IS 2150 / TEL 2810 Information Security & Privacy

Slides:



Advertisements
Similar presentations
Partial Orderings Section 8.6.
Advertisements

June 1, 2004Computer Security: Art and Science © Matt Bishop Slide #30-1 Chapter 30: Lattices Overview Definitions Lattices Examples.
Relations Relations on a Set. Properties of Relations.
November 1, 2004Introduction to Computer Security ©2004 Matt Bishop Slide #27-1 Chapter 27: Lattices Overview Definitions Lattices Examples.
Syllabus Every Week: 2 Hourly Exams +Final - as noted on Syllabus
Propositional Logic. Negation Given a proposition p, negation of p is the ‘not’ of p.
Discrete Mathematics Math 6A Instructor: M. Welling.
Partially Ordered Sets (POSets)
Mathematical Induction Assume that we are given an infinite supply of stamps of two different denominations, 3 cents and and 5 cents. Prove using mathematical.
Adapted from Discrete Math
Logics for Data and Knowledge Representation Introduction to Algebra Chiara Ghidini, Luciano Serafini, Fausto Giunchiglia and Vincenzo Maltese.
Propositions and Truth Tables
Course Outline Book: Discrete Mathematics by K. P. Bogart Topics:
CSCI 115 Chapter 2 Logic. CSCI 115 §2.1 Propositions and Logical Operations.
Mathematical Structures A collection of objects with operations defined on them and the accompanying properties form a mathematical structure or system.
Chap. 2 Fundamentals of Logic. Proposition Proposition (or statement): an declarative sentence that is either true or false, but not both. e.g. –Margret.
Barnett/Ziegler/Byleen Finite Mathematics 11e1 Chapter 7 Review Important Terms, Symbols, Concepts 7.1. Logic A proposition is a statement (not a question.
1 CMSC 250 Discrete Structures CMSC 250 Lecture 1.
DISCRETE COMPUTATIONAL STRUCTURES
CS 381 DISCRETE STRUCTURES Gongjun Yan Aug 25, November 2015Introduction & Propositional Logic 1.
Fundamentals of Logic 1. What is a valid argument or proof? 2. Study system of logic 3. In proving theorems or solving problems, creativity and insight.
January 30, 2002Applied Discrete Mathematics Week 1: Logic and Sets 1 Let’s Talk About Logic Logic is a system based on propositions.Logic is a system.
1 IS 2150 / TEL 2810 Introduction to Security James Joshi Associate Professor, SIS Lecture 3 September 15, 2009 Mathematical Review Security Policies.
1 Introduction to Abstract Mathematics Expressions (Propositional formulas or forms) Instructor: Hayk Melikya
Mathematical Preliminaries
Chapter 2 Logic 2.1 Statements 2.2 The Negation of a Statement 2.3 The Disjunction and Conjunction of Statements 2.4 The Implication 2.5 More on Implications.
Chapter 2 Symbolic Logic. Section 2-1 Truth, Equivalence and Implication.
Lecture 1 Overview Topics 1. Proof techniques: induction, contradiction Proof techniques June 1, 2015 CSCE 355 Foundations of Computation.
Chapter 2 Fundamentals of Logic 1. What is a valid argument or proof?
Symbolic Logic The Following slide were written using materials from the Book: The Following slide were written using materials from the Book: Discrete.
Set Theory Concepts Set – A collection of “elements” (objects, members) denoted by upper case letters A, B, etc. elements are lower case brackets are used.
Section 1.4. Propositional Functions Propositional functions become propositions (and have truth values) when their variables are each replaced by a value.
1 IS 2150 / TEL 2810 Introduction to Security James Joshi Assistant Professor, SIS Lecture 3 September 13, 2007 Mathematical Review Security Policies.
Discrete Math by R.S. Chang, Dept. CSIE, NDHU1 Fundamentals of Logic 1. What is a valid argument or proof? 2. Study system of logic 3. In proving theorems.
English for Economic Informatics I Tomáš Foltýnek Theoretical Foundations of Informatics.
Chapter 1 Logic and proofs
DISCRETE COMPUTATIONAL STRUCTURES CSE 2353 Fall 2010 Most slides modified from Discrete Mathematical Structures: Theory and Applications by D.S. Malik.
Chapter 1 Logic and Proof.
Review: Discrete Mathematics and Its Applications
CSCE 355 Foundations of Computation
2. The Logic of Compound Statements Summary
Equivalence Relations
Advanced Algorithms Analysis and Design
CSE15 Discrete Mathematics 01/23/17
CSNB 143 Discrete Mathematical Structures
Discrete Mathematics Logic.
CMSC Discrete Structures
CSCE 355 Foundations of Computation
The Foundations: Logic and Proofs
Principles of Computing – UFCFA3-30-1
CSCI 3310 Mathematical Foundation of Computer Science
Information Technology Department
Discrete Math & Fixed points
CHAPTER 1: LOGICS AND PROOF
Computer Security: Art and Science
IS 2150 / TEL 2810 Introduction to Security
Sungho Kang Yonsei University
IS 2150 / TEL 2810 Introduction to Security
Review: Discrete Mathematics and Its Applications
Computer Security: Art and Science, 2nd Edition
Discrete Mathematics Logic.
Computer Security: Art and Science, 2nd Edition
Predicates and Quantifiers
Introduction to Computer Security
Background material.
Logic Logic is a discipline that studies the principles and methods used to construct valid arguments. An argument is a related sequence of statements.
Background material.
IS 2150 / TEL 2810 Introduction to Security
The Foundations: Logic and Proofs
IS 2150 / TEL 2810 Information Security & Privacy
Presentation transcript:

