A Secure Implementation of Java Inner Classes

Size: px
Start display at page:

Download "A Secure Implementation of Java Inner Classes"

Transcription

1 A Secure Implemetatio of Java Ier Classes By Aasua Bhowmik ad William Pugh Departmet of Computer Sciece Uiversity of Marylad More ifo at:

2 Motivatio ad Overview Preset implemetatio of Java ier classes provides a security hole i order to allow ier classes access the private fields of the outer class ad vice versa We desiged a secure techique for allowig access to private fields ad methods No eed to chage the JVM Very little overhead Developed a byte code trasformig tool which modify the class files ad make the ier classes safe

3 Java Ier Classes Ier class is a ew feature added i Java 1.1 Ier classes are classes defied as member of other class Ier classes are allowed to access the private members of the eclosig class ad vice versa For each istace of a outer class there is a correspodig istace of the ier classes class A { private a; class B { private b; void f() { b = a+a; // accessig pvt. var of A public g(){ B myobj = ew B(); myobj.f(); it x = myobj.b; // accessig pvt. var of A

4 Ier Classes AreÕt Uderstood By JVMs Ier classes are implemeted as a compiler trasformatio JVM do ot eed to uderstad ier classes Ð code will ru o 1.0 JVMÕs JVM prohibits access to private members from outside the class Compiler trasforms the class, cotaiig ier classes, to a umber of o-ested classes

5 Implemetatio of Ier Classes class A class A private it m; private class B { private it x; void f(){ x = m; public void g(){ B ob = ew B(); ob.f(); After compilatio private it m; public void g() { A$B ob = ew A$B(); ob.f(); it access$0() { retur m; class A$B A this$0; private it x; void f(){ x = this$0.access$0(); Access$0() of class A has package level visibility. The class A$B also has package level visibility

6 Security Threats with Preset Implemetatio The private data members of classes get exposed through access fuctios Other classes belogig to the same package ca call the access fuctios ad tamper the private data member fu(){ A a = ew A();.. it x = a.access$0(); Class C Udesired access Class C ad A belogs to the same package Class A private it m; public void g() { A$B ob = ew A$B(); ob.f(); it access$0() { retur m;

7 Is This A Problem? Lots of Java code uses ier classes Usig ew 1.2 security model, all privileged code is put i ier classes Still requires attacker get iside package Oe security barrier dow Ð Prefer defese i depth Ed Felto recommeds agaist usig curret versio of ier classes

8 New Implemetatio of Ier Classes The access to the private members are restricted oly to the iteded classes The ew implemetatio is built o top of the curret implemetatio Ð class files are rewritte No eed to chage the JVM A secret key is shared betwee all the classes that eed access to each others private data members Ð Class B wats to access a class AÕs private member m Ð ivokes AÕs access fuctio Ð B passes itõs shared secret key to AÕs access fuctio Ð A verifies whether BÕs secret key ad AÕs secret key are the same object if yes, give access to its private variable m otherwise, throw a security exceptio

9 New Implemetatio of Ier Classes The secret key is a object allocated dyamically durig ru time. Class A allocates a object i its static iitializer ad stores it i its ow private static field A.sharedSecret Class A passes dow the secret key by ivokig the receivesecretkey(a.sharedsecret) of class B I receivesecretkey(object) B stores AÕs secret key i itõs ow private static field, B.sharedSecret Wheever B tries to access AÕs private field it passes itõs shared secret key for autheticatio

10 New Implemetatio of Ier Classes Iitializatio Phase A allocates a ew object ad stores it i A.sharesSecret B wats to access AÕs private Field B ivokes AÕs access method with B.sharedSecret as a argumet A passes the secret key object to B B passes the secret key for verificatio B stores the secret key passed by A i B.sharedSecret A throws security exceptio if secret keys ot match I access method A verifies BÕs secret key A grats access if BÕs secret key matches with AÕs

11 Class A { static private fial Object sharedsecret = ew Object(); static { A$B.receiveSecretForA(sharedSecret); private it x; it access$1(object secretfora) { if (secretfora!=sharedsecret) throw retur x; ew SecurityExceptio(); Class A$B { private A this$0; static private Object sharedsecret; static void receivesecretfora(object secretkey) { if (sharedsecret!= ull) throw ew VerifyError(); sharedsecret = secretkey; É ivoke this$0.access$1(sharedsecret)é

12 Advatages of the New Implemetatio Access is permitted oly to the desired classes No eed to chage the existig JVMs The secret key value is a poiter to memory, allocated dyamically Ð Absolutely impossible to forge The additioal overhead for iitializatio ad validatio of the secret keys are small Very small icrease i the size of the class files

13 Overhead Due to Modificatio For each class allowig/eedig access Ð Oe static field For each set of objects eedig mutual access Ð Oe object created All iitializatios are doe i static iitializer Oe additioal argumet i each access$ method Few additioal istructios are executed for each access call to Ð pass the extra argumet Ð verify the secret key

14 A Rewritig Tool For Jar Files Developed a tool to trasform the byte codes Takes a jar file, examies the class files ad fids out the sets of classes which eed mutual access modify all the class files which are either defiig access$ methods or ivokig access$ methods All the classes i the jar file are made safe i the presece of ier classes Used our tool to modify several jar files - rt.jar, swig.jar etc.

