...Jeg plejede at more mig over ”hykleriske” og snæversynede udtalelser, som man hørte i medierne og lign. angående legalisering af hash, og hvor ganske farligt det er. Jeg plejede at tænke, at selvom hash ikke ligefrem er lige så sundt, som Fru. Hansens hjemmelavet grøntsagssuppe, så var det jo altså ikke mere skadeligt end andre legale rusmidler, herunder vores gode ven alkohol. Jeg hørte ofte forskere udtale, at cannabis slet ikke er så slemt, og at cannabisolie også kan være kureende over for mange sygdomme, og på en eller anden måde, kom jeg til en konklusion om, at hash var da egentligt ikke så slemt? Overlæge Henrik Rindom påpeger faktisk, at hvis hash nu skulle gå hen og blive legaliseret, så vil det reelt ikke øget forbruget, i det det alligevel er så hyppigt brugt i Danmark. Som de fleste af os ved, så er det ikke super svært, at få fat på. Men er det nu rigtigt? Bliver det legaliseret bliver man jo ikke 'stemplet' som en kriminel mere, og det kan muligvis øge forbruget. Lige pludselig så legalisering af hash lidt mere farligt ud. Med farlig mener jeg altså, at konkurrencen på det sorte marked vil dø ud, og en legalisering vil betyde at hash vil blive en integreret del af vores kultur og hverdag. Mere end hvad det allerede er i forvejen. Hvilket også er noget vi bør tage som et forbehold. Som Peter Skaarup mener i hans ugeblad, er hash et fundament for brugen af hårdere stoffer. Så havde jeg taget fejl i første omgang? Men der er altså også mange argumenter for...
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...in a dictionary as a password” (Rouse, 2005). In addition Cain and Abel has the ability to use Cryptanalysis attacks to break passwords, it is considered the fastest [time memory trade off method], being faster than brute force attacks while also not needing as much memory as dictionary attacks (Gates, 2006). During the lab assignment I found that Dictionary attack with NTLM was the most effective. It allows the user to select more search options like reverse, lowercase and uppercase…etc. It was the fastest method in cracking the passwords. According to Cain and Able online user manual LM hash is the weakest between the two hashes. NT LAN Manager was put into place to tackle the security issues and weaknesses missing from LM encryption. 2. Compare and contrast the results from the two methods used to crack the accounts for the three passwords each encrypted by the two hash algorithms. What conclusions can you make...
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... Bubble Sort 20 Selection sort 21 Section 4: Searching 22 Array 22 Linked Lists 23 Section 5: Recursion 30 References 33 Executive Summary Phase 1 A list is a collection of items in which the items have a position (Weiss, 2010). A linked list allows data to be input or removed easily because each of the data items in the list is connected to its neighbor by a pointer that can be quickly and easily modified to accommodate new or removed items (CTU M.U.S.E. 2014). The Phase 1 portion of this document will be demonstrating the implementation of Stacks and Queues. Phase 2 Hash tables can be viewed as an array of lists and are used to speed up a search for data by creating a situation that does not require the search to start at the beginning and go through every item. The identifying value is the key and the associated record is the data, thus a hash table is a collection of (key, value) pairs. Phase 3 In order to efficiently use a database, the data must be stored in some sort of order. There are a number of different sorting algorithms; a programmer would choose which one to use depending on the amount and type of data being sorted. Insertion sort, Bubble sort, and Selection sort are described with examples. Phase 4 A binary tree, is a node-based data structure where each node has a comparable key (and an associated value) and satisfies the restriction that the key in any node is larger than the keys in all nodes in that node's left subtree...
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...All DBMS definition files have the same structure made up of a number of categories, each of which may contain items or other categories. The items, and their values are different for each DBMS. Each item is present only if it is relevant to the DBMS. Each value is a SQL statement or other parameter to define how to model, generate and reverse engineer for the DBMS. Each DBMS file has the following structure: * General - contains general information about the database, without any categories (see General Category). All items defined in the General category apply to all database objects. * Script - used for generation and reverse engineering. Contains the following sub-categories: * SQL - contains the following sub-categories, each of which contains items whose values define general syntax for the database: * Syntax - general parameters for SQL syntax (see Syntax Category) * Format - parameters for allowed characters (see Format Category) * File - header, footer and usage text items used during generation (see File Category) * Keywords - the list of SQL reserved words and functions (see Keywords Category) * Objects - contains commands to create, delete or modify all the objects in the database. Also includes commands that define object behavior, defaults, necessary SQL queries, reverse engineering options, and so on (see Script/Objects Category). * Data Type - contains the list of valid data types for the specified...
