Propositions
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Automated Unbounded Verification of Stateful Cryptographic Protocols
Automated Unbounded Verification of Stateful Cryptographic Protocols with Exclusive OR Jannik Dreier Lucca Hirschi Sasaˇ Radomirovic´ Ralf Sasse Universite´ de Lorraine Department of School of Department of CNRS, Inria, LORIA Computer Science Science and Engineering Computer Science F-54000 Nancy ETH Zurich University of Dundee ETH Zurich France Switzerland UK Switzerland [email protected] [email protected] [email protected] [email protected] Abstract—Exclusive-or (XOR) operations are common in cryp- on widening the scope of automated protocol verification tographic protocols, in particular in RFID protocols and elec- by extending the class of properties that can be verified to tronic payment protocols. Although there are numerous appli- include, e.g., equivalence properties [19], [24], [27], [51], cations, due to the inherent complexity of faithful models of XOR, there is only limited tool support for the verification of [14], extending the adversary model with complex forms of cryptographic protocols using XOR. compromise [13], or extending the expressiveness of protocols, The TAMARIN prover is a state-of-the-art verification tool e.g., by allowing different sessions to update a global, mutable for cryptographic protocols in the symbolic model. In this state [6], [43]. paper, we improve the underlying theory and the tool to deal with an equational theory modeling XOR operations. The XOR Perhaps most significant is the support for user-specified theory can be freely combined with all equational theories equational theories allowing for the modeling of particular previously supported, including user-defined equational theories. cryptographic primitives [21], [37], [48], [24], [35]. -
Against Logical Form
Against logical form Zolta´n Gendler Szabo´ Conceptions of logical form are stranded between extremes. On one side are those who think the logical form of a sentence has little to do with logic; on the other, those who think it has little to do with the sentence. Most of us would prefer a conception that strikes a balance: logical form that is an objective feature of a sentence and captures its logical character. I will argue that we cannot get what we want. What are these extreme conceptions? In linguistics, logical form is typically con- ceived of as a level of representation where ambiguities have been resolved. According to one highly developed view—Chomsky’s minimalism—logical form is one of the outputs of the derivation of a sentence. The derivation begins with a set of lexical items and after initial mergers it splits into two: on one branch phonological operations are applied without semantic effect; on the other are semantic operations without phono- logical realization. At the end of the first branch is phonological form, the input to the articulatory–perceptual system; and at the end of the second is logical form, the input to the conceptual–intentional system.1 Thus conceived, logical form encompasses all and only information required for interpretation. But semantic and logical information do not fully overlap. The connectives “and” and “but” are surely not synonyms, but the difference in meaning probably does not concern logic. On the other hand, it is of utmost logical importance whether “finitely many” or “equinumerous” are logical constants even though it is hard to see how this information could be essential for their interpretation. -
Truth-Bearers and Truth Value*
