. If it is work time, it will be one value; if it is time with children, another. At $100 an hour with no fill-in tasks, the average login cost comes to $7,223. And people wonder why computers are so frustrating. Now imagine spending 8 years dealing with ID.me.
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- If this login model is implemented across millions of people, one would hope the company is protecting more than the aggregate login cost per user, otherwise they are costing users more than the value they hold on the system.
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- Catastrophic failure
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- When a person is sitting in an airplane, they probably hope the airline engineers were not thinking in terms of averages, and indeed the engineers were not. Instead, they planned for a very low probability of catastrophic failure.
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- P = 1 - Î (1 - p(ti))
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- Here p(ti) again represents the probability that a specific failure ti could happen. P is then the probability that the system will fail due to any one of the independent parts ti failing. The symbol Î means to take the product.
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- As an example, consider a small business where a Wi-Fi password gets guessed with probability p(t1) = 0.02, the manager clicks a scam email with probability p(t2) = 0.10, and a thief sneaks into the back room with probability p(t3) = 0.01.
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- P = 1 - (1 - 0.02)(1 - 0.10)(1 - 0.01)
- P = 0.13
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- There is a 13% probability that the system will be compromised. That is far higher than would normally be tolerated for a catastrophic risk. Here the biggest contributor was the human variable.
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- This is called the failure equation. Notice that it scales exponentially with the number of terms, making it disproportionately more difficult to drive the total failure rate down as systems grow more complex. For a small, simple computer system it is possible to reach P = 0, but even then it is exceedingly difficult. When it comes to security, small and simple is beautiful.
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- That scenario is unlikely to be found for a system that serves the general public. Most security engineers simply implement existing protocols. Those protocols use algorithms that we assume to be formally proven to be correct, although that is often not the case, and it is certainly not the case for common algorithms used on the Internet. Even for correct security protocols that are correctly implemented, hackers have consistently found physical ways to vary timing, monitor power consumption, or grind the tops off chips to break into systems.
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- The role of perspective
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- It is typical that fraud cases act as linear risk failures from a credit card company's point of view, as they statically plan for some fraud to occur every year. However, those exact same risks are viewed as a catastrophic failure from the individual card holder's point of view. The entire purpose of insurance is to put card holders into the same boat as their card companies.
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- Computer security is almost always treated as an uninsured catastrophic risk situation. There is typically no contract with users, and legally there sometimes can be no contract, to make up for losses after a security lapse.
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- Dynamic behavior
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- In computer security, a single failure is not treated as an isolated event; it spreads like a disease. It is assumed that once an attacker has figured out a way in, the attacker will scale that solution mechanically or sell it on the dark web. Consequently, once a failure occurs, the catastrophic failure equation changes, with a near 100% probability of repeat for the failure term.
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- Helps the bad guys, hurts the good guys
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- Most security systems are breakable or bypassable in the face of extreme innovation and effort. Once broken, an organization starts adding layers of friction on its way to the Marianas Trench.
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- Good-intentioned users do not expend effort to break systems. In contrast, bad actors do. Thus, the trend over time is for security to severely hurt the productivity of good people, while bad actors make use of hard-won know-how to easily bypass it.
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- Emergent properties from secure systems
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- The Marianas Trench paradigm
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- To make a computer secure, disconnect it from the Internet, turn it off, lock it in a safe, hire a firm to take the user, the safe, and armed guards around the world on a ship; then drop the safe into the Marianas Trench.
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- Then to access said computer later, mount a deep sea salvage operation, raise said safe, unlock it, connect the computer to a generator, plug in Starlink, type in the user name, and oops, the password was forgotten.
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- Of course the password was forgotten, because when it was made the system forced the inclusion of capitals, numbers, and special characters, so unless a person named their dog Xr$nzD4s7, they will not remember it. So then travel back home, get out a notebook and look at the password.
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- We have all experienced this in some form or another, grace our IT friends. Thus, we all know intuitively that security comes at the expense of utility. The Marianas Trench paradigm is the asymptotic eventuality for all computer systems that have security as their top priority.
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- Reliability and Security are Competing Forces
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- Security requires the centralization of control where logins, passwords, and identification information are accessed and verified. Central points of control are open to single points of failure. They are also honeypots that attract the most sophisticated of attacks. Once the cat is out of the bag, there is no putting it back, regardless of how capable the security staff is.
