This presentation demonstrates the historical and mathematical background to the brilliant work done by Polish and British cryptology experts before and during World War II.
The solutions provided by Marian Rejewski, Alan Turing and their co-workers had a major impact on the outcome of the war.
The purpose of making this presentation is to explain Kruskal's Algorithm in a simple and attractive way. However, the content of this presentation is taken from more than one resources and merged at one place for the better understanding of students. It also contains an example which will definitely help students to understand it more quickly.
The purpose of making this presentation is to explain Kruskal's Algorithm in a simple and attractive way. However, the content of this presentation is taken from more than one resources and merged at one place for the better understanding of students. It also contains an example which will definitely help students to understand it more quickly.
Extracting Hierarchies with Recursive Tree Traversal Using FMESafe Software
The Problem:
You have been given a really large (~ 400MB) kmz file to convert to shapefile(s) to be loaded into ArcGIS. The kmz source has been aggregated with the google earth “My Places” tools. This kmz file has ~4000 folders and ~400 kml documents with a very deep document/folder hierarchy; over 7 levels deep in some places.
The folder hierarchy contains important semantic information that needs to be saved as an attribute to be used for folder creation or feature classification.
Many of the kml balloons contain raw html tables of name value pairs of important semantic information that need to be saved as attribute values inside of a feature classes.
The end goal is to capture the geometry into GIS feature classes while retaining semantic information.
The Solution:
Use FME with the kmz reader and SQL Recursive functions to build the tree hierarchy.
Use FME custom transformer to extract name/value pairs from html tables.
Use FME data set and feature type fanout to create dynamic tables and attributes.
This presentation will demonstrate this solution and show how to set up a SQL WITH RECUSIVE query with fme as well as how to capture attributes from the kml balloons.
FellowBuddy.com is an innovative platform that brings students together to share notes, exam papers, study guides, project reports and presentation for upcoming exams.
We connect Students who have an understanding of course material with Students who need help.
Benefits:-
# Students can catch up on notes they missed because of an absence.
# Underachievers can find peer developed notes that break down lecture and study material in a way that they can understand
# Students can earn better grades, save time and study effectively
Our Vision & Mission – Simplifying Students Life
Our Belief – “The great breakthrough in your life comes when you realize it, that you can learn anything you need to learn; to accomplish any goal that you have set for yourself. This means there are no limits on what you can be, have or do.”
Like Us - https://www.facebook.com/FellowBuddycom
This is the second lecture in the CS 6212 class. Covers asymptotic notation and data structures. Also outlines the coming lectures wherein we will study the various algorithm design techniques.
Extracting Hierarchies with Recursive Tree Traversal Using FMESafe Software
The Problem:
You have been given a really large (~ 400MB) kmz file to convert to shapefile(s) to be loaded into ArcGIS. The kmz source has been aggregated with the google earth “My Places” tools. This kmz file has ~4000 folders and ~400 kml documents with a very deep document/folder hierarchy; over 7 levels deep in some places.
The folder hierarchy contains important semantic information that needs to be saved as an attribute to be used for folder creation or feature classification.
Many of the kml balloons contain raw html tables of name value pairs of important semantic information that need to be saved as attribute values inside of a feature classes.
The end goal is to capture the geometry into GIS feature classes while retaining semantic information.
The Solution:
Use FME with the kmz reader and SQL Recursive functions to build the tree hierarchy.
Use FME custom transformer to extract name/value pairs from html tables.
Use FME data set and feature type fanout to create dynamic tables and attributes.
This presentation will demonstrate this solution and show how to set up a SQL WITH RECUSIVE query with fme as well as how to capture attributes from the kml balloons.
FellowBuddy.com is an innovative platform that brings students together to share notes, exam papers, study guides, project reports and presentation for upcoming exams.
We connect Students who have an understanding of course material with Students who need help.
Benefits:-
# Students can catch up on notes they missed because of an absence.
# Underachievers can find peer developed notes that break down lecture and study material in a way that they can understand
# Students can earn better grades, save time and study effectively
Our Vision & Mission – Simplifying Students Life
Our Belief – “The great breakthrough in your life comes when you realize it, that you can learn anything you need to learn; to accomplish any goal that you have set for yourself. This means there are no limits on what you can be, have or do.”
Like Us - https://www.facebook.com/FellowBuddycom
This is the second lecture in the CS 6212 class. Covers asymptotic notation and data structures. Also outlines the coming lectures wherein we will study the various algorithm design techniques.