Truth-Bearers and Truth Value* I. Introduction The purpose of this document is to explain the following concepts and the relationships between them: statements, propositions, and truth value. In what follows each of these will be discussed in turn. II. Language and Truth-Bearers A. Statements 1. Introduction For present purposes, we will define the term “statement” as follows. Statement: A meaningful declarative sentence.1 It is useful to make sure that the definition of “statement” is clearly understood. 2. Sentences in General To begin with, a statement is a kind of sentence. Obviously, not every string of words is a sentence. Consider: “John store.” Here we have two nouns with a period after them—there is no verb. Grammatically, this is not a sentence—it is just a collection of words with a dot after them. Consider: “If I went to the store.” This isn’t a sentence either. “I went to the store.” is a sentence. However, using the word “if” transforms this string of words into a mere clause that requires another clause to complete it. For example, the following is a sentence: “If I went to the store, I would buy milk.” This issue is not merely one of conforming to arbitrary rules. Remember, a grammatically correct sentence expresses a complete thought.2 The construction “If I went to the store.” does not do this. One wants to By Dr. Robert Tierney. This document is being used by Dr. Tierney for teaching purposes and is not intended for use or publication in any other manner. 1 More precisely, a statement is a meaningful declarative sentence-type. -
CS 50010 Module 1
CS 50010 Module 1 Ben Harsha Apr 12, 2017 Course details ● Course is split into 2 modules ○ Module 1 (this one): Covers basic data structures and algorithms, along with math review. ○ Module 2: Probability, Statistics, Crypto ● Goal for module 1: Review basics needed for CS and specifically Information Security ○ Review topics you may not have seen in awhile ○ Cover relevant topics you may not have seen before IMPORTANT This course cannot be used on a plan of study except for the IS Professional Masters program Administrative details ● Office: HAAS G60 ● Office Hours: 1:00-2:00pm in my office ○ Can also email for an appointment, I’ll be in there often ● Course website ○ cs.purdue.edu/homes/bharsha/cs50010.html ○ Contains syllabus, homeworks, and projects Grading ● Module 1 and module are each 50% of the grade for CS 50010 ● Module 1 ○ 55% final ○ 20% projects ○ 20% assignments ○ 5% participation Boolean Logic ● Variables/Symbols: Can only be used to represent 1 or 0 ● Operations: ○ Negation ○ Conjunction (AND) ○ Disjunction (OR) ○ Exclusive or (XOR) ○ Implication ○ Double Implication ● Truth Tables: Can be defined for all of these functions Operations ● Negation (¬p, p, pC, not p) - inverts the symbol. 1 becomes 0, 0 becomes 1 ● Conjunction (p ∧ q, p && q, p and q) - true when both p and q are true. False otherwise ● Disjunction (p v q, p || q, p or q) - True if at least one of p or q is true ● Exclusive Or (p xor q, p ⊻ q, p ⊕ q) - True if exactly one of p or q is true ● Implication (p → q) - True if p is false or q is true (q v ¬p) ● -
Notes on Mathematical Logic David W. Kueker
Notes on Mathematical Logic David W. Kueker University of Maryland, College Park E-mail address: [email protected] URL: http://www-users.math.umd.edu/~dwk/ Contents Chapter 0. Introduction: What Is Logic? 1 Part 1. Elementary Logic 5 Chapter 1. Sentential Logic 7 0. Introduction 7 1. Sentences of Sentential Logic 8 2. Truth Assignments 11 3. Logical Consequence 13 4. Compactness 17 5. Formal Deductions 19 6. Exercises 20 20 Chapter 2. First-Order Logic 23 0. Introduction 23 1. Formulas of First Order Logic 24 2. Structures for First Order Logic 28 3. Logical Consequence and Validity 33 4. Formal Deductions 37 5. Theories and Their Models 42 6. Exercises 46 46 Chapter 3. The Completeness Theorem 49 0. Introduction 49 1. Henkin Sets and Their Models 49 2. Constructing Henkin Sets 52 3. Consequences of the Completeness Theorem 54 4. Completeness Categoricity, Quantifier Elimination 57 5. Exercises 58 58 Part 2. Model Theory 59 Chapter 4. Some Methods in Model Theory 61 0. Introduction 61 1. Realizing and Omitting Types 61 2. Elementary Extensions and Chains 66 3. The Back-and-Forth Method 69 i ii CONTENTS 4. Exercises 71 71 Chapter 5. Countable Models of Complete Theories 73 0. Introduction 73 1. Prime Models 73 2. Universal and Saturated Models 75 3. Theories with Just Finitely Many Countable Models 77 4. Exercises 79 79 Chapter 6. Further Topics in Model Theory 81 0. Introduction 81 1. Interpolation and Definability 81 2. Saturated Models 84 3. Skolem Functions and Indescernables 87 4. Some Applications 91 5. -