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...aAPPLICATION CONTROLS Application controls are programmed procedures designed to deal with potential exposures that threaten specific applications, such as payroll, purchases, and cash disbursements systems. Application controls fall into three broad categories: input controls, processing controls, and output controls. Input Controls Input controls at this stage are designed to ensure that these transactions are valid, accurate, and complete. Data input procedures can be either source document-triggered (batch) or direct input (real time). Source document input requires human involvement and is prone to clerical errors. Some types of errors that are entered on the source documents cannot be detected and corrected during the data input stage. Dealing with these problems may require tracing the transaction back to its source (such as contacting the customer) to correct the mistake. Direct input, on the other hand, employs real-time editing techniques to identify and correct errors immediately, thus significantly reducing the number of errors that enter the system. Classes of Input Control a. Source Document Controls. Careful control must be exercised over physical source documents in systems that use them to initiate transactions. Source document fraud can be used to remove assets from the organization. In the absence of other compensating controls to detect this type of fraud, the system would create an account payable and subsequently write a check in payment...
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...structure of a file (especially a data file) defined in terms of its components and how they are mapped onto backing store. For example, if we want to retrieve student records in alphabetical order of name, sorting the file by student name is a good file organization. However, if we want to retrieve all students whose marks is in a certain range, a file ordered by student name would not be a good file organization. Some file organizations are efficient for bulk loading data into the database but inefficient for retrieve and other activities. Types of file organization In order to make effective selection of file organizations and indexes, here we present in details different types of file Organization. These are: • Heap File Organization • Hash File Organization • Indexed Sequential Access Methods...
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...Cryptanalysis (via “rainbow tables”). The sniffer (captures and analyzes network traffic) in this version can also analyze encrypted protocols such as SSH-1 and HTTPS, and contains filters to capture credentials from a wide range of authentication mechanisms, including Kerberos. In addition to this, Cain and Abel can used to recover wireless passwords, uncover cached passwords, and analyze routing protocols. 2. Algorithms There are two authentication protocols used to store passwords depending on which version of Windows is being run. The two are LM and NTLM. * LM The LM, sometimes referred to as LanMan or the LAN Manager hash, is the primary authentication protocol that Microsoft employed in Windows versions prior to Windows NT; it is used to store user passwords in an encrypted format on the disk. In order to transform a user's password to the LM hash, the password is first converted to all uppercase letters. If the password is greater than 14 bytes (14 characters) any character after the 14th is truncated; likewise, if the password is less than 14 bytes, it is null-padded to...
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...Notes on DBMS Internals Neil Conway neilc@samurai.com November 10, 2003 Preamble These notes were originally written for my own use while taking CISC-432, a course in DBMS design and implementation at Queen’s University. The textbook used by that class is Database Management Systems, 3rd Edition by Raghu Ramakrishnan and Johannes Gehkre; some of the material below may be specific to that text. This document is provided in the hope that it is useful, but I can’t provide any assurance that any information it contains is in any way accurate or complete. Corrections or additions are welcome. Distribution Terms: This document is released into the public domain. Query Evaluation External Sorting • A DBMS frequently needs to sort data (e.g. for a merge-join, ORDER BY, GROUP BY, etc.) that exceeds the amount of main memory available. In order to do this, an external sort algorithm is used. • 2-Way External Merge Sort: – In the first pass, each page of the input relation is read into memory, sorted, and written out to disk. This creates N runs of 1 page each. – In each successive pass, each run is read into memory and merged with another run, then written out to disk. Since the number of runs is halved with every pass, this requires log2 N passes. Since an additional initial pass is required and each pass requires 2N I/Os, the total cost is: 2N( log2 N + 1) – Thus, we can see that the number of passes we need to make is critical to the overall performance of the sort (since in...