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- Economic Progress and Security are Competing Forces
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- Productivity comes from efficiency, and the economy depends upon increased productivity. For reasons just outlined, security is at odds with efficiency. Therefore, overbearing security throttles the economy.
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- For security to be viable, the net economy must be greater than the economy suffering the theft: E - S > E - T. Often, the drag is so severe that S > T. There comes a point when less net forward progress is made on secure systems than insecure ones. Security becomes worse than the theft it prevents.
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- Extraordinary maintenance problem
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- When software has a bug, a patch can be written by most any developer, then issued as an update. In contrast, when security software has a bug, the problem must first be understood by experts, who might not even reside at the company. Often alternative approaches must be architected. Essentially it is starting over.
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- Security fixes are often not as easy to apply because an insecure system might have become compromised. Patching a system that has a backdoor installed on it will result in a patched system with a backdoor. If data has been stolen, no patch can take the stolen data out of the hands of those who took it. Furthermore, customer support can typically do little or nothing, as security features often cannot be turned off.
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- Engineers Design to Spec, Leaders Carry Vision
- The Biometric Fallacy
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- The startup Pay By Touch incinerated $130 million on the premise that fingerprints are passwords. Yet sounding like a cool tech was enough to command a lot of funding.
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- The physical reality: A person leaves their "password" on every water glass, door handle, and table they touch. Security engineers design to specifications and can lose sight of the forest for the trees. They can build a mathematically perfect verification algorithm while remaining structurally blind to the physical reality that the "secret" is being left on a restaurant table. Leaders provide common sense vision. If a person is a leader, they should not be afraid to ask questions about the base metrics of performance and expect answers that they understand.
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- The Technician's Crouch
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- In 1996, at a presentation to the SBC board, a man proposed a smartphone technology investment. One of the board members invited their "tech guy" to "interpret." Feeling his expertise was being challenged, the technician argued defensively that phone switches were the future and smartphones were a fad, simply because switches were what he understood. Two years later, the switch-centric giants like Nortel went into bankruptcy, and the world moved to the smartphone. Off switches were being handled by voice over IP.
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- Technicians optimize for the survival of their current tools and silos. They are rarely big-picture visionaries. Lawmakers must trust their common-sense judgment, and expect entrenched technology interests to propose further entrenchment. The goal is structural architectural integrity for the economy, rather than adding more layers that make life difficult for a person.
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- The coming security apocalypse
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- The situation with public key cryptography
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- All security today is built over communications that are secured by public key cryptography. There is no formal proof for any public key cryptography algorithm in use today that demonstrates that at a computation theoretical level it actually works.
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- Thus, catastrophic failure could arrive at any hour, and then all security on the Internet, current ID schemes, bitcoin, etc. would be broken. This lack of proof problem speaks to public key cryptography at the most fundamental level, and thus applies to existing hardware, software, and systems. When quantum computing comes online, Shorâs algorithm will break public key cryptography.
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- The situation with biometrics
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- Fingerprints are left on door knobs and glasses. A fingerprint cannot be used as a secure password. Our faces are shown in public and in modern times are captured by cameras in buildings on street corners, through the front windshield when we drive under traffic cameras, and by anyone who gets within a few hundred meters and can take a snapshot.
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- Generative AI is already a reality and a practical technology. With generative AI a signal with a life-like model can be created and given to a computer in place of a camera output. Today there is no long-term secure biometric system.
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- Why do we want to ID computer users
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- Policing money
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- A product of the 1970s War on Drugs. To stop the outflow of illicit payments, the state began monitoring the movement of value. This transformed the bank from a private vault into a state monitoring station. All money being transferred had to have a name attached to it.
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- Citizenship-Based Taxation (CBT)
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- The United States is one of only two nations that utilizes Citizenship-Based Taxation (CBT) instead of Residency-Based Taxation (RBT). Because the IRS must track every dollar a citizen touches globally, the US is the lead architect of the global financial "Phone Home" system. This requires every bank on the planet to report on American dealings (FATCA).
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- This structural requirement is the hidden driver for an interoperable, global digital ID. Every dollar is now a suspected launderer, a drug payment, or a tax-evading "sneak." In a CBT world, the source and identity of the money are more important to the state than the payment itself.