Least Sensitive (Most Robust) Fuzzy “Exclusive Or” Operations
Need for Fuzzy . A Crisp \Exclusive Or" . Need for the Least . Least Sensitive For t-Norms and t- . Definition of a Fuzzy . (Most Robust) Main Result Interpretation of the . Fuzzy \Exclusive Or" Fuzzy \Exclusive Or" . Operations Home Page Title Page 1 2 Jesus E. Hernandez and Jaime Nava JJ II 1Department of Electrical and J I Computer Engineering 2Department of Computer Science Page1 of 13 University of Texas at El Paso Go Back El Paso, TX 79968 [email protected] Full Screen [email protected] Close Quit Need for Fuzzy . 1. Need for Fuzzy \Exclusive Or" Operations A Crisp \Exclusive Or" . Need for the Least . • One of the main objectives of fuzzy logic is to formalize For t-Norms and t- . commonsense and expert reasoning. Definition of a Fuzzy . • People use logical connectives like \and" and \or". Main Result • Commonsense \or" can mean both \inclusive or" and Interpretation of the . \exclusive or". Fuzzy \Exclusive Or" . Home Page • Example: A vending machine can produce either a coke or a diet coke, but not both. Title Page • In mathematics and computer science, \inclusive or" JJ II is the one most frequently used as a basic operation. J I • Fact: \Exclusive or" is also used in commonsense and Page2 of 13 expert reasoning. Go Back • Thus: There is a practical need for a fuzzy version. Full Screen • Comment: \exclusive or" is actively used in computer Close design and in quantum computing algorithms Quit Need for Fuzzy . 2. A Crisp \Exclusive Or" Operation: A Reminder A Crisp \Exclusive Or" . Need for the Least . -
Logic, Proofs
CHAPTER 1 Logic, Proofs 1.1. Propositions A proposition is a declarative sentence that is either true or false (but not both). For instance, the following are propositions: “Paris is in France” (true), “London is in Denmark” (false), “2 < 4” (true), “4 = 7 (false)”. However the following are not propositions: “what is your name?” (this is a question), “do your homework” (this is a command), “this sentence is false” (neither true nor false), “x is an even number” (it depends on what x represents), “Socrates” (it is not even a sentence). The truth or falsehood of a proposition is called its truth value. 1.1.1. Connectives, Truth Tables. Connectives are used for making compound propositions. The main ones are the following (p and q represent given propositions): Name Represented Meaning Negation p “not p” Conjunction p¬ q “p and q” Disjunction p ∧ q “p or q (or both)” Exclusive Or p ∨ q “either p or q, but not both” Implication p ⊕ q “if p then q” Biconditional p → q “p if and only if q” ↔ The truth value of a compound proposition depends only on the value of its components. Writing F for “false” and T for “true”, we can summarize the meaning of the connectives in the following way: 6 1.1. PROPOSITIONS 7 p q p p q p q p q p q p q T T ¬F T∧ T∨ ⊕F →T ↔T T F F F T T F F F T T F T T T F F F T F F F T T Note that represents a non-exclusive or, i.e., p q is true when any of p, q is true∨ and also when both are true. -
Chapter 3 – Describing Syntax and Semantics CS-4337 Organization of Programming Languages
!" # Chapter 3 – Describing Syntax and Semantics CS-4337 Organization of Programming Languages Dr. Chris Irwin Davis Email: [email protected] Phone: (972) 883-3574 Office: ECSS 4.705 Chapter 3 Topics • Introduction • The General Problem of Describing Syntax • Formal Methods of Describing Syntax • Attribute Grammars • Describing the Meanings of Programs: Dynamic Semantics 1-2 Introduction •Syntax: the form or structure of the expressions, statements, and program units •Semantics: the meaning of the expressions, statements, and program units •Syntax and semantics provide a language’s definition – Users of a language definition •Other language designers •Implementers •Programmers (the users of the language) 1-3 The General Problem of Describing Syntax: Terminology •A