Alan turing's work before, during & after bletchley parkDavid Bew
The slide show combines various accounts in books generally available with new information released more recently. It attempts to portray Turing as a gifted man who found himself in an environment, at Bletchley Park in particular, where his particular skills and abilities, as well as his understanding of what was to be computer programming, were highly valued. The contention is that at Bletchley Park and in certain computer development work afterwards, Turing was able to perform as a specialised worker and at his best
[Question Paper] Fundamentals of Digital Computing (Revised Course) [April / ...Mumbai B.Sc.IT Study
This is a Question Papers of Mumbai University for B.Sc.IT Student of Semester - I [Fundamentals of Digital Computing] (Revised Course). [Year - April / 2015] . . .Solution Set of this Paper is Coming soon..
Köhler, Sven, Bertram Ludäscher, and Yannis Smaragdakis. 2012. “Declarative Datalog Debugging for Mere Mortals.” In Datalog in Academia and Industry, edited by Pablo Barceló and Reinhard Pichler, 111–22. Lecture Notes in Computer Science 7494. Springer Berlin Heidelberg. doi:10.1007/978-3-642-32925-8_12.
Abstract. Tracing why a “faulty” fact A is in the model M = P(I) of program P on input I quickly gets tedious, even for small examples. We propose a simple method for debugging and “logically profiling” P by generating a provenance-enriched rewriting P̂, which records rule firings according to the logical semantics. The resulting provenance graph can be easily queried and analyzed using a set of predefined and ad-hoc queries. We have prototypically implemented our approach for two different Datalog engines (DLV and LogicBlox), demonstrating the simplicity, effectiveness, and system-independent nature of our method.
Digital Signals and System (October – 2016) [Revised Syllabus | Question Paper]Mumbai B.Sc.IT Study
mumbai bscit study, kamal t, mumbai university, old question paper, previous year question paper, bscit question paper, bscit semester vi, internet technology, april - 2015, 75:25 Pattern, 60:40 Pattern, revised syllabus, old syllabus, cbsgc, question paper, may - 2016, april - 2017, april - 2014, april - 2013, may – 2016, october – 2016, digital signals and system
[Question Paper] Fundamentals of Digital Computing (Revised Course) [January ...Mumbai B.Sc.IT Study
This is a Question Papers of Mumbai University for B.Sc.IT Student of Semester - I [Fundamentals of Digital Computing] (Revised Course). [Year - January / 2014] . . .Solution Set of this Paper is Coming soon..
What we got from the Predicting Red Hat Business Value competitionUmaporn Kerdsaeng
This slide is to share what I've learned from the kaggle competition. There 3 topics -1) Overview of the competition 2) Introduction to Decision Tree and 3) R package XGboost.
Similar to Cracking the Enigma Machine - Rejewski, Turing and the Math that saved the world (20)
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Epistemic Interaction - tuning interfaces to provide information for AI support
Cracking the Enigma Machine - Rejewski, Turing and the Math that saved the world
1. The Math That Saved the World Brad Young brad@clearpoint.co.il A Mathematical and Historical Analysis of the Cryptographic Attacks on the Nazi Enigma Machine Marian Rejewski Alan Turing
2. Agenda Development of Enigma Machine – Why/How/What The Rejewski Crack The Turing Crack Historical Impact
3. WWI Cryptology First major war with radio + telegraph Very large volume of communications Hand-ciphers Playfair, ADFGVX etc. Bigraph substitution + transformation Encryption/Decryption Inefficient …Became bottleneck Cryptanalysis Difficult, time-consuming… But successful (mainly)
5. Invention of Enigma Machine Arthur Scherbius Efficient! (oh, and also Secure, by the way) Business, Military versions Early 1920’s – very poor sales German economy in trouble
