The Security of Multiple Encryption in the Ideal Cipher Model
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Advanced Encryption Standard Real-World Alternatives
Outline Multiple Encryption Birthday Attack Advanced Encryption Standard Real-World Alternatives CPSC 367: Cryptography and Security Michael Fischer Lecture 7 February 5, 2019 Thanks to Ewa Syta for the slides on AES CPSC 367, Lecture 7 1/58 Outline Multiple Encryption Birthday Attack Advanced Encryption Standard Real-World Alternatives Multiple Encryption Composition Group property Birthday Attack Advanced Encryption Standard AES Real-World Issues Alternative Private Key Block Ciphers CPSC 367, Lecture 7 2/58 Outline Multiple Encryption Birthday Attack Advanced Encryption Standard Real-World Alternatives Multiple Encryption CPSC 367, Lecture 7 3/58 Outline Multiple Encryption Birthday Attack Advanced Encryption Standard Real-World Alternatives Composition Composition of cryptosystems Encrypting a message multiple times with the same or different ciphers and keys seems to make the cipher stronger, but that's not always the case. The security of the composition can be difficult to analyze. For example, with the one-time pad, the encryption and decryption functions Ek and Dk are the same. The composition Ek ◦ Ek is the identity function! CPSC 367, Lecture 7 4/58 Outline Multiple Encryption Birthday Attack Advanced Encryption Standard Real-World Alternatives Composition Composition within practical cryptosystems Practical symmetric cryptosystems such as DES and AES are built as a composition of simpler systems. Each component offers little security by itself, but when composed, the layers obscure the message to the point that it is difficult for an adversary to recover. The trick is to find ciphers that successfully hide useful information from a would-be attacker when used in concert. CPSC 367, Lecture 7 5/58 Outline Multiple Encryption Birthday Attack Advanced Encryption Standard Real-World Alternatives Composition Double Encryption Double encryption is when a cryptosystem is composed with itself. -
The Data Encryption Standard (DES) – History
Chair for Network Architectures and Services Department of Informatics TU München – Prof. Carle Network Security Chapter 2 Basics 2.1 Symmetric Cryptography • Overview of Cryptographic Algorithms • Attacking Cryptographic Algorithms • Historical Approaches • Foundations of Modern Cryptography • Modes of Encryption • Data Encryption Standard (DES) • Advanced Encryption Standard (AES) Cryptographic algorithms: outline Cryptographic Algorithms Symmetric Asymmetric Cryptographic Overview En- / Decryption En- / Decryption Hash Functions Modes of Cryptanalysis Background MDC’s / MACs Operation Properties DES RSA MD-5 AES Diffie-Hellman SHA-1 RC4 ElGamal CBC-MAC Network Security, WS 2010/11, Chapter 2.1 2 Basic Terms: Plaintext and Ciphertext Plaintext P The original readable content of a message (or data). P_netsec = „This is network security“ Ciphertext C The encrypted version of the plaintext. C_netsec = „Ff iThtIiDjlyHLPRFxvowf“ encrypt key k1 C P key k2 decrypt In case of symmetric cryptography, k1 = k2. Network Security, WS 2010/11, Chapter 2.1 3 Basic Terms: Block cipher and Stream cipher Block cipher A cipher that encrypts / decrypts inputs of length n to outputs of length n given the corresponding key k. • n is block length Most modern symmetric ciphers are block ciphers, e.g. AES, DES, Twofish, … Stream cipher A symmetric cipher that generats a random bitstream, called key stream, from the symmetric key k. Ciphertext = key stream XOR plaintext Network Security, WS 2010/11, Chapter 2.1 4 Cryptographic algorithms: overview -
On the Foundations of Cryptography∗