sentence is a string of characters over some alphabet •A language is a set of sentences •A lexeme is the lowest level syntactic unit of a language (e.g., *, sum, begin) •A token is a category of lexemes (e.g., identifier) 1-4 Example: Lexemes and Tokens index = 2 * count + 17 Lexemes Tokens index identifier = equal_sign 2 int_literal * mult_op count identifier + plus_op 17 int_literal ; semicolon Formal Definition of Languages • Recognizers – A recognition device reads input strings over the alphabet of the language and decides whether the input strings belong to the language – Example: syntax analysis part of a compiler - Detailed discussion of syntax analysis appears in Chapter 4 • Generators – A device that generates sentences of a language – One can determine if the syntax of a particular sentence is syntactically correct by comparing it to the structure of the generator 1-5 Formal Methods of Describing Syntax •Formal language-generation mechanisms, usually called grammars, are commonly used to describe the syntax of programming languages. -
Hardware Abstract the Logic Gates References Results Transistors Through the Years Acknowledgements
The Practical Applications of Logic Gates in Computer Science Courses Presenters: Arash Mahmoudian, Ashley Moser Sponsored by Prof. Heda Samimi ABSTRACT THE LOGIC GATES Logic gates are binary operators used to simulate electronic gates for design of circuits virtually before building them with-real components. These gates are used as an instrumental foundation for digital computers; They help the user control a computer or similar device by controlling the decision making for the hardware. A gate takes in OR GATE AND GATE NOT GATE an input, then it produces an algorithm as to how The OR gate is a logic gate with at least two An AND gate is a consists of at least two A NOT gate, also known as an inverter, has to handle the output. This process prevents the inputs and only one output that performs what inputs and one output that performs what is just a single input with rather simple behavior. user from having to include a microprocessor for is known as logical disjunction, meaning that known as logical conjunction, meaning that A NOT gate performs what is known as logical negation, which means that if its input is true, decision this making. Six of the logic gates used the output of this gate is true when any of its the output of this gate is false if one or more of inputs are true. If all the inputs are false, the an AND gate's inputs are false. Otherwise, if then the output will be false. Likewise, are: the OR gate, AND gate, NOT gate, XOR gate, output of the gate will also be false. -
Boolean Algebra
Boolean Algebra ECE 152A – Winter 2012 Reading Assignment Brown and Vranesic 2 Introduction to Logic Circuits 2.5 Boolean Algebra 2.5.1 The Venn Diagram 2.5.2 Notation and Terminology 2.5.3 Precedence of Operations 2.6 Synthesis Using AND, OR and NOT Gates 2.6.1 Sum-of-Products and Product of Sums Forms January 11, 2012 ECE 152A - Digital Design Principles 2 Reading Assignment Brown and Vranesic (cont) 2 Introduction to Logic Circuits (cont) 2.7 NAND and NOR Logic Networks 2.8 Design Examples 2.8.1 Three-Way Light Control 2.8.2 Multiplexer Circuit January 11, 2012 ECE 152A - Digital Design Principles 3 Reading Assignment Roth 2 Boolean Algebra 2.3 Boolean Expressions and Truth Tables 2.4 Basic Theorems 2.5 Commutative, Associative, and Distributive Laws 2.6 Simplification Theorems 2.7 Multiplying Out and Factoring 2.8 DeMorgan’s Laws January 11, 2012 ECE 152A - Digital Design Principles 4 Reading Assignment Roth (cont) 3 Boolean Algebra (Continued) 3.1 Multiplying Out and Factoring Expressions 3.2 Exclusive-OR and Equivalence Operation 3.3 The Consensus Theorem 3.4 Algebraic Simplification of Switching Expressions January 11, 2012 ECE 152A - Digital Design Principles 5 Reading Assignment Roth (cont) 4 Applications of Boolean Algebra Minterm and Maxterm Expressions 4.3 Minterm and Maxterm Expansions 7 Multi-Level Gate Circuits NAND and NOR Gates 7.2 NAND and NOR Gates 7.3 Design of Two-Level Circuits Using NAND and NOR Gates 7.5 Circuit Conversion Using Alternative Gate Symbols January 11, 2012 ECE 152A - Digital Design Principles 6 Boolean Algebra Axioms of Boolean Algebra Axioms generally presented without proof 0 · 0 = 0 1 + 1 = 1 1 · 1 = 1 0 + 0 = 0 0 · 1 = 1 · 0 = 0 1 + 0 = 0 + 1 = 1 if X = 0, then X’ = 1 if X = 1, then X’ = 0 January 11, 2012 ECE 152A - Digital Design Principles 7 Boolean Algebra The Principle of Duality from Zvi Kohavi, Switching and Finite Automata Theory “We observe that all the preceding properties are grouped in pairs. -