15 Experimetal Result for swig.jar Static Evaluatio: % icrease i the code size - 2.9% # of class files i swig.jar # of ier classes # of ier classes eedig access # of objects created - 53 # of ew fields added # of access methods # of places access methods are ivoked - 439

16 Experimetal Result for swig.jar Rutime Performace For a trial ru of SwigSet demo, which tests all the fuctioalities Total umber of calls to access$ fuctios - 46,638 Total user time sec Total system time sec Note: The user ad system times are comparable whe we ru the demo with origial swig.jar file. Although it is ot possible to ru the demo exactly the same way ad compare precisely

17 Eve Better Security Before A gives the secret to A$B Ð Check sigatures o A$B imply the sigatures o A Prevets situatio where a attacker tries to combie a siged versio of A with a modified ( ad usiged ) versio of A$B

18 Coclusio Desiged a ew implemetatio for ier classes to fix the security hole of the curret implemetatio Little additioal overhead Ð regardig both code size ad executio time Implemeted a byte code rewriter to icorporate the chages by trasformig the byte code Ca be implemeted i the compiler Ca exted this idea to have fried classes like C++

Soving Recurrence Relations

Soving Recurrence Relations Sovig Recurrece Relatios Part 1. Homogeeous liear 2d degree relatios with costat coefficiets. Cosider the recurrece relatio ( ) T () + at ( 1) + bt ( 2) = 0 This is called a homogeeous liear 2d degree

More information

Static revisited. Odds and ends. Static methods. Static methods 5/2/16. Some features of Java we haven t discussed

Static revisited. Odds and ends. Static methods. Static methods 5/2/16. Some features of Java we haven t discussed Odds ad eds Static revisited Some features of Java we have t discussed Static methods // Example: // Java's built i Math class public class Math { public static it abs(it a) { if (a >= 0) { retur a; else

More information

Domain 1: Designing a SQL Server Instance and a Database Solution

Domain 1: Designing a SQL Server Instance and a Database Solution Maual SQL Server 2008 Desig, Optimize ad Maitai (70-450) 1-800-418-6789 Domai 1: Desigig a SQL Server Istace ad a Database Solutio Desigig for CPU, Memory ad Storage Capacity Requiremets Whe desigig a

More information

Engineering Data Management

Engineering Data Management BaaERP 5.0c Maufacturig Egieerig Data Maagemet Module Procedure UP128A US Documetiformatio Documet Documet code : UP128A US Documet group : User Documetatio Documet title : Egieerig Data Maagemet Applicatio/Package

More information

(VCP-310) 1-800-418-6789

(VCP-310) 1-800-418-6789 Maual VMware Lesso 1: Uderstadig the VMware Product Lie I this lesso, you will first lear what virtualizatio is. Next, you ll explore the products offered by VMware that provide virtualizatio services.

More information

.04. This means $1000 is multiplied by 1.02 five times, once for each of the remaining sixmonth

.04. This means $1000 is multiplied by 1.02 five times, once for each of the remaining sixmonth Questio 1: What is a ordiary auity? Let s look at a ordiary auity that is certai ad simple. By this, we mea a auity over a fixed term whose paymet period matches the iterest coversio period. Additioally,

More information

Desktop Management. Desktop Management Tools

Desktop Management. Desktop Management Tools Desktop Maagemet 9 Desktop Maagemet Tools Mac OS X icludes three desktop maagemet tools that you might fid helpful to work more efficietly ad productively: u Stacks puts expadable folders i the Dock. Clickig

More information

Agenda. Outsourcing and Globalization in Software Development. Outsourcing. Outsourcing here to stay. Outsourcing Alternatives

Agenda. Outsourcing and Globalization in Software Development. Outsourcing. Outsourcing here to stay. Outsourcing Alternatives Outsourcig ad Globalizatio i Software Developmet Jacques Crocker UW CSE Alumi 2003 jc@cs.washigto.edu Ageda Itroductio The Outsourcig Pheomeo Leadig Offshore Projects Maagig Customers Offshore Developmet

More information

Modified Line Search Method for Global Optimization

Modified Line Search Method for Global Optimization Modified Lie Search Method for Global Optimizatio Cria Grosa ad Ajith Abraham Ceter of Excellece for Quatifiable Quality of Service Norwegia Uiversity of Sciece ad Techology Trodheim, Norway {cria, ajith}@q2s.tu.o

More information

Lesson 15 ANOVA (analysis of variance)

Lesson 15 ANOVA (analysis of variance) Outlie Variability -betwee group variability -withi group variability -total variability -F-ratio Computatio -sums of squares (betwee/withi/total -degrees of freedom (betwee/withi/total -mea square (betwee/withi

More information

Enhancing Oracle Business Intelligence with cubus EV How users of Oracle BI on Essbase cubes can benefit from cubus outperform EV Analytics (cubus EV)

Enhancing Oracle Business Intelligence with cubus EV How users of Oracle BI on Essbase cubes can benefit from cubus outperform EV Analytics (cubus EV) Ehacig Oracle Busiess Itelligece with cubus EV How users of Oracle BI o Essbase cubes ca beefit from cubus outperform EV Aalytics (cubus EV) CONTENT 01 cubus EV as a ehacemet to Oracle BI o Essbase 02

More information

Department of Computer Science, University of Otago

Department of Computer Science, University of Otago Departmet of Computer Sciece, Uiversity of Otago Techical Report OUCS-2006-09 Permutatios Cotaiig May Patters Authors: M.H. Albert Departmet of Computer Sciece, Uiversity of Otago Micah Colema, Rya Fly

More information

How to use what you OWN to reduce what you OWE

How to use what you OWN to reduce what you OWE How to use what you OWN to reduce what you OWE Maulife Oe A Overview Most Caadias maage their fiaces by doig two thigs: 1. Depositig their icome ad other short-term assets ito chequig ad savigs accouts.