On the Foundations of Cryptography∗ Oded Goldreich Department of Computer Science Weizmann Institute of Science Rehovot, Israel. [email protected] May 6, 2019 Abstract We survey the main paradigms, approaches and techniques used to conceptualize, define and provide solutions to natural cryptographic problems. We start by presenting some of the central tools used in cryptography; that is, computational difficulty (in the form of one-way functions), pseudorandomness, and zero-knowledge proofs. Based on these tools, we turn to the treatment of basic cryptographic applications such as encryption and signature schemes as well as the design of general secure cryptographic protocols. Our presentation assumes basic knowledge of algorithms, probability theory and complexity theory, but nothing beyond this. Keywords: Cryptography, Theory of Computation. ∗This revision of the primer [59] will appear as Chapter 17 in an ACM book celebrating the work of Goldwasser and Micali. 1 Contents 1 Introduction and Preliminaries 1 1.1 Introduction.................................... ............... 1 1.2 Preliminaries ................................... ............... 4 I Basic Tools 6 2 Computational Difficulty and One-Way Functions 6 2.1 One-WayFunctions................................ ............... 6 2.2 Hard-CorePredicates . .. .. .. .. .. .. .. ................ 9 3 Pseudorandomness 11 3.1 Computational Indistinguishability . ....................... 11 3.2 PseudorandomGenerators. ................. 12 3.3 PseudorandomFunctions . ............... -
Multiple Results on Multiple Encryption
Multiple Results on Multiple Encryption Itai Dinur, Orr Dunkelman, Nathan Keller, and Adi Shamir The Security of Multiple Encryption: Given a block cipher with n-bit plaintexts and n-bit keys, we would like to enhance its security via sequential composition Assuming that – the basic block cipher has no weaknesses – the k keys are independently chosen how secure is the resultant composition? P C K1 K2 K3 K4 Double and Triple Encryptions: Double DES and triple DES were widely used by banks, so their security was thoroughly analyzed By using a Meet in the Middle (MITM) attack, Diffie and Hellman showed in 1981 that double encryption can be broken in T=2^n time and S=2^n space. Note that TS=2^{2n} Given the same amount of space S=2^n, we can break triple encryption in time T=2^{2n}, so again TS=2^{3n} How Secure is k-encryption for k>3? The fun really starts at quadruple encryption (k=4), which was not well studied so far, since we can show that breaking 4-encryption is not harder than breaking 3-encryption when we use 2^n space! Our new attacks: – use the smallest possible amount of data (k known plaintext/ciphertext pairs which are required to uniquely define the k keys) – Never err (if there is a solution, it will always be found) The time complexity of our new attacks (expressed by the coefficient c in the time formula T=2^{cn}) k = c = The time complexity of our new attacks (expressed by the coefficient c in the time formula T=2^{cn}) k = 2 c = 1 The time complexity of our new attacks (expressed by the coefficient c in the time -
Aes Encryption Java Example Code
Aes Encryption Java Example Code Emerging and gleg Whitby enduing: which Paten is minuscule enough? Emasculate Roderic evaded aversely while Hamel always incinerated his trio decollating ontogenetically, he ferment so scrutinizingly. Sargent is top-level and dialogised esuriently while alchemical Rickey delimitated and claw. How to Encrypt and Decrypt using AES in Java JavaPointers. Typically the first time any longer preclude subsequent encryption attempts. Java AES encryption and decryption with static secret. Strategies to keep IV The IV used to encrypt the message is best to decrypting the message therefore leaving question is raised, the data contained in multiple files should have used several keys to encrypt the herd thus bringing down risk of character total exposure loss. AES Encryption with HMAC Integrity in Java netnixorg. AES was developed by two belgian cryptographers. Gpg key example, aes encryption java service encrypt text file, and is similar to connect to read the codes into different. It person talk about creating AES keys and storing AES keys in a JCEKS keystore format. As a predecessor value initialization vector using os. Where to Go live Here? Cipher to took the data bank it is passed to the underlying stream. This code if you use aes? Change i manage that you how do. Copyright The arc Library Authors. First house get an arms of Cipher for your chosen encryption type. To encrypt the dom has access to java encryption? You would do the encryption java service for file transfer to. The java or? Find being on Facebook and Twitter. There put two ways for generating a digit key is used on each router that use. -