6. Oops Publishes history book Reveals the impact of crypto on WWI Now, the Germans want Enigma!
7. A B C D E F G H Reflector 3rd Rotor 2nd Rotor 1st Rotor Lightbulbs Keyboard Enigma Schematic
8. A B C D E F G H Reflector Lightbulbs 3rd Rotor 2nd Rotor 1st Rotor Keyboard Electric Circuit
9. A B Pressing ‘A’ on the keyboard… C D E F … lights the ‘B’ lightbulb G H NOTE: Because it is a electric circuit, no letter can map to itself. Minor detail combinatorically speaking, but very important for the Turing crack. Reflector Lightbulbs 3rd Rotor 2nd Rotor 1st Rotor Keyboard Electric Circuit
10. A B C D E After each letter, the first rotor shifts one step. So now, pressing ‘A’ lights a different lightbulb….’F’ F G H Reflector Lightbulbs 3rd Rotor 2nd Rotor 1st Rotor Keyboard Rotor Shift
11. A B C D E F Sits between keyboard and rotors. Each plug cable swaps signal between two letters. 6 cables connect 12 letters. 14 other letters are not plugged at all. G H Reflector Lightbulbs Plugboard 3rd Rotor 2nd Rotor 1st Rotor Keyboard Plugboard
13. Keysize A B Rotor Order Rotor Setting Plugboard Wiring I – III - II VYJ A/G, D/Q, J/Z,L/S, M/V, N/T 3! = 6 263 =17,576 C(26,2) x C(24,2) x C(22,2) x C(20,2) x C(18,2) x C(16,2) x 1/6! (26!)3 x C(26,2)…C(2,2)x1/13! C ≈ 105 D E F ≈ 1011 ≈ 1092 G H Total Key Size ≈ 10108 Variable Key Size ≈ 1016
16. Agenda Development of Enigma Machine – Why/How/What The Rejewski Crack The Turing Crack Historical Impact
17. Biuro Szyfrów 1918 – Polish Independence 1919 – Creation (and success) of Cipher Bureau 1926 – Germany goes dark as Enigma is adopted 1930 – Bring in the mathematicians (?!?) Marian Rejewski Jerzy Różycki Henryk Zygalski
18. The Rejewski Crack Intuition,Espionage,Engineering Understand how Enigma works Reverse-engineer the wiring Be able to crack the key each day Permutational Mathematics
20. Cycle Notation P = P = (AECH)(BFD)(G) = (BFD)(G) (AECH) = (FDB)(G)(CHAE) P-1 = (HCEA)(DFB)(G) Benefits of cycle notation: Concise Easier to take inverse (These are benefits of efficiency)
21. Cycle Structure = (AECH)(BFD)(G) P = 4 3 1 = (AFC)(BG)(D)(EH) Q = 3 2 1 2 Benefits of cycle notation: Concise Easier to take inverse Gives more info – Cycle Structure (This is a benefit of value-add information)
22. Composition P = = (AECH)(BFD)(G) Q = = (AFC)(BG)(D)(EH) Q ◦ P = Q(P()) = (AHFDGBCE) Q ◦ P ≠ P ◦ Q - NOT Commutative Q ◦ ( P ◦ R ) = ( Q ◦ P ) ◦ R - Associative
23. Identity = (A)(B)(C)(D)(E)(F)(G)(H) I = P ◦ I = I ◦ P = P P ◦ P -1 = I I ◦ I = I i.e. I = I -1 (ab) ≠ I , but (ab) ◦ (ab) = (a)(b) i.e. (ab) = (ab)-1
24. Conjugation Conjugation of Q by P is defined as P ◦ Q ◦ P-1 P = (AECH)(BFD)(G) P-1 = (HCEA)(DFB)(G) Q = (AFC)(BG)(D)(EH) 1-2-2-3 1-2-2-3 This is not a coincidence! This is not a coincidence! P ◦ Q ◦ P-1 = (AC)(B)(DHE)(FG)
25. Theorem: Cycle structure is invariant under conjugation Proof: Suppose Q: ij, that is Q(i) = j. Consider P ◦ Q ◦ P-1 (P(i)). P ◦ Q ◦ P-1 (P(i)) = P ◦ Q ◦ (P-1 ◦ P)(i) = P ◦ Q(i) = P(j) i.e. P ◦ Q ◦ P-1: P(i)P(j) Therefore… If Q has k-cycle (i1, i2 … ik) then P ◦ Q ◦ P-1 has k-cycle (P(i1), P(i2)…P(ik)) QED
26. Using Permuation Cycles on Enigma A B Suppose we intercept a message: BOLJRVSQIGPQTMNWJRAKOBYTKMTTGBBRQUPWLHSOLNFEQTHJOVX Plaintext: abcabcCiphertext: BOLJRV Define En as the permutation that occurs when Enigma machine is in state n. So, in the first state, aB. In the fourth state, aJ E1 = (aB …E4 = (aJ … Now…Recall the effect of the Reflector, which creates 2-letter circuits So, if aB, then Ba. So the cycle is closed. E1 = (aB) …E4 = (aJ) … So, we can now compute E4 ◦ E1 = (BJ … C These are the variablesa,b,c, not the actual letters D E F G H
