Shining Light on Darkness
Paquette Has Found Algorithms in the
Wisconsin State Voter Registration
Data Base, Plus Illegal Clone Voters
Article Published
by Jerome R. Corsi, Ph.D.
Andrew Paquette, Ph.D., has discovered the presence of cryptographic algorithms in the Wisconsin State Board of Elections voter registration database. Similar to what Paquette found in New York and Ohio, the Wisconsin Board of Elections assigns voter identification numbers (IDs) in three different methods: incrementing voter ID numbers by 1, according to the order of voter registration (considered the normal way of assigning voter IDs); incrementing voter registration numbers by variable multiples of ten; and an increment method designed to appear random.
As we have noted previously, renumbering voter registration databases so that voter ID is not a function of the date the voter registered appears to be the first step in an encryption scheme resembling the ciphers card cheats utilize to insert marked cards into a fresh deck of cards.
Paquette explained that an indication that cryptographic algorithms were present in the Wisconsin voter registration database were various county scatterplots in which voter ID was assigned by undisclosed algorithmic reordering (not by the chronological ordering of their registration dates).
For instance, Paquette noted the scatterplot of voter IDs for Wood County, Wisconsin (Figure 1) “shows a clear shift in ID number assignment around 2016. From 2006 to 2015, there’s a pattern of ascending ID numbers. In 2016, there was an abrupt change, with new registrations receiving ID numbers similar to those used a decade earlier. This pattern continues through 2024, suggesting a significant reset or change in the ID assignment system in 2016.”
Figure 1, Wood County, Wisconsin, ID numbers, close-up
Table 1: Dane County, Wisconsin
50 gap frequencies compared
Paquette stressed the covert nature of cryptographic algorithms placed within voter registration ID databases:
A fundamental rule of database management is that all data should be transparent, traceable, and used only for its intended purpose. The algorithms found in various state databases violate this rule by introducing what amounts to undocumented attributes into the database. This makes it untraceable by normal means and can enable manipulations that violate the intended purpose of the databases.
In what he terms “gap analysis,” Paquette found a pattern in which sequential voter IDs in various Wisconsin counties were incremented by multiples of 10. “The order of the numbers appears randomized,” he observed, “leading to sequences like the following: 20, 120, 50, 120, 430, 190, 50, 489, 40, 570, 10. Analysis of Dane County, Wisconsin, showed the most significant number of gap frequencies occurred with increment of subsequent numbers by 10 (65,898 occurrences in the first 50 gap frequencies compared), by 20 (25,907 frequencies), by 30 (15,389 frequencies), etc., as demonstrated in Table 1.
He was particularly alarmed at the exceptionally high number of clone voters (duplicate registrations for the same voter) he found in Wisconsin. Paquette reported that in a Wisconsin voter registration database numbering 7,744,986 records, he found 874,455 suspicious records, with at least 437,227 likely clones. He explained:
While I haven’t discussed these findings with Wisconsin officials, I have conferred with multiple county Board of Elections (BOE) commissioners in New York about similar findings. Two commissioners explicitly acknowledged that the records I presented were either real and existed in their database or were similar to records they knew of in their databases. They both told me that clone records violate state and federal law.
One commissioner explained that preventing cloned records was beyond his control due to multiple legal sources for registration applications, claiming it was impossible to prevent simultaneous processing of forms for the same voter. However, this explanation fails to account for cases where multiple ID numbers had photographic reproductions of the same signature, indicating a single origin rather than disparate sources.
Table 2: Clone registrations by year, Wisconsin
An even more significant concern was that the number of new clone records generated yearly has rapidly increased since the passage of the Help America Vote Act (HAVA) in 2002. Until 2002, new clone registrations never exceeded 3.00 percent of the total registrations in any given year (Table 2).
Paquette explained his concern: “In 2003, clones crossed the 3.00% barrier to 3.41% for the first time. From then on, the number of clones increases year over year, with spikes in presidential election years. The highest number recorded to date is 35.82% of all registrations in 2021, and currently rests at 20.06% for the still incomplete year 2024.”
He concluded: “These findings indicate potentially unethical management of Wisconsin’s voter roll records. Regardless of intent, the algorithm’s use creates a hidden classification system for data segregation, posing a security risk. The large number of cloned records exacerbates this risk, as such records would be of particular interest to those seeking to misuse voter rolls—a concern recently realized when Wisconsin mailed absentee ballots to inactive voters.”