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...secret society. The uniforms you see when you walk in waffle house are very old style diner like. From the blue striped shirt to the black scarf around the neck. The uniforms at waffle house say happy to be me. Big bright smiley face yellow name tags. Ladies with the black bandana around there hair says old style service with a smile. They certainly have a unique style of their very own. Even the language inside the waffle house is unique and fun. From the time you step in the door with a great big smile they all yell “Hey welcome to Waffle House”. The best part is when you place your order. They could easily say put onions, cheese and ham on the hash browns but that wouldn’t be unique or fun would it? Instead when you ask for these items you will hear scattered, smothered, covered and chunked. Instead of make the round hash browns they yell “one in the ring”. There are many things that after visiting my waffle house for a while you notice as norms. In the morning here there are always a group of seniors drinking there coffee and reading the paper. During lunch, you have your in and out quick lunch crowd. You also will encounter your night owls predominately younger crowd that come in after 2 am to soak up alcohol. If you come into my waffle house it is normal or understood that there is a pretty big jukebox and it is going to be playing the waffle house favorites twenty...
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...601 in both equations A = 0.5(601)2 = 0.5(361201) = 180600.5 B = 300(601) = 180300 Thus B is the most efficient 2. A long, long time ago, when I was in graduate school, I wrote a program to solve a difficult problem. The program had a time complexity of 2n(yeah, no kidding!). On input of size 50, my program finished in about an hour. How long would it have taken me to run my program on input of size 100? If input of 50 takes 1hr in a time complexity of 2n It also takes 1 hour to execute and input of 100 3. Write an All-Pairs algorithm that is given a list of numbers and a target and outputs each pair of values that sum to the target. The two algorithms can work Algorithm 1: 1) Initialize Binary Hash Map M[] = {0, 0, …} 2) Do following for each element A[i] in A[] (a)If M[x - A[i]] is set then print the pair (A[i], x – A[i]) (b)Set M[A[i]] Algorithm 2: 1) Sort the array in non-decreasing order. 2) Initialize two index variables to find the candidate elements in the sorted array. (a) Initialize first to the leftmost index: l = 0 (b) Initialize second the rightmost index: r = ar_size-1 3) Loop while l < r. (a) If (A[l] + A[r] == sum) then return 1 (b) Else if( A[l] + A[r] < sum ) then l++ (c) Else r-- 4) No candidates in whole array - return...
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...About Cognizant Cognizant (NASDAQ: CTSH) is a leading provider of information technology, consulting and business Process outsourcing services. Cognizant’s single-minded passion is to dedicate our global technology and Innovation know-how, our industry expertise and worldwide resources to working together with clients to make their business stronger. With more than 40 global delivery centers and approximately 61,700 employees as of December 31, 2008, we combine onsite/offshore model infused by a distinct culture of customer satisfaction. A member of the NASDAQ-100 Index and S&P 500 Index, Cognizant is a Forbes Global 2000 company and a member of the Fortune 1000 and is ranked among the top information technology companies in Business Week’s Hot Growth and Top 50 Performers listings Start Today For more information on how to drive your business results with Cognizant, contact us at inquiry@cognizant.com or visit our website at: www.cognizant.com. World Headquarters 500 Frank W. Burr Blvd. Teaneck, NJ 07666 USA Phone: +1 201 801 0233 Fax: +1 201 801 0243 Toll Free: +1 888 937 3277 Email: inquiry@cognizant.com European Headquarters Haymarket House 28-29 Haymarket London SW1Y 4SP UK Phone: +44 (0) 20 7321 4888 Fax: +44 (0) 20 7321 4890 Email: infouk@cognizant.com India Operations Headquarters #5/535, Old Mahabalipuram Road Okkiyam Pettai, Thoraipakkam Chennai, 600 096 India Phone: +91 (0) 44 4209 6000 Fax: +91 (0) 44 4209 6060 Email: inquiryindia@cognizant.com ...
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...1.2. Representation of integer has no size restriction • The important factor affecting the running time is normally size of the input. • Normally the built in data type has a fixed size, to enter and to store the larger data. • The Linked List can be used to store the integer without size restriction, which stores each digit in nodes. • The data can also be reused. Addition: A= 456 Represented by 6 → 5 → 4 in linked list B= 094 Represented by 4 → 9 → 0 in linked list The Resultant is C = 550 Represented by 0 → 5 → 5 in linked list. Multiplication: A= 123 * B= 456 A= Represented by 3 → 2 → 1 in linked list. B= Represented by 6 → 5 → 4 in linked list. STEP 1: 123 * 6 = 8 → 3 → 7 in linked list. STEP 2: 123 * 50= 0 → 5 → 1 → 6 in linked list. STEP 3: ADD STEP 1 AND STEP 2 8 → 8 → 8 → 6 in linked list. STEP 4: 123 * 400= 0 → 0 → 2 → 9 → 4 in linked list. STEP 5: ADD STEP 3 AND STEP 4 8 → 8 → 0 → 6 → 5 in linked list. Exponentiation: The initial step is to arrange in decreasing order of exponents and then perform the action. The other method is by using Θ(log n) time algorithm based on binary representation. 1.5. Representation of one’s and two’s complement 1’s complement: + 4= 0100 - 4= 1011 (taking 1’s complement of +4 is -4 (i.e.) inverting the bit). So, 1’s complement is used to represent both positive and negative integers. 2’s complement: Converting the value to 1’s complement and then adding 1 to that complement. ...
