Defining Privacy for Weighted Votes, Single and Multi-Voter Coercion - PowerPoint PPT Presentation

Introduction Defining Privacy Defining Receipt-Freeness Defining Coercion-Resistance Conclusion Defining Privacy for Weighted Votes, Single and Multi-Voter Coercion Jannik Dreier, Pascal Lafourcade, Yassine Lakhnech Université Grenoble 1, CNRS, Verimag, France European Symposium on Research in Computer Security (ESORICS), Pisa, Italy September 11, 2012 Jannik Dreier, Pascal Lafourcade, Yassine Lakhnech Privacy for Weighted Votes, Single & Multi-Voter Coercion

Introduction Defining Privacy Defining Receipt-Freeness Defining Coercion-Resistance Conclusion Internet voting Available in Estonia France Switzerland . . . Jannik Dreier, Pascal Lafourcade, Yassine Lakhnech Privacy for Weighted Votes, Single & Multi-Voter Coercion

Introduction Defining Privacy Defining Receipt-Freeness Defining Coercion-Resistance Conclusion Security Requirements Fairness Verifiability Eligibility Correctness Security Requirements Privacy Receipt-Freeness Robustness Coercion-Resistance Jannik Dreier, Pascal Lafourcade, Yassine Lakhnech Privacy for Weighted Votes, Single & Multi-Voter Coercion

Introduction Defining Privacy Defining Receipt-Freeness Defining Coercion-Resistance Conclusion Security Requirements Fairness Verifiability Eligibility Correctness Security Requirements Privacy Receipt-Freeness Robustness Coercion-Resistance Jannik Dreier, Pascal Lafourcade, Yassine Lakhnech Privacy for Weighted Votes, Single & Multi-Voter Coercion

Introduction Defining Privacy Defining Receipt-Freeness Defining Coercion-Resistance Conclusion Defining Vote-Privacy [Swap-Privacy (SwP)] Classical definition (e.g. [ ? , ? , ? ]): Observational equivalence between two situations where two voters swap votes. Alice Bob Vote A B ≈ l Vote B A Jannik Dreier, Pascal Lafourcade, Yassine Lakhnech Privacy for Weighted Votes, Single & Multi-Voter Coercion

Introduction Defining Privacy Defining Receipt-Freeness Defining Coercion-Resistance Conclusion Problem: Weighted Votes What happens if votes are weighted (e.g. according to the number of shares in a company)? Alice Bob Result 66% 34% Vote A B 66% A, 34% B ≈ l Vote B A 34% A, 66% B Jannik Dreier, Pascal Lafourcade, Yassine Lakhnech Privacy for Weighted Votes, Single & Multi-Voter Coercion

Introduction Defining Privacy Defining Receipt-Freeness Defining Coercion-Resistance Conclusion Problem: Weighted Votes What happens if votes are weighted (e.g. according to the number of shares in a company)? Alice Bob Result 66% 34% Vote A B 66% A, 34% B ≈ l Vote B A 34% A, 66% B Jannik Dreier, Pascal Lafourcade, Yassine Lakhnech Privacy for Weighted Votes, Single & Multi-Voter Coercion

Introduction Defining Privacy Defining Receipt-Freeness Defining Coercion-Resistance Conclusion Problem: Weighted Votes What happens if votes are weighted (e.g. according to the number of shares in a company)? Alice Bob Result 66% 34% Vote A B 66% A, 34% B ≈ l � = Vote B A 34% A, 66% B Jannik Dreier, Pascal Lafourcade, Yassine Lakhnech Privacy for Weighted Votes, Single & Multi-Voter Coercion

Introduction Defining Privacy Defining Receipt-Freeness Defining Coercion-Resistance Conclusion Problem: Weighted Votes What happens if votes are weighted (e.g. according to the number of shares in a company)? Alice Bob Result 66% 34% Vote A B 66% A, 34% B �≈ l � = Vote B A 34% A, 66% B Jannik Dreier, Pascal Lafourcade, Yassine Lakhnech Privacy for Weighted Votes, Single & Multi-Voter Coercion

Introduction Defining Privacy Defining Receipt-Freeness Defining Coercion-Resistance Conclusion Problem: Weighted Votes Still: Some privacy is possible! Alice Bob Carol Result 50% 25% 25% Vote A B B 50% A, 50% B Vote B A A 50% A, 50% B Jannik Dreier, Pascal Lafourcade, Yassine Lakhnech Privacy for Weighted Votes, Single & Multi-Voter Coercion

Introduction Defining Privacy Defining Receipt-Freeness Defining Coercion-Resistance Conclusion Problem: Weighted Votes Still: Some privacy is possible! Alice Bob Carol Result 50% 25% 25% Vote A B B 50% A, 50% B Vote B A A 50% A, 50% B Jannik Dreier, Pascal Lafourcade, Yassine Lakhnech Privacy for Weighted Votes, Single & Multi-Voter Coercion

Introduction Defining Privacy Defining Receipt-Freeness Defining Coercion-Resistance Conclusion Problem: Weighted Votes Still: Some privacy is possible! Alice Bob Carol Result 50% 25% 25% Vote A B B 50% A, 50% B = Vote B A A 50% A, 50% B Jannik Dreier, Pascal Lafourcade, Yassine Lakhnech Privacy for Weighted Votes, Single & Multi-Voter Coercion