More information

Tradigms of Astundithi and Toyota

Tradigms of Astundithi and Toyota Tradig the radomess - Desigig a optimal tradig strategy uder a drifted radom walk price model Yuao Wu Math 20 Project Paper Professor Zachary Hamaker Abstract: I this paper the author iteds to explore

More information

Domain 1: Configuring Domain Name System (DNS) for Active Directory

Domain 1: Configuring Domain Name System (DNS) for Active Directory Maual Widows Domai 1: Cofigurig Domai Name System (DNS) for Active Directory Cofigure zoes I Domai Name System (DNS), a DNS amespace ca be divided ito zoes. The zoes store ame iformatio about oe or more

More information

LECTURE 13: Cross-validation

LECTURE 13: Cross-validation LECTURE 3: Cross-validatio Resampli methods Cross Validatio Bootstrap Bias ad variace estimatio with the Bootstrap Three-way data partitioi Itroductio to Patter Aalysis Ricardo Gutierrez-Osua Texas A&M

More information

CHAPTER 11 Financial mathematics

CHAPTER 11 Financial mathematics CHAPTER 11 Fiacial mathematics I this chapter you will: Calculate iterest usig the simple iterest formula ( ) Use the simple iterest formula to calculate the pricipal (P) Use the simple iterest formula

More information

Finding the circle that best fits a set of points

Finding the circle that best fits a set of points Fidig the circle that best fits a set of poits L. MAISONOBE October 5 th 007 Cotets 1 Itroductio Solvig the problem.1 Priciples............................... Iitializatio.............................

More information

A Combined Continuous/Binary Genetic Algorithm for Microstrip Antenna Design

A Combined Continuous/Binary Genetic Algorithm for Microstrip Antenna Design A Combied Cotiuous/Biary Geetic Algorithm for Microstrip Atea Desig Rady L. Haupt The Pesylvaia State Uiversity Applied Research Laboratory P. O. Box 30 State College, PA 16804-0030 haupt@ieee.org Abstract:

More information

NEW HIGH PERFORMANCE COMPUTATIONAL METHODS FOR MORTGAGES AND ANNUITIES. Yuri Shestopaloff,

NEW HIGH PERFORMANCE COMPUTATIONAL METHODS FOR MORTGAGES AND ANNUITIES. Yuri Shestopaloff, NEW HIGH PERFORMNCE COMPUTTIONL METHODS FOR MORTGGES ND NNUITIES Yuri Shestopaloff, Geerally, mortgage ad auity equatios do ot have aalytical solutios for ukow iterest rate, which has to be foud usig umerical

More information

Document Control Solutions

Document Control Solutions Documet Cotrol Solutios State of the art software The beefits of Assai Assai Software Services provides leadig edge Documet Cotrol ad Maagemet System software for oil ad gas, egieerig ad costructio. AssaiDCMS

More information

Shared Memory with Caching

Shared Memory with Caching Vorlesug Recherarchitektur 2 Seite 164 Cachig i MIMD-Architectures ] MIMD-Architekture Programmiermodell Behadlug der Kommuikatioslatez Nachrichteorietiert globaler Adressraum Latez miimiere Latez verstecke

More information

I. Why is there a time value to money (TVM)?

I. Why is there a time value to money (TVM)? Itroductio to the Time Value of Moey Lecture Outlie I. Why is there the cocept of time value? II. Sigle cash flows over multiple periods III. Groups of cash flows IV. Warigs o doig time value calculatios

More information

Chapter 5 Unit 1. IET 350 Engineering Economics. Learning Objectives Chapter 5. Learning Objectives Unit 1. Annual Amount and Gradient Functions

Chapter 5 Unit 1. IET 350 Engineering Economics. Learning Objectives Chapter 5. Learning Objectives Unit 1. Annual Amount and Gradient Functions Chapter 5 Uit Aual Amout ad Gradiet Fuctios IET 350 Egieerig Ecoomics Learig Objectives Chapter 5 Upo completio of this chapter you should uderstad: Calculatig future values from aual amouts. Calculatig

More information

Automatic Tuning for FOREX Trading System Using Fuzzy Time Series

Automatic Tuning for FOREX Trading System Using Fuzzy Time Series utomatic Tuig for FOREX Tradig System Usig Fuzzy Time Series Kraimo Maeesilp ad Pitihate Soorasa bstract Efficiecy of the automatic currecy tradig system is time depedet due to usig fixed parameters which

More information

Mathematical goals. Starting points. Materials required. Time needed

Mathematical goals. Starting points. Materials required. Time needed Level A1 of challege: C A1 Mathematical goals Startig poits Materials required Time eeded Iterpretig algebraic expressios To help learers to: traslate betwee words, symbols, tables, ad area represetatios

More information

CHAPTER 3 THE TIME VALUE OF MONEY

CHAPTER 3 THE TIME VALUE OF MONEY CHAPTER 3 THE TIME VALUE OF MONEY OVERVIEW A dollar i the had today is worth more tha a dollar to be received i the future because, if you had it ow, you could ivest that dollar ad ear iterest. Of all

More information

Ekkehart Schlicht: Economic Surplus and Derived Demand

Ekkehart Schlicht: Economic Surplus and Derived Demand Ekkehart Schlicht: Ecoomic Surplus ad Derived Demad Muich Discussio Paper No. 2006-17 Departmet of Ecoomics Uiversity of Muich Volkswirtschaftliche Fakultät Ludwig-Maximilias-Uiversität Müche Olie at http://epub.ub.ui-mueche.de/940/