IS 2150 / TEL 2810 Information Security & Privacy James Joshi Associate Professor, SIS Maths Review Sept 27, 2013 Mathematical Review Security Policies

Objective Review some mathematical concepts Propositional logic Predicate logic Mathematical induction Lattice

Propositional logic/calculus Atomic, declarative statements (propositions) that can be shown to be either TRUE or FALSE but not both; E.g., “Sky is blue”; “3 is less than 4” Propositions can be composed into compound sentences using connectives Negation  p (NOT) highest precedence Disjunction p  q (OR) second precedence Conjunction p  q (AND) second precedence Implication p  q q logical consequence of p Exercise: Truth tables?

Propositional logic/calculus Contradiction: Formula that is always false : p  p What about: (p  p)? Tautology: Formula that is always True : p  p What about: (p  p)? Others Exclusive OR: p  q; p or q but not both Bi-condition: p  q [p if and only if q (p iff q)] Logical equivalence: p  q [p is logically equivalent to q] Some exercises…

Some Laws of Logic Double negation DeMorgan’s law Commutative (p  q)  (p  q) (p  q)  (p  q) Commutative (p  q)  (q  p) Associative law p  (q  r)  (p  q)  r Distributive law p  (q  r)  (p  q)  (p  r) p  (q  r)  (p  q)  (p  r)

Predicate/first order logic Propositional logic Variable, quantifiers, constants and functions Consider sentence: Every directory contains some files Need to capture “every” “some” F(x): x is a file D(y): y is a directory C(x, y): x is a file in directory y

Predicate/first order logic Existential quantifiers  (There exists) E.g.,  x is read as There exists x Universal quantifiers  (For all) y D(y)  (x (F(x) C(x, y))) read as for every y, if y is a directory, then there exists a x such that x is a file and x is in directory y What about x F(x)  (y (D(y) C(x, y)))?

Mathematical Induction Proof technique - to prove some mathematical property E.g. want to prove that M(n) holds for all natural numbers Base case OR Basis: Prove that M(1) holds Induction Hypothesis: Assert that M(n) holds for n = 1, …, k Induction Step: Prove that if M(k) holds then M(k+1) holds

Mathematical Induction Exercise: prove that sum of first n natural numbers is S(n): 1 + … + n = n (n + 1)/2 Prove S(n): 1^2+ .. +n^2 = n (n +1)(2n + 1)/6

Lattice Sets Binary relation R from S to T is a subset of S x T Collection of unique elements Let S, T be sets Cartesian product: S x T = {(a, b) | a  A, b  B} A set of order pairs Binary relation R from S to T is a subset of S x T Binary relation R on S is a subset of S x S If (a, b)  R we write aRb Example: R is “less than equal to” () For S = {1, 2, 3} Example of R on S is {(1, 1), (1, 2), (1, 3), ????) (1, 2)  R is another way of writing 1  2

Lattice Properties of relations Reflexive: Anti-symmetric: Transitive: if aRa for all a  S Anti-symmetric: if aRb and bRa implies a = b for all a, b  S Transitive: if aRb and bRc imply that aRc for all a, b, c  S Which properties hold for “less than equal to” ()? Draw the Hasse diagram Captures all the relations

Lattice Total ordering: Partial ordering (poset): when the relation orders all elements E.g., “less than equal to” () on natural numbers Partial ordering (poset): the relation orders only some elements not all E.g. “less than equal to” () on complex numbers; Consider (2 + 4i) and (3 + 2i)

Lattice u is an upper bound of a and b means aRu and bRu Upper bound (u, a, b  S) u is an upper bound of a and b means aRu and bRu Least upper bound : lub(a, b) closest upper bound Lower bound (l, a, b  S) l is a lower bound of a and b means lRa and lRb Greatest lower bound : glb(a, b) closest lower bound

Lattice A lattice is the combination of a set of elements S and a relation R meeting the following criteria R is reflexive, antisymmetric, and transitive on the elements of S For every s, t  S, there exists a greatest lower bound For every s, t  S, there exists a lowest upper bound Some examples S = {1, 2, 3} and R = ? S = {2+4i; 1+2i; 3+2i, 3+4i} and R = ?

Overview of Lattice Based Models Confidentiality Bell LaPadula Model First rigorously developed model for high assurance - for military Objects are classified Objects may belong to Compartments Subjects are given clearance Classification/clearance levels form a lattice Two rules No read-up No write-down