Exclusive Or. Compound Statements. Order of Operations. Logically Equivalent Statements
MATH110 Lecturenotes–1 Exclusive or. Compound statements. Order of operations. Logically equivalent statements. Expressing some operations in terms of others. Exclusive or (exclusive disjunction). Exclusive or (aka exclusive disjunction) is an operation denoted by ⊕ and defined by the following truth table: P Q P ⊕ Q T T F T F T F T T F F F So, P ⊕ Q means “either P or Q, but not both.” Compound statements. A compound statement is an expression with one or more propositional vari- able(s) and two or more logical connectives (operators). Examples: • (P ∧ Q) → R • (¬P → (Q ∨ P )) ∨ (¬Q) • ¬(¬P ). Given the truth value of each propositional variable, we can determine the truth value of the compound statement. 1 Order of operations. Just like in algebra, expressions in parentheses are evaluated first. Otherwise, negations are performed first, then conjunctions, followed by disjunctions (in- cluding exclusive disjunctions), implications, and, finally, the biconditionals. For example, if P is True, Q is False, and R is True, then the truth value of ¬P → Q∧(R∨P ) is computed as follows: first, in parentheses we have R∨P is True, next, ¬P is False, then Q ∧ (R ∨ P ) is False, so ¬P → Q ∧ (R ∨ P ) is True. In other words, ¬P → Q ∧ (R ∨ P ) is equivalent to (¬P ) → (Q ∧ (R ∨ P )). Remark. The order given above is the most often used one. Some authors use other orders. In particular, many authors treat ∧ and ∨ equally (so these are evaluated in the order in which they appear in the expression, just like × and ÷ in algebra), and → and ↔ equally (but after ∧ and ∨, like + and − are performed after × and ÷). -
The History of Logic
c Peter King & Stewart Shapiro, The Oxford Companion to Philosophy (OUP 1995), 496–500. THE HISTORY OF LOGIC Aristotle was the first thinker to devise a logical system. He drew upon the emphasis on universal definition found in Socrates, the use of reductio ad absurdum in Zeno of Elea, claims about propositional structure and nega- tion in Parmenides and Plato, and the body of argumentative techniques found in legal reasoning and geometrical proof. Yet the theory presented in Aristotle’s five treatises known as the Organon—the Categories, the De interpretatione, the Prior Analytics, the Posterior Analytics, and the Sophistical Refutations—goes far beyond any of these. Aristotle holds that a proposition is a complex involving two terms, a subject and a predicate, each of which is represented grammatically with a noun. The logical form of a proposition is determined by its quantity (uni- versal or particular) and by its quality (affirmative or negative). Aristotle investigates the relation between two propositions containing the same terms in his theories of opposition and conversion. The former describes relations of contradictoriness and contrariety, the latter equipollences and entailments. The analysis of logical form, opposition, and conversion are combined in syllogistic, Aristotle’s greatest invention in logic. A syllogism consists of three propositions. The first two, the premisses, share exactly one term, and they logically entail the third proposition, the conclusion, which contains the two non-shared terms of the premisses. The term common to the two premisses may occur as subject in one and predicate in the other (called the ‘first figure’), predicate in both (‘second figure’), or subject in both (‘third figure’).