Introduction Defining Privacy Defining Receipt-Freeness Defining Coercion-Resistance Conclusion Problem: Weighted Votes Still: Some privacy is possible! Alice Bob Carol Result 50% 25% 25% Vote A B B 50% A, 50% B ≈ l = Vote B A A 50% A, 50% B Jannik Dreier, Pascal Lafourcade, Yassine Lakhnech Privacy for Weighted Votes, Single & Multi-Voter Coercion

Introduction Defining Privacy Defining Receipt-Freeness Defining Coercion-Resistance Conclusion Plan 1 Introduction 2 Defining Privacy 3 Defining Receipt-Freeness 4 Defining Coercion-Resistance 5 Conclusion Jannik Dreier, Pascal Lafourcade, Yassine Lakhnech Privacy for Weighted Votes, Single & Multi-Voter Coercion

Introduction Defining Privacy Defining Receipt-Freeness Defining Coercion-Resistance Conclusion Plan 1 Introduction 2 Defining Privacy 3 Defining Receipt-Freeness 4 Defining Coercion-Resistance 5 Conclusion Jannik Dreier, Pascal Lafourcade, Yassine Lakhnech Privacy for Weighted Votes, Single & Multi-Voter Coercion

Introduction Defining Privacy Defining Receipt-Freeness Defining Coercion-Resistance Conclusion Solution: Defining Vote-Privacy (VP) for weighted votes Idea: If two instances give the same result, they should be bisimilar. . . . Alice Bob Result . . . V A V A Vote Result 1 1 2 . . . V B V B Vote Result 2 1 2 Jannik Dreier, Pascal Lafourcade, Yassine Lakhnech Privacy for Weighted Votes, Single & Multi-Voter Coercion

Introduction Defining Privacy Defining Receipt-Freeness Defining Coercion-Resistance Conclusion Solution: Defining Vote-Privacy (VP) for weighted votes Idea: If two instances give the same result, they should be bisimilar. . . . Alice Bob Result . . . V A V A Vote Result 1 1 2 ? = . . . V B V B Vote Result 2 1 2 Jannik Dreier, Pascal Lafourcade, Yassine Lakhnech Privacy for Weighted Votes, Single & Multi-Voter Coercion

Introduction Defining Privacy Defining Receipt-Freeness Defining Coercion-Resistance Conclusion Solution: Defining Vote-Privacy (VP) for weighted votes Idea: If two instances give the same result, they should be bisimilar. . . . Alice Bob Result . . . V A V A Vote Result 1 1 2 ⇐ ? = . . . V B V B Vote Result 2 1 2 Jannik Dreier, Pascal Lafourcade, Yassine Lakhnech Privacy for Weighted Votes, Single & Multi-Voter Coercion

Introduction Defining Privacy Defining Receipt-Freeness Defining Coercion-Resistance Conclusion Solution: Defining Vote-Privacy (VP) for weighted votes Idea: If two instances give the same result, they should be bisimilar. . . . Alice Bob Result . . . V A V A Vote Result 1 1 2 ≈ l ⇐ ? = . . . V B V B Vote Result 2 1 2 Jannik Dreier, Pascal Lafourcade, Yassine Lakhnech Privacy for Weighted Votes, Single & Multi-Voter Coercion

Introduction Defining Privacy Defining Receipt-Freeness Defining Coercion-Resistance Conclusion Example revisited Applying the definition: Alice Bob Carol Result 50% 25% 25% Vote A B B 50% A, 50% B Vote B A A 50% A, 50% B Jannik Dreier, Pascal Lafourcade, Yassine Lakhnech Privacy for Weighted Votes, Single & Multi-Voter Coercion

Introduction Defining Privacy Defining Receipt-Freeness Defining Coercion-Resistance Conclusion Example revisited Applying the definition: Alice Bob Carol Result 50% 25% 25% Vote A B B 50% A, 50% B ? = Vote B A A 50% A, 50% B Jannik Dreier, Pascal Lafourcade, Yassine Lakhnech Privacy for Weighted Votes, Single & Multi-Voter Coercion

Introduction Defining Privacy Defining Receipt-Freeness Defining Coercion-Resistance Conclusion Example revisited Applying the definition: Alice Bob Carol Result 50% 25% 25% Vote A B B 50% A, 50% B ⇐ ? = Vote B A A 50% A, 50% B Jannik Dreier, Pascal Lafourcade, Yassine Lakhnech Privacy for Weighted Votes, Single & Multi-Voter Coercion

Introduction Defining Privacy Defining Receipt-Freeness Defining Coercion-Resistance Conclusion Example revisited Applying the definition: Alice Bob Carol Result 50% 25% 25% Vote A B B 50% A, 50% B ≈ l ⇐ ? = Vote B A A 50% A, 50% B Jannik Dreier, Pascal Lafourcade, Yassine Lakhnech Privacy for Weighted Votes, Single & Multi-Voter Coercion

Introduction Defining Privacy Defining Receipt-Freeness Defining Coercion-Resistance Conclusion The Applied Pi Calculus [ ? ] Syntax P , Q , R := processes 0 null process P | Q parallel composition ! P replication ν n . P name restriction (“new”) if M = N then P else Q conditional in ( u , x ) . P message input out ( u , x ) . P message output { M / x } substitution Jannik Dreier, Pascal Lafourcade, Yassine Lakhnech Privacy for Weighted Votes, Single & Multi-Voter Coercion