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- We are reaching a critical instability point where we need ID to organize our databases
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- Due to the explosion in number and size of databases, IDs are needed to keep the databases coherent and accurate, and to unify them. This is desired both by the tech companies and law enforcement.
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- State (The Sovereign Sinks & Secret Ledgers)
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- | State Database / Agency |
- Primary Data Harvested |
- Impact on Identity |
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- | State DMVs / Real ID |
- Facial biometrics, physical characteristics, home address. |
- The foundational physical anchor; increasingly weaponized by law enforcement for automated facial recognition sweeps. |
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- | IRS & Social Security (SSA) |
- SSN, income, employment history, family structure. |
- The ultimate financial gatekeeper; defines the "Right to Work" and the legal existence of the citizen. |
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- | Incarceration (3 Layers) |
- Local jail bookings, State DOC records, Federal BOP data. |
- Creates a permanent, multi-jurisdictional underclass. Often networked via private aggregators, ensuring data persists even after exoneration. |
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- | Child Welfare (e.g., CCWIS) |
- Abuse allegations, family history, psychological profiles. |
- Interstate data sharing ensures subjective stigmas follow citizens across borders. |
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- | FBI (NGI Database) / CODIS |
- Fingerprints, iris scans, palm prints, DNA, arrest records. |
- Permanent biological tracking; high risk of false-positive algorithmic criminalization. |
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- | DHS / Customs (CBP) |
- Passport data, international travel history, border scans. |
- Controls physical freedom of movement; tracks global associations and jurisdictional shifts. |
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- | Voter Registration & Courts |
- Party affiliation, voting frequency, civil judgments. |
- Publicly accessible state data aggressively scraped by commercial brokers to fuse political identity with consumer profiles. |
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- | EDGAR (SEC) |
- Corporate submissions, quarterly/annual financial filings. |
- Publicly exposes the financial footprints and corporate affiliations of executives and major shareholders. |
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- Commercial (The Surveillance Brokers & Shadow Financials)
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- | Data Broker / AdTech |
- Primary Data Harvested |
- Impact on Identity |
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- | ChexSystems & EWS (KYC) |
- Account history, bounced checks, suspected fraud profiles. |
- The "Shadow Credit Score" used to deny banking. Crucial Note: Under the Bank Secrecy Act, banks are legally prohibited from telling a citizen what is in their fraud file. |
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- | Meta (Facebook/IG) Graph |
- Social graphs, political leanings, private communications. |
- A de facto global ID database; continuously scraped by AI algorithms to feed state intelligence. |
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- | Acxiom / LiveRamp |
- Up to 3,000 data points per person (offline & online). |
- Creates a "connected identity" linking web browsing to offline purchases. |
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- | Experian / Equifax |
- Credit health, employer data, loan default likelihood. |
- Dictates financial participation; heavily targeted by hackers. |
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- | CoreLogic |
- Complete property, mortgage, and historical tax records. |
- Aggregates physical residence history across millions of property transactions. |
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- | LexisNexis |
- Demographic info, behavioral analytics, public court records. |
- Sells targeted audience segments to private entities and law enforcement. |
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- Monotonic failure: each database is a honeypot, and once data is stolen, the damage cannot be undone. The KYC/Fraud database point is particularly chilling for a Congressional briefing because it highlights a system where the citizen has zero due process, they are judged, convicted, and digitally exiled by a black box they have zero permission to look inside.
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- International scammers
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- Though we police money internationally, to the great consternation of out of jurisdiction banks, many of whom will no longer serve Americans, quizzically we take no enforcement action on international scammers who steal from our senior citizens through phone calls and spam mail. Russian hackers who were found creating conflict on the Internet. By IDing those on the Internet, we can deny access and prevent bad actors from entering the ecosystem in the first place.