27. Using Permuation Cycles on Enigma If we have many intercepts from the same day, then they were produced with the same day settings. So we can calculate the entire compositions… E4 ◦ E1 = (BJUMPWTCFE)(ARDNHSLYZK)(G)(I)(O)(Q)(X)(V)E5 ◦ E2 = (ORJCLVHGXKF)(AUYMPZQNDWB)(ES)(IT)E6 ◦ E3 = (BWOIKTZHXB)(EPQJYLVGN)(ARCU)(DSMF) Good news: abc variables have been eliminated! We’ve found a unique identifier! Bad news: It is one of 10,000,000,000,000,000 possibilities
28. Explore the nature of En A B En = P ◦ Rn ◦ P where P is the plugboard permutation and Rn is rotor permutation when in state n E4 ◦ E1 = P ◦ R4 ◦ P ◦ P ◦ R1 ◦ P Now, recall the plugboard… P = (ab)(cd)(ef)(gh)(ij)(kl)(m)(n)(o)(p)(q)(r)(s)(t)(u)(v)(w)(x)(y)(z) All 2-cycles and 1-cycles, therefore P = P-1 ! E4 ◦ E1 = P ◦ R4 ◦ P ◦ P ◦ R1 ◦ P = P ◦ R4 ◦ P ◦ P-1 ◦ R1 ◦ P = P ◦ R4 ◦ (P ◦ P-1 ) ◦ R1 ◦ P = P ◦ R4 ◦ R1 ◦ P = P ◦ (R4 ◦ R1 ) ◦ P = P ◦ (R4 ◦ R1 ) ◦ P-1 C P R D E F G H Conjugation:Cycle structure of E4 ◦ E1 is same as cycle structure of R4 ◦ R1 and is not affected at all by the plugboard! E4 ◦ E1 = (BJUMPWTCFE)(ARDNHSLYZK)(G)(I)(O)(Q)(X)(V)E5 ◦ E2 = (AUYMPZQNDWB)(CLVHGXKFORJ)(ES)(IT)E6 ◦ E3 = (BWOIKTZHXB)(EPQJYLVGN)(ARCU)(DSMF) 1-1-1-1-1-1-10-10 ; 2-2-11-11 ; 4-4-9-9 Remember: Keysize(R) ≈ 105 Keysize(P) ≈ 1011
29. Now, where are we? Figuring out En is problem of size 1016 Now, we have Rn, a smaller problem: 105 Just barely small enough to attack brute force
31. Recovering the Plugboard Plugboard is the biggest problem combinatorically But… It is trivial to solve E4 ◦ E1 = (BJUMPWTCFE)(ARDNHSLYZK)(G)(I)(O)(Q)(X)(V) R4 ◦ R1 = (MGWTREFBJU)(AKZCINLSHY)(P)(D)(O)(Q)(V)(X) (BJUMPWTCFE) (BJUMGWTREF) Plugboard settings: P/G , C/R , E/F , etc.
33. Agenda Development of Enigma Machine – Why/How/What The Rejewski Crack The Turing Crack Historical Impact
34. 1939 – Brink of War Polish deliver Enigma replica and training to England and France Biuro Szyfrów is dismantled
35. Bletchley Park HQ of British Government Code and Cypher School (GCCS)
36. New Challenges Combinatoric More rotors to choose from Increase # of plugs Ring settings Procedural Eliminate Message Key repetition Navy / Air Force / Army mods Keysize now 1023
37. Turing’s Solution Known-Plaintext attack Heil Hitler Wetterbericht Seeding values Plaintext Crib:Ciphertext: Try to place the crib without letter any letter mapping to itself WETTERBERICHT WETTERBERICHT WETTERBERICHT WETTERBERICHT WETTERBERICHT EXLMBTWZXBITWZCIQ P(false hit) = (25/26)length of crib
42. M V C b a E1 M Z C b E5 c M B D E7 P(false hit) = (1/26)length of cycle-1 a c
43. Turing’s Bombe NOT a computer Multi-Enigma Wiring 120 rpm max 6 hrs to solve ~70% of days cracked Accurate crib? Location of crib in message? Find cycle in message? Not too many false hits? Crib seeding Fake missions – Get spotted 18’26”N, 72’49”E = einachtzweisechsnordensiebenzweivierneunosten Reimann zeta zeros
44. Agenda Development of Enigma Machine – Why/How/What The Rejewski Crack The Turing Crack Historical Impact
70. Addenda, Errata, Anecdotes Wiring analysis Hans Thilo-Schmidt TTTTTTTTTTTT Entry wheel order Why E1-E6, instead of E0-E5 ? Ring Settings and Rotor Stepping “Turing. Alan Turing.” Other WWII Cryptanalysis Disguising ULTRA intelligence Suggested Reading David Kahn – The Codebreakers Simon Singh – The Code Book