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...CS 143 Final Exam Notes Disks A typical disk ▪ Platter diameter: 1-5 in ▪ Cylinders: 100 – 2000 ▪ Platters: 1 – 20 ▪ Sectors per track: 200 – 500 ▪ Sector size: 512 – 50K ▪ Overall capacity: 1G – 200GB ❖ ( sectors / track ) ( ( sector size ) ( ( cylinders ) ( ( 2 ( number of platters ) Disk access time ▪ Access time = (seek time) + (rotational delay) + (transfer time) ❖ Seek time – moving the head to the right track ❖ Rotational delay – wait until the right sector comes below the head ❖ Transfer time – read/transfer the data Seek time ▪ Time to move a disk head between tracks ❖ Track to track ~ 1ms ❖ Average ~ 10 ms ❖ Full stroke ~ 20 ms Rotational delay ▪ Typical disk: ❖ 3600 rpm – 15000 rpm ❖ Average rotational delay ➢ 1/2 * 3600 rpm / 60 sec = 60 rps; average delay = 1/120 sec Transfer rate ▪ Burst rate ❖ (# of bytes per track) / (time to rotate once) ▪ Sustained rate ❖ Average rate that it takes to transfer the data ❖ (# of bytes per track) / (time to rotate once + track-to-track seek time) Abstraction by OS ▪ Sequential blocks – No need to worry about head, cylinder, sector ▪ Access to random blocks – Random I/O ▪ Access to consecutive blocks – Sequential I/O Random I/O vs. Sequential I/O ▪ Assume ❖ 10ms seek time ❖ 5ms rotational delay ❖ 10MB/s transfer rate ❖ Access time = (seek time) + (rotational delay) + (transfer...
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...TeamLRN Robert Lafore Teach Yourself Data Structures and Algorithms in 24 Hours 201 West 103rd St., Indianapolis, Indiana, 46290 USA Sams Teach Yourself Data Structures and Algorithms in 24 Hours Copyright © 1999 by Sams Publishing All rights reserved. No part of this book shall be reproduced, stored in a retrieval system, or transmitted by any means, electronic, mechanical, photocopying, recording, or otherwise, without written permission from the publisher. No patent liability is assumed with respect to the use of the information contained herein. Although every precaution has been taken in the preparation of this book, the publisher and author assume no responsibility for errors or omissions. Neither is any liability assumed for damages resulting from the use of the information contained herein. International Standard Book Number: 0-672-31633-1 Library of Congress Catalog Card Number: 98-83221 Printed in the United States of America First Printing: May 1999 01 00 99 4 3 2 1 EXECUTIVE EDITOR Brian Gill DEVELOPMENT EDITOR Jeff Durham MANAGING EDITOR Jodi Jensen PROJECT EDITOR Tonya Simpson COPY EDITOR Mike Henry INDEXER Larry Sweazy PROOFREADERS Mona Brown Jill Mazurczyk TECHNICAL EDITOR Richard Wright Trademarks All terms mentioned in this book that are known to be trademarks or service marks have been appropriately capitalized. Sams Publishing cannot attest to the accuracy of this information. Use of a term in this...
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...database for that person's data. A database search mechanism would first have to start looking character-by-character across the name for matches until it found the match (or ruled the other entries out). But if each of the names were hashed, it might be possible (depending on the number of names in the database) to generate a unique four-digit key for each name. For example: 7864 Abernathy, Sara 9802 Epperdingle, Roscoe 1990 Moore, Wilfred 8822 Smith, David (and so forth) A search for any name would first consist of computing the hash value (using the same hash function used to store the item) and then comparing for a match using that value. It would, in general, be much faster to find a match across four digits, each having only 10 possibilities, than across an unpredictable value length where each character had 26 possibilities. The hashing algorithm is called the hash function-- probably the term is derived from the idea that the resulting hash value can be thought of as a "mixed up" version of the represented value. In addition to faster data retrieval, hashing is also...
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