More information

DAME - Microsoft Excel add-in for solving multicriteria decision problems with scenarios Radomir Perzina 1, Jaroslav Ramik 2

DAME - Microsoft Excel add-in for solving multicriteria decision problems with scenarios Radomir Perzina 1, Jaroslav Ramik 2 Itroductio DAME - Microsoft Excel add-i for solvig multicriteria decisio problems with scearios Radomir Perzia, Jaroslav Ramik 2 Abstract. The mai goal of every ecoomic aget is to make a good decisio,

More information

Cooley-Tukey. Tukey FFT Algorithms. FFT Algorithms. Cooley

Cooley-Tukey. Tukey FFT Algorithms. FFT Algorithms. Cooley Cooley Cooley-Tuey Tuey FFT Algorithms FFT Algorithms Cosider a legth- sequece x[ with a -poit DFT X[ where Represet the idices ad as +, +, Cooley Cooley-Tuey Tuey FFT Algorithms FFT Algorithms Usig these

More information

Now here is the important step

Now here is the important step LINEST i Excel The Excel spreadsheet fuctio "liest" is a complete liear least squares curve fittig routie that produces ucertaity estimates for the fit values. There are two ways to access the "liest"

More information

optimise your investment in Microsoft technology. Microsoft Consulting Services from CIBER

optimise your investment in Microsoft technology. Microsoft Consulting Services from CIBER optimise your ivestmet i Microsoft techology. Microsoft Cosultig Services from Microsoft Cosultig Services from MICROSOFT CONSULTING SERVICES ca help with ay stage i the lifecycle of adoptig Microsoft

More information

Ranking Irregularities When Evaluating Alternatives by Using Some ELECTRE Methods

Ranking Irregularities When Evaluating Alternatives by Using Some ELECTRE Methods Please use the followig referece regardig this paper: Wag, X., ad E. Triataphyllou, Rakig Irregularities Whe Evaluatig Alteratives by Usig Some ELECTRE Methods, Omega, Vol. 36, No. 1, pp. 45-63, February

More information

Supply Chain Management

Supply Chain Management Supply Chai Maagemet LOA Uiversity October 9, 205 Distributio D Distributio Authorized to Departmet of Defese ad U.S. DoD Cotractors Oly Aim High Fly - Fight - Wi Who am I? Dr. William A Cuigham PhD Ecoomics

More information

Lecture 2: Karger s Min Cut Algorithm

Lecture 2: Karger s Min Cut Algorithm priceto uiv. F 3 cos 5: Advaced Algorithm Desig Lecture : Karger s Mi Cut Algorithm Lecturer: Sajeev Arora Scribe:Sajeev Today s topic is simple but gorgeous: Karger s mi cut algorithm ad its extesio.

More information

Output Analysis (2, Chapters 10 &11 Law)

Output Analysis (2, Chapters 10 &11 Law) B. Maddah ENMG 6 Simulatio 05/0/07 Output Aalysis (, Chapters 10 &11 Law) Comparig alterative system cofiguratio Sice the output of a simulatio is radom, the comparig differet systems via simulatio should

More information

A probabilistic proof of a binomial identity

A probabilistic proof of a binomial identity A probabilistic proof of a biomial idetity Joatho Peterso Abstract We give a elemetary probabilistic proof of a biomial idetity. The proof is obtaied by computig the probability of a certai evet i two

More information

Present Value Factor To bring one dollar in the future back to present, one uses the Present Value Factor (PVF): Concept 9: Present Value

Present Value Factor To bring one dollar in the future back to present, one uses the Present Value Factor (PVF): Concept 9: Present Value Cocept 9: Preset Value Is the value of a dollar received today the same as received a year from today? A dollar today is worth more tha a dollar tomorrow because of iflatio, opportuity cost, ad risk Brigig

More information

The Power of Free Branching in a General Model of Backtracking and Dynamic Programming Algorithms

The Power of Free Branching in a General Model of Backtracking and Dynamic Programming Algorithms The Power of Free Brachig i a Geeral Model of Backtrackig ad Dyamic Programmig Algorithms SASHKA DAVIS IDA/Ceter for Computig Scieces Bowie, MD sashka.davis@gmail.com RUSSELL IMPAGLIAZZO Dept. of Computer

More information

2-3 The Remainder and Factor Theorems

2-3 The Remainder and Factor Theorems - The Remaider ad Factor Theorems Factor each polyomial completely usig the give factor ad log divisio 1 x + x x 60; x + So, x + x x 60 = (x + )(x x 15) Factorig the quadratic expressio yields x + x x

More information

COMPARISON OF THE EFFICIENCY OF S-CONTROL CHART AND EWMA-S 2 CONTROL CHART FOR THE CHANGES IN A PROCESS

COMPARISON OF THE EFFICIENCY OF S-CONTROL CHART AND EWMA-S 2 CONTROL CHART FOR THE CHANGES IN A PROCESS COMPARISON OF THE EFFICIENCY OF S-CONTROL CHART AND EWMA-S CONTROL CHART FOR THE CHANGES IN A PROCESS Supraee Lisawadi Departmet of Mathematics ad Statistics, Faculty of Sciece ad Techoology, Thammasat

More information

Unicenter TCPaccess FTP Server

Unicenter TCPaccess FTP Server Uiceter TCPaccess FTP Server Release Summary r6.1 SP2 K02213-2E This documetatio ad related computer software program (hereiafter referred to as the Documetatio ) is for the ed user s iformatioal purposes