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- Current ID efforts
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- Base Categorizations of ID Technology
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- Technologies Used |
- The Structural Flaw |
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- | Physical Hardware Gates |
- mDL (Mobile Wallets), Smart Cards, NFC/RFID |
- Demands mandatory capital expense (Smartphones) and exposes users to tracking. |
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- | Biometric Anchors |
- Facial Recognition, Iris, Fingerprint |
- Biological identifiers cannot be rotated or changed once compromised. |
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- | Cryptographic Ledgers |
- PKI, X.509 Certificates, eIDAS Wallets |
- Requires a centralized "State Bishop" (Certificate Authority) to grant trust. |
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- | Algorithmic Profiling |
- Age-Gating, Credit Scoring, AdTech MAIDs |
- Fuses offline identity with unregulated commercial surveillance markets. |
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- State Sanctioned ID efforts
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- | Initiative Name |
- Jurisdiction |
- Core Technology |
- The Structural Failure |
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- | EU Digital Identity Wallet |
- European Union |
- Public Key (W3C/OpenID) |
- Mandatory cross-border tracking. Vulnerable to quantum collapse and centralized CA compromise. |
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- | Aadhaar |
- India |
- Biometric Match |
- World's largest biometric honeypot. Fails physically: manual labor wears off prints, excluding the poorest. |
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- | GOV.UK One Login |
- United Kingdom |
- AI Biometric Match |
- No offline parity. Deepfakes and injection attacks bypass liveness checks, locking citizens out. |
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- | e-ID |
- Estonia |
- Public Key (Smart Cards) |
- Total digital dependency. "State Bishop" architecture means a single chip failure or CA breach deletes the citizen. |
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- | Singpass |
- Singapore |
- AI Biometric Match |
- Fuses private banking and state services. Synthetic media renders the gatekeeper mathematically blind. |
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- | gov.br |
- Brazil |
- Biometric Match |
- The "Water Glass" Lift: high-res biometrics are static. Once copied, the citizen's identity is permanently breached. |
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- | Login.gov & ID.me |
- United States |
- AI Biometric Match |
- Outsourcing core rights to private VC firms. Honeypot creation. Generative AI makes the biometric barrier obsolete. |
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- | Apple/Google Wallets (mDL) |
- US (General) |
- Public Key (SE) |
- The Mandated Shackle. Gives Silicon Valley monopoly control. Vulnerable to supply chain hardware attacks. |
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- A house built on sand
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- Every one of these technologies collapses under the scenario where identity is proven via credential data that can be observed and duplicated, because any system relying on a replicable digital signal structurally fails to distinguish a legitimate human being from a perfect mathematical or physical simulation.
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- Even Public Key Infrastructure (PKI) falls victim to this structural failure because it merely replaces a physical secret with a mathematical one, while still transmitting the proof across the same channel as the data. Possession Is Not Identity: A public key system proves that a person possesses a private key; it does not prove who that person is. If an attacker uses a memory injection to scrape a private key or intercepts the signing process, the resulting bit-stream is mathematically perfect.
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- The server has no capability to distinguish between the rightful owner and a thief because the "signal" of identity is simply another string of data bundled with the transaction. Because current architectures mix control signals and data, a person's "identity" becomes observable to the system itself. If the math can be seen, it can be simulated.
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- Evolution of ID technology
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- Based on concepts of bureaucracy, mandated expense, and the biometric fallacy, we are looking at Dante's 7 Levels of ID Heck:
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- - Stage 1: The Bureaucratic Number (The Card) - Dehumanization through serialization. Every human is reduced to a state-issued number; the fake ID industry becomes the only "free market."
- - Stage 2: The Mandated Shackle (The Smartphone) - The first government-mandated capital expense. Forcing citizens to pay for a commercial product to exist in society. The "Corporate Smartphone" (Mic/Camera/GPS) ends privacy.
- - Stage 3: The Biological Theft (The Biometric) - Treating a biological "username" as a "password." Security theater. A person leaves their physical "password" on a coffee cup or a door handle.
- - Stage 4: The Aggregation Sinkhole (The Database Explosion) - Convergence of all state and commercial human data. The "Aggregation Force" creates a single point of failure for a person's entire life.
- - Stage 5: The Algorithmic Gatekeeper (The Profiling) - Automated "Evil Thought" detection. Using the ID as a key for age-gating and "child safety" (California model).
- - Stage 6: The Interoperable Web (The Global Wallet) - The end of jurisdictional escape. EU/UK cross-border standards. If a person is banned in one place, they are invisible in all.
- - Stage 7: The Digital Exile (The Marianas Trench) - Total disconnection from the "Right to Exist." De-banking and removal from the digital society. The "Attractor" is reached: a system so secure that even the rightful owner cannot access their life.