Access Control Model with Attribute Based Multiple Encryption
International Journal for Research in Engineering Application & Management (IJREAM) ISSN : 2454-9150 Vol-03, Issue 01, Apr 2017 Access Control Model with Attribute Based Multiple Encryption 1Aishwarya Shinde, 2Rupali Kangane, 3Priyanka Deshmukh, 4Mr. Satish L. Kuchiwale 1,2,3UG Student, 4Professor, 1,2,3,4S.I.G.C.E, Mumbai, Maharashtra, India. [email protected], [email protected], [email protected], [email protected] Abstract — Users are provided by an online storage space hosted on drobox, accessible anywhere via the Internet. Hierarchical Attributed Set Based Encryption (HASBE) concept used in existing system. User is responsible for keeping the data available and accessible but issues arises such as time complexity, flexibility, data security, scalability. These issues are solved in developed system with the help of Cipher Text-Policy attribute-set-based Encryption (CP-ABE). It is an access control model where data will be stored in encrypted form on drobox and data will decrypted using keys. In developed system, multiple encryption is done using four different algorithms named as AES, Blowfish, RSA and Triple DES. These algorithms are used for images, doc and pdf files etc. Furthermore, integrating all these algorithms with CP-ABE key generation techniques used for encrypting file. When compared to existing system, developed system provides data security with less time complexity. Keywords — Scalability, Flexibility, Attribute, Cipher text-policy. I. INTRODUCTION1 security depends on more than simply applying appropriate data security procedures. Computer based security measures Cryptography is a technique for securing the secrecy of mostly capitalizes on user authorization and authentication. communication and many different methods have been HASBE(Hierarchical Attributed Set Based developed to encrypt and decrypt data in order to keep the Encryption)scheme is not scalable and flexible for key message secret. -
Draft Lecture Notes
CS-282A / MATH-209A Foundations of Cryptography Draft Lecture Notes Winter 2010 Rafail Ostrovsky UCLA Copyright © Rafail Ostrovsky 2003-2010 Acknowledgements: These lecture notes were produced while I was teaching this graduate course at UCLA. After each lecture, I asked students to read old notes and update them according to the lecture. I am grateful to all of the students who participated in this massive endeavor throughout the years, for asking questions, taking notes and improving these lecture notes each time. Table of contents PART 1: Overview, Complexity classes, Weak and Strong One-way functions, Number Theory Background. PART 2: Hard-Core Bits. PART 3: Private Key Encryption, Perfectly Secure Encryption and its limitations, Semantic Security, Pseudo-Random Generators. PART 4: Implications of Pseudo-Random Generators, Pseudo-random Functions and its applications. PART 5: Digital Signatures. PART 6: Trapdoor Permutations, Public-Key Encryption and its definitions, Goldwasser-Micali, El-Gamal and Cramer-Shoup cryptosystems. PART 7: Interactive Proofs and Zero-Knowledge. PART 8: Bit Commitment Protocols in different settings. PART 9: Non-Interactive Zero Knowledge (NIZK) PART 10: CCA1 and CCA2 Public Key Encryption from general Assumptions: Naor-Yung, DDN. PART 11: Non-Malleable Commitments, Non-Malleable NIZK. PART 12: Multi-Server PIR PART 13: Single-Server PIR, OT, 1-2-OT, MPC, Program Obfuscation. PART 14: More on MPC including GMW and BGW protocols in the honest-but-curious setting. PART 15: Yao’s garbled circuits, Efficient ZK Arguments, Non-Black-Box Zero Knowledge. PART 16: Remote Secure Data Storage (in a Cloud), Oblivious RAMs. CS 282A/MATH 209A: Foundations of Cryptography °c 2006-2010 Prof. -
How to Encipher Messages on a Small Domain Deterministic Encryption and the Thorp Shuffle