More information

Designing and Implementing a Family of Intrusion Detection Systems

Designing and Implementing a Family of Intrusion Detection Systems Desigig ad Implemetig a Family of Itrusio Detectio Systems Giovai Viga Fredrik Valeur Richard A. Kemmerer Reliable Software Group Departmet of Computer Sciece Uiversity of Califoria Sata Barbara [viga,fredrik,kemm]@cs.ucsb.edu

More information

Evaluation of Different Fitness Functions for the Evolutionary Testing of an Autonomous Parking System

Evaluation of Different Fitness Functions for the Evolutionary Testing of an Autonomous Parking System Evaluatio of Differet Fitess Fuctios for the Evolutioary Testig of a Autoomous Parkig System Joachim Wegeer 1, Oliver Bühler 2 1 DaimlerChrysler AG, Research ad Techology, Alt-Moabit 96 a, D-1559 Berli,

More information

IT Support. 020 8269 6878 n www.premierchoiceinternet.com n support@premierchoiceinternet.com. 30 Day FREE Trial. IT Support from 8p/user

IT Support. 020 8269 6878 n www.premierchoiceinternet.com n support@premierchoiceinternet.com. 30 Day FREE Trial. IT Support from 8p/user IT Support IT Support Premier Choice Iteret has bee providig reliable, proactive & affordable IT Support solutios to compaies based i Lodo ad the South East of Eglad sice 2002. Our goal is to provide our

More information

Bond Valuation I. What is a bond? Cash Flows of A Typical Bond. Bond Valuation. Coupon Rate and Current Yield. Cash Flows of A Typical Bond

Bond Valuation I. What is a bond? Cash Flows of A Typical Bond. Bond Valuation. Coupon Rate and Current Yield. Cash Flows of A Typical Bond What is a bod? Bod Valuatio I Bod is a I.O.U. Bod is a borrowig agreemet Bod issuers borrow moey from bod holders Bod is a fixed-icome security that typically pays periodic coupo paymets, ad a pricipal

More information

THE ARITHMETIC OF INTEGERS. - multiplication, exponentiation, division, addition, and subtraction

THE ARITHMETIC OF INTEGERS. - multiplication, exponentiation, division, addition, and subtraction THE ARITHMETIC OF INTEGERS - multiplicatio, expoetiatio, divisio, additio, ad subtractio What to do ad what ot to do. THE INTEGERS Recall that a iteger is oe of the whole umbers, which may be either positive,

More information

Quantitative Computer Architecture

Quantitative Computer Architecture Performace Measuremet ad Aalysis i Computer Quatitative Computer Measuremet Model Iovatio Proposed How to measure, aalyze, ad specify computer system performace or My computer is faster tha your computer!

More information

The analysis of the Cournot oligopoly model considering the subjective motive in the strategy selection

The analysis of the Cournot oligopoly model considering the subjective motive in the strategy selection The aalysis of the Courot oligopoly model cosiderig the subjective motive i the strategy selectio Shigehito Furuyama Teruhisa Nakai Departmet of Systems Maagemet Egieerig Faculty of Egieerig Kasai Uiversity

More information

Chapter 6: Variance, the law of large numbers and the Monte-Carlo method

Chapter 6: Variance, the law of large numbers and the Monte-Carlo method Chapter 6: Variace, the law of large umbers ad the Mote-Carlo method Expected value, variace, ad Chebyshev iequality. If X is a radom variable recall that the expected value of X, E[X] is the average value

More information

Domain 1: Identifying Cause of and Resolving Desktop Application Issues Identifying and Resolving New Software Installation Issues

Domain 1: Identifying Cause of and Resolving Desktop Application Issues Identifying and Resolving New Software Installation Issues Maual Widows 7 Eterprise Desktop Support Techicia (70-685) 1-800-418-6789 Domai 1: Idetifyig Cause of ad Resolvig Desktop Applicatio Issues Idetifyig ad Resolvig New Software Istallatio Issues This sectio

More information

Project Deliverables. CS 361, Lecture 28. Outline. Project Deliverables. Administrative. Project Comments

Project Deliverables. CS 361, Lecture 28. Outline. Project Deliverables. Administrative. Project Comments Project Deliverables CS 361, Lecture 28 Jared Saia Uiversity of New Mexico Each Group should tur i oe group project cosistig of: About 6-12 pages of text (ca be loger with appedix) 6-12 figures (please

More information

Traffic Modeling and Prediction using ARIMA/GARCH model

Traffic Modeling and Prediction using ARIMA/GARCH model Traffic Modelig ad Predictio usig ARIMA/GARCH model Preseted by Zhili Su, Bo Zhou, Uiversity of Surrey, UK COST 285 Symposium 8-9 September 2005 Muich, Germay Outlie Motivatio ARIMA/GARCH model Parameter

More information

C.Yaashuwanth Department of Electrical and Electronics Engineering, Anna University Chennai, Chennai 600 025, India..

C.Yaashuwanth Department of Electrical and Electronics Engineering, Anna University Chennai, Chennai 600 025, India.. (IJCSIS) Iteratioal Joural of Computer Sciece ad Iformatio Security, A New Schedulig Algorithms for Real Time Tasks C.Yaashuwath Departmet of Electrical ad Electroics Egieerig, Aa Uiversity Cheai, Cheai

More information

Simple Annuities Present Value.

Simple Annuities Present Value. Simple Auities Preset Value. OBJECTIVES (i) To uderstad the uderlyig priciple of a preset value auity. (ii) To use a CASIO CFX-9850GB PLUS to efficietly compute values associated with preset value auities.

