Supporting Electronic Voting Research

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Daniel Lopresti Computer Science & Engineering Lehigh University Bethlehem, PA, USA George Nagy Elisa Barney Smith Electrical, Computer, and Systems Engineering Rensselaer Polytechnic Institute Troy, NY, USA Electrical and Computer Engineering Boise State University Boise, ID, USA Lopresti Slide 1

Overview Background: the push toward paper-based voting Issues in processing scanned ballots Opportunties for document analysis research Overview of our ongoing work* Summary * Ideas and a prototype system, but no experimental results yet. Lopresti Slide 2

E-voting in the news Lopresti Slide 3

What are the problems? Recent transition to e-voting in U.S. has been rocky at best: Well-publicized attacks by computer security researchers who have obtained examples of such systems. Votes lost in real elections due to software / hardware failures...... and due to under-trained workers, bad user interface designs. No matter the vendor, one truth holds: all computer systems of this complexity have bugs. Situation exacerbated by: Closed (proprietary) systems, no independent audit trail. Result is loss of voter trust, lawsuits, flurry of new legislation. Lopresti Slide 4

Voting system use in the U.S. From Voting Technology: The Not-So-Simple Act of Casting a Ballot, by Paul S. Herrnson, et al, Brookings Institution Press, 2008. Lopresti Slide 5

How did we get where we are? The infamous butterfly ballot from the 2000 U.S. Presidential election: The Florida ballot is a classic example of bad user interface design. (Computer software can suffer from such problems just as easily.) http://www2.indystar.com/library/factfiles/gov/politics/election2000/img/prezrace/butterfly_large.jpg Lopresti Slide 6

Hanging chads & voter intent Votomatic technology used in Florida was prone to paper jams. This led to hanging and dimpled chads, making it hard to determine voter intent, which provides the legal standard. http://www.cs.uiowa.edu/~jones/cards/chad.html http://www.pushback.com/justice/votefraud/dimpledchadpictures.html Lopresti Slide 7

Counting votes may not be easy Is this a legal vote? Courts would probably say so...... but op-scan readers might not count it. Increasing demands that machine's interpretation match a human's. Lopresti Slide 8

Evaluating election technologies Some general system-level goals for trustworthy elections: Need accurate determination of voter intent. Must preserve voter anonymity. Accessibility for disabled voters and non-native speakers. If possible, prevent overvoting (invalidates voter's ballot). If possible, prevent unintentional undervoting (voter confusion?). Easy to administer, even by under-trained poll workers. Transparently fair. Lopresti Slide 9

Lingering concerns about paper Draft report on Voluntary Voting Systems Guidelines by the Security and Transparency Subcommittee for the Technical Guidelines Development Committee of the National Institute of Standards and Technology (NIST): The widespread adoption of voting systems incorporating paper did not seem to cause any widespread problems in the November 2006 elections. But, the use of paper in elections places more stress on (1) the capabilities of voting system technology, (2) of voters to verify their accuracy, and (3) of election workers to securely handle the ballots and accurately count them. Clearly, the needs of voters and election officials need to be addressed with improved and new technology. The STS believes that current paper-based approaches can be improved to be significantly more usable to voters and election officials... W. Burr, J. Kelsey, R. Peralta, and J. Wack. Requiring software independence in VVSG 2007: STS recommendations for the TGDC. Technical report, National Institute of Standards and Technology, November 2006. http://vote.nist.gov/draftwhitepaperonsiinvvsg2007-20061120.pdf. Lopresti Slide 10

Research questions Issues that arise from using paper ballots in elections: Accurate interpretation of marginal markings. Human cost, error rate, and bias in performing manual recounts. Failure modes in ballot imaging (e.g., paper jams). Systematic errors due to ballot layout (one candidate may be disadvantaged over another based on physical location on page). Also keep in mind: U.S. Elections can be complex (10's to 100's of choices). Impact of voter error (e.g., improper markings, erasures). Potential for traditional ballot-box stuffing. Computer hackers attempting to manipulate the vote. Lopresti Slide 11

Connection to forms processing Similarities to forms processing, but also some key differences: Much broader range of users (education level, literacy, etc.) than for traditional forms applications. Ballots must preserve a voter s anonymity. Demand to count votes and report results quickly. Elections are held infrequently, so voting equipment sits unused for long periods in storage. Poll workers often lack technical expertise. Maintaining chain-of-custody is a critical security requirement. No financial interest in making sure votes are counted accurately, but there is tremendous public interest. Lopresti Slide 12