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- Current Legislation
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- The following bills represent the current trajectory of federally funded digital identity infrastructure:
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- - H.R. 7270 (The Stop Identity Fraud and Identity Theft Act) - A bill creating federal grant programs through the Treasury to incentivize states to adopt Mobile Driver's Licenses (mDLs) and centralized biometric verification systems.
- - S. 884 (Improving Digital Identity Act) - A bill establishing an interagency task force to develop a nationwide, interoperable digital identity architecture, heavily reliant on existing state DMVs and biometric ledgers.
- - H.R. 4589 (National Digital Identity Act) - A companion proposal pushing for the commercialization and federated sharing of state identity databases with private sector verifiers.
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- A better way forward: The reasoning technology plan
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- We are currently charting a course for the byzantine ending of American civilization, but there is time to change course. We must simplify. Incentives are more powerful than regulations.
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- - Mandatory Efficiency and Economic Impact Statements: Any federal agency or regulated private entity implementing a new security or identity measure must provide a "Net Economic Impact" audit. This addresses the "Nobody Home" problem. If a security measure costs the economy S in lost productivity through customer service paralysis, and the theft it prevents is only T, the measure is illegal if S > T.
- - The Research Integrity Act (Scientific Transparency): Criminalize and fine academic and corporate dishonesty in federally funded or regulated research. Apply the Daubert principle to regulatory research to prevent "Microwaves are Candy" style industry capture.
- - The Digital Habeas Corpus (Database Transparency): Apply FOIA-style transparency to all databases, public and corporate, that utilize a citizen's data. Every person has a right to see, contest, and correct any entry.
- - Verifiable Architectural Provenance: Mandate that the provenance of all AI-driven media be identifiable via an architectural signaling standard. A person must be able to distinguish between human and synthetic media at the architectural level.
- - Shift to Offensive International Policing: Redirect federal resources from "IDing the Victim" to "Tracking the Attacker." Policing the borders of the internet is more effective than turning the interior into a digital prison for citizens.
- - Structural elimination of security dependencies: The best security is removing the need for it. Citizenship-Based Taxation (CBT) requires a massive, global surveillance apparatus to track every citizenâs financial movements. Ending CBT and shifting from income tax to trade duties would structurally eliminate the need for vast swathes of the current global digital tracking infrastructure. Organizations like American Citizens Abroad (ACA) advocate for ending CBT, and similar efforts support state-side banking access for expats burdened by the current surveillance dragnet.
- - Reasoning Technology ID technology, RTID: Existing models force lawmakers into a false choice between massive surveillance honeypots or zero utility. Reasoning Technology has developed a foundational identity architecture that shatters this dichotomy. It works in the presence of quantum technology, works in the presence of strong AI, works without special hardware features, has minimal productivity impact, and is maintainable.
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- Appendices
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- Appendix A: "Microwaves are Candy" and the Corporate Track Record
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- The current RF/Microwave regulations entirely ignore cellular and neurological damage. When told that wireless signals are entirely safe, look at the historical track record of corporate industry assurances: X-Rays, Leaded Gasoline, Thalidomide, Asbestos, Tobacco, PFAS, and Glyphosate. The FDA must conduct and rely upon conflict-free studies.
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- Appendix B: The Aadhaar Tragedy
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- India's Aadhaar system is the ultimate realization of Stage 4. A centralized biometric database that has suffered massive data leaks and routinely excludes the poorest citizens because their manual labor has worn off their fingerprints.
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- Appendix C: The History of "Secure" Cryptographic Backdoors
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- - The "Clipper Chip" (1990s): The NSA attempted to mandate a microchip with a "key escrow." Independent researchers found vulnerabilities allowing anyone to exploit the backdoor.
- - The _NSAKEY Controversy (1999): A secondary cryptographic key embedded inside Windows NT 4.0 highlighted the vulnerability of relying on proprietary corporate security.
- - Dual_EC_DRBG (2006-2013): The NSA promoted a standard containing a structural backdoor, completely compromising the "secure" networks of anyone using it.
- - Crypto AG & Operation Rubicon: A Swiss manufacturer of encryption machines was secretly owned by intelligence agencies to intentionally weaken algorithms.
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As demonstrated in the