How to Encipher Messages on a Small Domain Deterministic Encryption and the Thorp Shuffle Ben Morris1, Phillip Rogaway2, and Till Stegers2 1 Dept. of Mathematics, University of California, Davis, California 95616, USA 2 Dept. of Computer Science, University of California, Davis, California 95616, USA Abstract. We analyze the security of the Thorp shuffle, or, equivalently, a maximally unbalanced Feistel network. Roughly said, the Thorp shuffle on N cards mixes any N 1−1/r of them in O(r lg N) steps. Correspond- ingly, making O(r) passes of maximally unbalanced Feistel over an n-bit string ensures CCA-security to 2n(1−1/r) queries. Our results, which em- ploy Markov-chain techniques, enable the construction of a practical and provably-secure blockcipher-based scheme for deterministically encipher- ing credit card numbers and the like using a conventional blockcipher. 1 Introduction Small-space encryption. Suppose you want to encrypt a 9-decimal-digit plaintext, say a U.S. social-security number, into a ciphertext that is again a 9-decimal-digit number. A shared key K is used to control the encryption. Syn- tactically, you seek a cipher E: K×M → M where M = {0, 1,...,N− 1}, 9 N =10 ,andEK = E(K, ·) is a permutation for each key K ∈K. You aim to construct your scheme from a well-known primitive, say AES, and to prove your scheme is as secure as the primitive from which you start. The problem is harder than it sounds. You can’t just encode each plaintext M ∈Mas a 128-bit string and then apply AES, say, as that will return a 128-bit string and projecting back onto M will destroy permutivity. -
Stdin (Ditroff)
- 50 - Foundations of Cryptography Notes of lecture No. 5B (given on Apr. 2nd) Notes taken by Eyal Kushilevitz Summary In this (half) lecture we introduce and define the concept of secure encryption. (It is assumed that the reader is familiar with the notions of private-key and public-key encryption, but we will define these notions too for the sake of self-containment). 1. Secure encryption - motivation. Secure encryption is one of the fundamental problems in the field of cryptography. One of the important results of this field in the last years, is the success to give formal definitions to intuitive concepts (such as secure encryption), and the ability to suggest efficient implementations to such systems. This ability looks more impressive when we take into account the strong requirements of these definitions. Loosely speaking, an encryption system is called "secure", if seeing the encrypted message does not give any partial information about the message, that is not known beforehand. We describe here the properties that we would like the definition of encryption system to capture: g Computational hardness - As usual, the definition should deal with efficient procedures. That is, by saying that the encryption does not give any partial information about the message, we mean that no efficient algorithm is able to gain such an information Clearly, we also require that the encryption and decryption procedures will be efficient. g Security with respect to any probability distribution of messages - The encryption system should be secure independently of the probability distribution of the messages we encrypt. For example: we do not want a system which is secure with respect to messages taken from a uniform distribution, but not secure with respect to messages written in English. -
CMCC: Misuse Resistant Authenticated Encryption with Minimal Ciphertext Expansion
cryptography Article CMCC: Misuse Resistant Authenticated Encryption with Minimal Ciphertext Expansion Jonathan Trostle Independent Researcher, Washington, DC 98684, USA; [email protected] or [email protected]; Tel.: +1-360-253-8417 Received: 21 September 2018; Accepted: 4 December 2018; Published: 19 December 2018 Abstract: In some wireless environments, minimizing the size of messages is paramount due to the resulting significant energy savings. We present CMCC (CBC-MAC-CTR-CBC), an authenticated encryption scheme with associated data (AEAD) that is also nonce misuse resistant. The main focus for this work is minimizing ciphertext expansion, especially for short messages including plaintext lengths less than the underlying block cipher length (e.g., 16 bytes). For many existing AEAD schemes, a successful forgery leads directly to a loss of confidentiality. For CMCC, changes to the ciphertext randomize the resulting plaintext, thus forgeries do