More information

Infinite Sequences and Series

Infinite Sequences and Series CHAPTER 4 Ifiite Sequeces ad Series 4.1. Sequeces A sequece is a ifiite ordered list of umbers, for example the sequece of odd positive itegers: 1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25, 27, 29...

More information

INVESTMENT PERFORMANCE COUNCIL (IPC) Guidance Statement on Calculation Methodology

INVESTMENT PERFORMANCE COUNCIL (IPC) Guidance Statement on Calculation Methodology Adoptio Date: 4 March 2004 Effective Date: 1 Jue 2004 Retroactive Applicatio: No Public Commet Period: Aug Nov 2002 INVESTMENT PERFORMANCE COUNCIL (IPC) Preface Guidace Statemet o Calculatio Methodology

More information

5.4 Amortization. Question 1: How do you find the present value of an annuity? Question 2: How is a loan amortized?

5.4 Amortization. Question 1: How do you find the present value of an annuity? Question 2: How is a loan amortized? 5.4 Amortizatio Questio 1: How do you fid the preset value of a auity? Questio 2: How is a loa amortized? Questio 3: How do you make a amortizatio table? Oe of the most commo fiacial istrumets a perso

More information

FM4 CREDIT AND BORROWING

FM4 CREDIT AND BORROWING FM4 CREDIT AND BORROWING Whe you purchase big ticket items such as cars, boats, televisios ad the like, retailers ad fiacial istitutios have various terms ad coditios that are implemeted for the cosumer

More information

Sole trader financial statements

Sole trader financial statements 3 Sole trader fiacial statemets this chapter covers... I this chapter we look at preparig the year ed fiacial statemets of sole traders (that is, oe perso ruig their ow busiess). We preset the fiacial

More information

Systems Design Project: Indoor Location of Wireless Devices

Systems Design Project: Indoor Location of Wireless Devices Systems Desig Project: Idoor Locatio of Wireless Devices Prepared By: Bria Murphy Seior Systems Sciece ad Egieerig Washigto Uiversity i St. Louis Phoe: (805) 698-5295 Email: bcm1@cec.wustl.edu Supervised

More information

Evaluating Model for B2C E- commerce Enterprise Development Based on DEA

Evaluating Model for B2C E- commerce Enterprise Development Based on DEA , pp.180-184 http://dx.doi.org/10.14257/astl.2014.53.39 Evaluatig Model for B2C E- commerce Eterprise Developmet Based o DEA Weli Geg, Jig Ta Computer ad iformatio egieerig Istitute, Harbi Uiversity of

More information

SPC for Software Reliability: Imperfect Software Debugging Model

SPC for Software Reliability: Imperfect Software Debugging Model IJCSI Iteratioal Joural of Computer Sciece Issues, Vol. 8, Issue 3, o., May 0 ISS (Olie: 694-084 www.ijcsi.org 9 SPC for Software Reliability: Imperfect Software Debuggig Model Dr. Satya Prasad Ravi,.Supriya

More information

Research Article Sign Data Derivative Recovery

Research Article Sign Data Derivative Recovery Iteratioal Scholarly Research Network ISRN Applied Mathematics Volume 0, Article ID 63070, 7 pages doi:0.540/0/63070 Research Article Sig Data Derivative Recovery L. M. Housto, G. A. Glass, ad A. D. Dymikov

More information

Caché SQL Version F.12 Release Information

Caché SQL Version F.12 Release Information Caché SQL Versio F.12 Release Iformatio Versio: Caché SQL F.12 Date: October 22, 1997 Part Number IS-SQL-0-F.12A-CP-R Caché SQL F.12 Release Iformatio Copyright IterSystems Corporatio 1997 All rights reserved

More information

Developing the Application of 360 Degree Performance Appraisal through Logic Model

Developing the Application of 360 Degree Performance Appraisal through Logic Model Iteratioal Joural of Busiess ad Social Sciece Vol. 3 No. 22 [Special Issue November 2012] Developig the Applicatio of 360 Degree Performace Appraisal through Logic Model Ozge OZ Huma Resources Specialist

More information

Configuring Additional Active Directory Server Roles

Configuring Additional Active Directory Server Roles Maual Upgradig your MCSE o Server 2003 to Server 2008 (70-649) 1-800-418-6789 Cofigurig Additioal Active Directory Server Roles Active Directory Lightweight Directory Services Backgroud ad Cofiguratio

More information

Composable Tools For Network Discovery and Security Analysis

Composable Tools For Network Discovery and Security Analysis Composable Tools For Network Discovery ad Security Aalysis Giovai Viga Fredrik Valeur Jigyu Zhou Richard A. Kemmerer Reliable Software Group Departmet of Computer Sciece Uiversity of Califoria Sata Barbara

More information

Authentication - Access Control Default Security Active Directory Trusted Authentication Guest User or Anonymous (un-authenticated) Logging Out

Authentication - Access Control Default Security Active Directory Trusted Authentication Guest User or Anonymous (un-authenticated) Logging Out FME Server Security Table of Cotets FME Server Autheticatio - Access Cotrol Default Security Active Directory Trusted Autheticatio Guest User or Aoymous (u-autheticated) Loggig Out Authorizatio - Roles

More information

Routine for 8-Bit Binary to BCD Conversion

Routine for 8-Bit Binary to BCD Conversion Algorithm - Fast ad Compact Usiged Biary to BCD Coversio Applicatio Note Abstract AN2338 Author: Eugee Miyushkovich, Ryshtu Adrij Associated Project: Yes Associated Part Family: CY8C24x23A, CY8C24x94,

More information

ODBC. Getting Started With Sage Timberline Office ODBC

ODBC. Getting Started With Sage Timberline Office ODBC ODBC Gettig Started With Sage Timberlie Office ODBC NOTICE This documet ad the Sage Timberlie Office software may be used oly i accordace with the accompayig Sage Timberlie Office Ed User Licese Agreemet.

