Cryptography

Core Lecture in Summer Term 2008

Instructors

Teaching Assitants

Tutors

Fabienne Eigner

Robert Kühnemann

Kim Pecina

Stefan Schuh

Robert Kühnemann

Kim Pecina

Stefan Schuh

Lecture Time

Tue/Fri 10-12

Location

E2.2 (new lecture hall building)

Language

English

Contact

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na.chiobotaru@gmail.com# Latest News

- Students qualified for the final exam are allowed to participate in the backup exam in order
to improve their grade.

Assignment for the backup exam**Tuesday, October 14, 10:00 - 12:00 (s.t.)!** Family Name Room A - D HS 003, Building E1.3 E - Z HS 002, Building E1.3 - Discussion board is now open.
- The assignment for the tutorials is online. If there are problems with it, write us an email, or contact the tutor of the tutorial you wish to join.
- The slides of the lecture can be downloaded here. Registered course participants will receive the login data in a separate mail. In case you are registered but did not get such a mail, either ask one of your colleagues for the login data, or come to our offices.

# Description

This course is an introduction to Modern Cryptography. It will introduce cryptography from scratch, i.e., no previous knowledge in cryptography or computer security is required. The list of topics comprises:- Information-theoretic security and the One-time Pad
- Symmetric encryption, stream ciphers, block ciphers, Data Encryption Standard (DES), Advanced Encryption Standard (AES)
- Asymmetric encryption, cryptosystems based on RSA and on the discrete logarithm problem, Cramer-Shoup encryption
- Digital signature schemes
- Cryptographic hash functions
- Selected cryptographic protocols and their security
- Crypto in the "real world"
- Basic concepts of advanced cryptographic primitives and current research topics: Bit commitment, zero-knowledge proofs, simulatability, linking formal verification and cryptography

- Douglas R. Stinson: Cryptography: Theory and Practice. CRC Press, 2005
- Nigel Smart: Cryptography: An introduction, McGraw-Hill, 2003

# Prerequisites

This course is a core theory lecture. Basic knowledge in computability, complexity theory, and number theory is useful, but not utterly necessary, as it can be acquired during the course.# Tutorials

The following times for tutorials are available:- Wednesday 10:00 to 12:00
- SR014 (Building E 1.3) Stefan Schuh

- Wednesday 12:00 to 14:00
- SR014 (Building E 1.3) Fabienne Einger
- HS002 (Building E 1.3) Kim Pecina
- HS003 (Building E 1.3) Robert K¨nnemann

Michael Backes will be available for your questions on Tuesday, 13:00 - 14:00 in building E1.1, room U15.

Oana Ciobotaru will be available for your questions on Tuesday, 15:00 - 16:00 in building E1.1, room U13.

The tutors will be available for your questions at the following times in building E1.1, room U21:

- Monday : 12:00 - 14:00
- Tuesday: 13:00 - 15:00

# Homeworks

Weekly homework exercises will be handed out in class and posted to the course page each Tuesday, after the lecture. Their solutions will be posted one week later. No homeworks have to be submitted, but you are encouraged to ask any question you might have concerning the course in the office hours. Homework exercises will thus not influence your grade, however, by presenting solutions in the tutorials you may gain a better grading in the quiz, see below.# Weekly Quiz

Each tutorial starts with a short (approx. 15 minutes) quiz covering
the topics of the same two lectures that were addressed in the last
homework exercise. Your overall quiz-grade is determined by dropping
the quiz with the
lowest grading, and calculating the average of the remaining quizzes. You can further improve your quiz-grade by presenting solutions of the homework exercises in the tutorials. For each correct solution you presented you may drop one additional quiz, up to a maximum of two additional quizzes, i.e., at most three quizzes may be dropped. Please be aware that there is a limited number of exercises, and if more than one student opts for one particular solution, a random student will be drawn. So start early enough!

Quizzes will affect your final grading by 30%, and you need an overall quiz-grading of at least 50% to pass the course.

# Exams

There will be two mandatory exams: A mid-term exam, and a final exam.The mid-term exam will be approx. one hour and consist of multiple-choice and simple questions intended to test your basic understanding of the course material covered so far. Your mid-term grade will affect your final grading by 20%, however, there is no lower bound that has to be reached in order to pass the course.

The final exam will be a written test of two hours. It will make up 50% of your final grade, you need at least 50% to pass the course.

# Grading & Requirements for Passing the Course

Let Q be your quiz score, M your score in the mid-term exam, and E your score in the final exam, each in percent. Then your final overall score Final is calculated asFinal
= 0.3*Q + 0.2*M + 0.5*E,

you pass the course ifQ
≥50% and
E≥50% and Final≥50%.

Q: I got only 49% in the quizzes, but 100% in both exams, will I pass?

A: No, you need 50% in your quizzes to pass.

Q: I got only 49% in the final exam, but 100% in the quizzes and the mid-term exam, will I pass?

A: No, you need 50% in your final exam to pass.

Q: I got only 30% in the mid-term exam, but 100% in final exam and in the quizzes, will I pass?

A: Yes, there is no minimum requirement on the mid-term exam. However, of course, you need a final score of 50% to pass.

# Backup Exams

Date and time of the backup exam is October 14, from 10:00 to 12:00 (s.t). You may take part in the backup exam if you qualified for the final exam, i.e., you got at least 50% score in the quizzes.The backup exam will be written. Please note that if you have passed the final exam and also take the backup exam, the better score between the two will count for your final grade.

# Further Reading

- Summary of basic probability theory by David Joyce (.pdf): A very concise introduction to probability theory
- Introduction to Probability by Albert Meyer (.pdf): Provides more material on probability theory
- A Primer on number theory for computer scientists by Victor Shoup (.pdf): Provides more material and more details on number theory and algebra.