not necessarily result in a loss of confidentiality which allows us to reduce the length of the authentication tag. For protocols that send short messages, our scheme is similar to Synthetic Initialization Vector (SIV) mode for computational overhead but has much smaller expansion. We prove both a misuse resistant authenticated encryption (MRAE) security bound and an authenticated encryption (AE) security bound for CMCC. We also present a variation of CMCC, CWM (CMCC With MAC), which provides a further strengthening of the security bounds. Keywords: energy constrained cryptography; authenticated encryption; misuse resistance 1. Introduction The current paradigm of providing confidentiality and integrity protection for distributed applications through the use of encryption combined with MAC’s (Message Authentication Codes) is reasonably efficient for many environments. -
On One-Way Functions and Kolmogorov Complexity
On One-way Functions and Kolmogorov Complexity Yanyi Liu Rafael Pass∗ Cornell University Cornell Tech [email protected] [email protected] September 25, 2020 Abstract We prove that the equivalence of two fundamental problems in the theory of computing. For every polynomial t(n) ≥ (1 + ")n; " > 0, the following are equivalent: • One-way functions exists (which in turn is equivalent to the existence of secure private-key encryption schemes, digital signatures, pseudorandom generators, pseudorandom functions, commitment schemes, and more); • t-time bounded Kolmogorov Complexity, Kt, is mildly hard-on-average (i.e., there exists a t 1 polynomial p(n) > 0 such that no PPT algorithm can compute K , for more than a 1 − p(n) fraction of n-bit strings). In doing so, we present the first natural, and well-studied, computational problem characterizing the feasibility of the central private-key primitives and protocols in Cryptography. arXiv:2009.11514v1 [cs.CC] 24 Sep 2020 ∗Supported in part by NSF Award SATC-1704788, NSF Award RI-1703846, AFOSR Award FA9550-18-1-0267, and a JP Morgan Faculty Award. This research is based upon work supported in part by the Office of the Director of National Intelligence (ODNI), Intelligence Advanced Research Projects Activity (IARPA), via 2019-19-020700006. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies, either expressed or implied, of ODNI, IARPA, or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for governmental purposes notwithstanding any copyright annotation therein. -
On One-Way Functions and Kolmogorov Complexity
On One-way Functions and Kolmogorov Complexity Yanyi Liu Rafael Pass∗ Cornell University Cornell Tech [email protected] [email protected] September 24, 2020 Abstract We prove that the equivalence of two fundamental problems in the theory of computing. For every polynomial t(n) ≥ (1 + ")n; " > 0, the following are equivalent: • One-way functions exists (which in turn is equivalent to the existence of secure private-key encryption schemes, digital signatures, pseudorandom generators, pseudorandom functions, commitment schemes, and more); • t-time bounded Kolmogorov Complexity, Kt, is mildly hard-on-average (i.e., there exists a t 1 polynomial p(n) > 0 such that no PPT algorithm can compute K , for more than a 1 − p(n) fraction of n-bit strings). In doing so, we present the first natural, and well-studied, computational problem characterizing the feasibility of the central private-key primitives and protocols in Cryptography. ∗Supported in part by NSF Award SATC-1704788, NSF Award RI-1703846, AFOSR Award FA9550-18-1-0267, and a JP Morgan Faculty Award. This research is based upon work supported in part by the Office of the Director of National Intelligence (ODNI), Intelligence Advanced Research Projects Activity (IARPA), via 2019-19-020700006. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies, either expressed or implied, of ODNI, IARPA, or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for governmental purposes notwithstanding any copyright annotation therein. 1 Introduction We prove the equivalence of two fundamental problems in the theory of computing: (a) the exis- tence of one-way functions, and (b) mild average-case hardness of the time-bounded Kolmogorov Complexity problem.