More information

Taking DCOP to the Real World: Efficient Complete Solutions for Distributed Multi-Event Scheduling

Taking DCOP to the Real World: Efficient Complete Solutions for Distributed Multi-Event Scheduling Taig DCOP to the Real World: Efficiet Complete Solutios for Distributed Multi-Evet Schedulig Rajiv T. Maheswara, Milid Tambe, Emma Bowrig, Joatha P. Pearce, ad Pradeep araatham Uiversity of Souther Califoria

More information

To c o m p e t e in t o d a y s r e t a i l e n v i r o n m e n t, y o u n e e d a s i n g l e,

To c o m p e t e in t o d a y s r e t a i l e n v i r o n m e n t, y o u n e e d a s i n g l e, Busiess Itelligece Software for Retail To c o m p e t e i t o d a y s r e t a i l e v i r o m e t, y o u e e d a s i g l e, comprehesive view of your busiess. You have to tur the decisio-makig of your

More information

Lesson 17 Pearson s Correlation Coefficient

Lesson 17 Pearson s Correlation Coefficient Outlie Measures of Relatioships Pearso s Correlatio Coefficiet (r) -types of data -scatter plots -measure of directio -measure of stregth Computatio -covariatio of X ad Y -uique variatio i X ad Y -measurig

More information

AP Calculus AB 2006 Scoring Guidelines Form B

AP Calculus AB 2006 Scoring Guidelines Form B AP Calculus AB 6 Scorig Guidelies Form B The College Board: Coectig Studets to College Success The College Board is a ot-for-profit membership associatio whose missio is to coect studets to college success

More information

e-trader user guide Introduction

e-trader user guide Introduction User guide e-trader user guide Itroductio At UK Geeral our aim is to provide you with the best possible propositio for you ad your customers. We believe i offerig brokers a choice of how they trade with

More information

A Balanced Scorecard

A Balanced Scorecard A Balaced Scorecard with VISION A Visio Iteratioal White Paper Visio Iteratioal A/S Aarhusgade 88, DK-2100 Copehage, Demark Phoe +45 35430086 Fax +45 35434646 www.balaced-scorecard.com 1 1. Itroductio

More information

3. Greatest Common Divisor - Least Common Multiple

3. Greatest Common Divisor - Least Common Multiple 3 Greatest Commo Divisor - Least Commo Multiple Defiitio 31: The greatest commo divisor of two atural umbers a ad b is the largest atural umber c which divides both a ad b We deote the greatest commo gcd

More information

Rainbow options. A rainbow is an option on a basket that pays in its most common form, a nonequally

Rainbow options. A rainbow is an option on a basket that pays in its most common form, a nonequally Raibow optios INRODUCION A raibow is a optio o a basket that pays i its most commo form, a oequally weighted average of the assets of the basket accordig to their performace. he umber of assets is called

More information

Digital Enterprise Unit. White Paper. Web Analytics Measurement for Responsive Websites

Digital Enterprise Unit. White Paper. Web Analytics Measurement for Responsive Websites Digital Eterprise Uit White Paper Web Aalytics Measuremet for Resposive Websites About the Authors Vishal Machewad Vishal Machewad has over 13 years of experiece i sales ad marketig, havig worked as a

More information

Time Value of Money, NPV and IRR equation solving with the TI-86

Time Value of Money, NPV and IRR equation solving with the TI-86 Time Value of Moey NPV ad IRR Equatio Solvig with the TI-86 (may work with TI-85) (similar process works with TI-83, TI-83 Plus ad may work with TI-82) Time Value of Moey, NPV ad IRR equatio solvig with

More information

Chatpun Khamyat Department of Industrial Engineering, Kasetsart University, Bangkok, Thailand ocpky@hotmail.com

Chatpun Khamyat Department of Industrial Engineering, Kasetsart University, Bangkok, Thailand ocpky@hotmail.com SOLVING THE OIL DELIVERY TRUCKS ROUTING PROBLEM WITH MODIFY MULTI-TRAVELING SALESMAN PROBLEM APPROACH CASE STUDY: THE SME'S OIL LOGISTIC COMPANY IN BANGKOK THAILAND Chatpu Khamyat Departmet of Idustrial

More information

Best of security and convenience

Best of security and convenience Get More with Additioal Cardholders. Importat iformatio. Add a co-applicat or authorized user to your accout ad you ca take advatage of the followig beefits: RBC Royal Bak Visa Customer Service Cosolidate

More information

5 Boolean Decision Trees (February 11)

5 Boolean Decision Trees (February 11) 5 Boolea Decisio Trees (February 11) 5.1 Graph Coectivity Suppose we are give a udirected graph G, represeted as a boolea adjacecy matrix = (a ij ), where a ij = 1 if ad oly if vertices i ad j are coected

More information

Handling. Collection Calls

Handling. Collection Calls Hadlig the Collectio Calls We do everythig we ca to stop collectio calls; however, i the early part of our represetatio, you ca expect some of these calls to cotiue. We uderstad that the first few moths

More information

Bio-Plex Manager Software

Bio-Plex Manager Software Multiplex Suspesio Array Bio-Plex Maager Software Extract Kowledge Faster Move Your Research Forward Bio-Rad cotiues to iovate where it matters most. With Bio-Plex Maager 5.0 software, we offer valuable

More information

where: T = number of years of cash flow in investment's life n = the year in which the cash flow X n i = IRR = the internal rate of return

where: T = number of years of cash flow in investment's life n = the year in which the cash flow X n i = IRR = the internal rate of return EVALUATING ALTERNATIVE CAPITAL INVESTMENT PROGRAMS By Ke D. Duft, Extesio Ecoomist I the March 98 issue of this publicatio we reviewed the procedure by which a capital ivestmet project was assessed. The

More information

I apply to subscribe for a Stocks & Shares ISA for the tax year 20 /20 and each subsequent year until further notice.