BallotToolkit Software components written in Tcl/Tk and runnable under both MS Windows and Linux. GUI logs user interactions (all events time-stamped) to facilitate user studies. Data interchange via XML-like file formats. Provides support for: Ballot specification (locating targets, defining races and elections). Ballot ground-truthing (human interpretation of ballot markings). Synthesizing collections of marked ballots. Investigating blind auditing to eliminate human bias. Investigating homogeneous class display to facilitate recounts. Lopresti Slide 13

BallotTool software Blank Ballot Ballot Collection (synthesized or scanned) Mark Recognition BallotTool Software Specification Ground-truth Blind Auditing experiments HCD experiments Lopresti Slide 14

BallotTool GUI Lopresti Slide 15

File format for specifying ballots Blank ballot Associated specification <election ID="election001" Election="Lehigh-Muhlenberg Survey" bb_x1="10" bb_y1="10" bb_x2="2542" bb_y2="3290"> <race ID="race001" Race="The War in Iraq" VoteFor="1" bb_x1="350" bb_y1="1050" bb_x2="800" bb_y2="1105"> <candidate ID="cand001" Candidate="Very Important" bbl_x1="830" bbl_y1="890" bbl_x2="1060" bbl_y2="1020" bbt_x1="900" bbt_y1="1050" bbt_x2="990" bbt_y2="1105"> <candidate ID="cand002" Candidate="Somewhat Important" bbl_x1="1130" bbl_y1="890" bbl_x2="1360" bbl_y2="1020" bbt_x1="1200" bbt_y1="1050" bbt_x2="1290" bbt_y2="1105"> <candidate ID="cand003" Candidate="Not Too Important" bbl_x1="1430" bbl_y1="890" bbl_x2="1660" bbl_y2="1020" bbt_x1="1500" bbt_y1="1050" bbt_x2="1590" bbt_y2="1105"> <candidate ID="cand004" Candidate="Not At All Important" bbl_x1="1730" bbl_y1="890" bbl_x2="1960" bbl_y2="1020" bbt_x1="1800" bbt_y1="1050" bbt_x2="1890" bbt_y2="1105"> </race> <race ID="race002" Race="Global Warming" VoteFor="1" bb_x1="350" bb_y1="1110" bb_x2="800" bb_y2="1165"> <candidate ID="cand001" Candidate="Very Important" bbl_x1="830" bbl_y1="890" bbl_x2="1060" bbl_y2="1020" bbt_x1="900" bbt_y1="1110" bbt_x2="990" bbt_y2="1165">,,, Lopresti Slide 16

BallotTool GUI for blind auditing Lopresti Slide 17

BallotTool GUI for HCD Lopresti Slide 18

BallotGen software Blank Ballot Mark Library Election Specification BallotGen Software Synthetic Ballot Collection (PDF, TIF) Print / Scan Machine interpretation Human interpretation Lopresti Slide 19

Synthesizing ballots Two paradigms for injecting marks on blank ballot substrate: Extract and place pre-marked targets on image. Transform and overlay marks with transparent backgrounds. In latter case, we can: Adjust x- and y-displacement from target center. Scale x- and y-dimensions independently. Rotate mark by a random amount. Re-map grayscale or color of mark. Lopresti Slide 20

Pre-marked targets Lopresti Slide 21

Synthesizing ballots Simulated Lehigh-Muhlenberg 2008 Presidential Election survey. Synthesized using marks that are randomly chosen and placed (some intentionally marginal ). Lopresti Slide 22

Transformed and overlayed marks Lopresti Slide 23

Synthesizing ballot collections Step 2: define marks (ratesstyle for mark Step 1: select blank ballot and4:mark Step define election (# winners) of ballots, Step 3: define races (rates for various prototypes, mark tranforms, etc.) undervote and overvote rates, etc.) Lopresti Slide 24

Summary Status: Prototype nearly complete blind auditing and HCD experiments will commence soon in collaboration with social scientist colleagues. Results to be presented in future papers. Conclusions: Paper ballot processing provides an opportunity to apply document analysis research to a timely and important problem. Upon reflection, a number of other ideas will come to mind. E.g., style-based recognition for interpreting marginal markings. Lopresti Slide 25

Whole-ballot recognition Stray mark? Valid vote? Capture voter intent via style-based techniques. Lopresti Slide 26

http://perfect.cse.lehigh.edu/ Paper and Electronic Records for Elections: Cultivating Trust Thank you! This work was supported in part by the National Science Foundation under award numbers NSF-0716368, NSF-0716393, NSF-0716647, and NSF-0716543. Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect those of the National Science Foundation. Lopresti Slide 27