I apply to subscribe for a Stocks & Shares ISA for the tax year 20 /20 and each subsequent year until further notice. IFSL Brooks Macdoald Fud Stocks & Shares ISA Trasfer Applicatio Form IFSL Brooks Macdoald Fud Stocks & Shares ISA Trasfer Applicatio Form Please complete usig BLOCK CAPITALS ad retur the completed form

More information

A Flexible Web-Based Publication Database

A Flexible Web-Based Publication Database A Flexible Web-Based Publicatio Database Karl Riedlig ad Siegfried Selberherr 2 Istitute of Sesor ad Actuator Systems 2 Istitute for Microelectroics Techische Uiversität Wie Gusshausstrasse 27-29 A-040

More information

Estimating Probability Distributions by Observing Betting Practices

Estimating Probability Distributions by Observing Betting Practices 5th Iteratioal Symposium o Imprecise Probability: Theories ad Applicatios, Prague, Czech Republic, 007 Estimatig Probability Distributios by Observig Bettig Practices Dr C Lych Natioal Uiversity of Irelad,

More information

Supply Chain Management

Supply Chain Management Supply Chai Maagemet Douglas M. Lambert, Ph.D. The Raymod E. Maso Chaired Professor ad Director, The Global Supply Chai Forum Supply Chai Maagemet is NOT a New Name for Logistics The Begiig of Wisdom Is

More information

Sequences and Series Using the TI-89 Calculator

Sequences and Series Using the TI-89 Calculator RIT Calculator Site Sequeces ad Series Usig the TI-89 Calculator Norecursively Defied Sequeces A orecursively defied sequece is oe i which the formula for the terms of the sequece is give explicitly. For

More information

Chapter 10 Computer Design Basics

Chapter 10 Computer Design Basics Logic ad Computer Desig Fudametals Chapter 10 Computer Desig Basics Part 1 Datapaths Charles Kime & Thomas Kamiski 2004 Pearso Educatio, Ic. Terms of Use (Hyperliks are active i View Show mode) Overview

More information

Parameter estimation for nonlinear models: Numerical approaches to solving the inverse problem. Lecture 11 04/01/2008. Sven Zenker

Parameter estimation for nonlinear models: Numerical approaches to solving the inverse problem. Lecture 11 04/01/2008. Sven Zenker Parameter estimatio for oliear models: Numerical approaches to solvig the iverse problem Lecture 11 04/01/2008 Sve Zeker Review: Trasformatio of radom variables Cosider probability distributio of a radom

More information

RUT - development handbook 1.3 The Spiral Model v 4.0

RUT - development handbook 1.3 The Spiral Model v 4.0 2007-01-16 LiTH RUT - developmet hadbook 1.3 The Spiral Model v 4.0 Fredrik Herbertsso ABSTRACT The idea behid the spiral model is to do system developmet icremetally while usig aother developmet model,

More information

Optimize your Network. In the Courier, Express and Parcel market ADDING CREDIBILITY

Optimize your Network. In the Courier, Express and Parcel market ADDING CREDIBILITY Optimize your Network I the Courier, Express ad Parcel market ADDING CREDIBILITY Meetig today s challeges ad tomorrow s demads Aswers to your key etwork challeges ORTEC kows the highly competitive Courier,

More information

Chair for Network Architectures and Services Institute of Informatics TU München Prof. Carle. Network Security. Chapter 2 Basics

Chair for Network Architectures and Services Institute of Informatics TU München Prof. Carle. Network Security. Chapter 2 Basics Chair for Network Architectures ad Services Istitute of Iformatics TU Müche Prof. Carle Network Security Chapter 2 Basics 2.4 Radom Number Geeratio for Cryptographic Protocols Motivatio It is crucial to

More information

CDs Bought at a Bank verses CD s Bought from a Brokerage. Floyd Vest

CDs Bought at a Bank verses CD s Bought from a Brokerage. Floyd Vest CDs Bought at a Bak verses CD s Bought from a Brokerage Floyd Vest CDs bought at a bak. CD stads for Certificate of Deposit with the CD origiatig i a FDIC isured bak so that the CD is isured by the Uited

More information

SECTION 1.5 : SUMMATION NOTATION + WORK WITH SEQUENCES

SECTION 1.5 : SUMMATION NOTATION + WORK WITH SEQUENCES SECTION 1.5 : SUMMATION NOTATION + WORK WITH SEQUENCES Read Sectio 1.5 (pages 5 9) Overview I Sectio 1.5 we lear to work with summatio otatio ad formulas. We will also itroduce a brief overview of sequeces,

More information

Design and Implementation of a Publication Database for the Vienna University of Technology

Design and Implementation of a Publication Database for the Vienna University of Technology Desig ad Implemetatio of a Publicatio Database for the Viea Uiversity of Techology Karl Riedlig Istitute of Idustrial Electroics ad Material Sciece, TU Wie, A-040 Viea karl.riedlig@tuwie.ac.at Abstract:

More information