Tornado Attack on RC4 with Applications to WEP & WPA

In this paper, we construct several tools for building and manipulating pools of biases in the analysis of RC4. We report extremely fast and optimized active and passive attacks against IEEE 802.11 wireless communication protocol WEP and a key recovery and a distinguishing attack against WPA. This was achieved through a huge amount of theoretical and experimental analysis (capturing WiFi packets), refinement and optimization of all the former known attacks and methodologies against RC4 stream cipher in WEP and WPA modes. We support all our claims on WEP by providing an implementation of this attack as a publicly available patch on Aircrack-ng. Our new attack improves its success probability drastically. Our active attack, based on ARP injection, requires 22500 packets to gain success probability of 50\% against a 104-bit WEP key, using Aircrack-ng in non-interactive mode. It runs in less than 5 seconds on an off-the-shelf PC. Using the same number of packets, Aicrack-ng yields around 3\% success rate. Furthermore, we describe very fast passive only attacks by just eavesdropping TCP/IPv4 packets in a WiFi communication. Our passive attack requires 27500 packets. This is much less than the number of packets Aircrack-ng requires in active mode (around 37500), which is a huge improvement. Deploying a similar theory, we also describe several attacks on WPA. Firstly, we describe a distinguisher for WPA with complexity 2^{42} and advantage 0.5 which uses 2^{42} packets. Then, based on several partial temporary key recovery attacks, we recover the full 128-bit temporary key of WPA by using 2^{42} packets. It works with complexity 2^{96}. So far, this is the best key recovery attack against WPA. We believe that our analysis brings on further insight to the security of RC4

Deep Learning based Cryptanalysis of Stream Ciphers

Conventional cryptanalysis techniques necessitate an extensive analysis of non-linear functions defining the relationship of plain data, key, and corresponding cipher data. These functions have very high degree terms and make cryptanalysis work extremely difficult. The advent of deep learning algorithms along with the better and efficient computing resources has brought new opportunities to analyze cipher data in its raw form. The basic principle of designing a cipher is to introduce randomness into it, which means the absence of any patterns in cipher data. Due to this fact, the analysis of cipher data in its raw form becomes essential. Deep learning algorithms are different from conventional machine learning algorithms as the former directly work on raw data without any formal requirement of feature selection or feature extraction steps. With these facts and the assumption of the suitability of employing deep learning algorithms for cipher data, authors introduced a deep learning based method for finding biases in stream ciphers in the black-box analysis model. The proposed method has the objective to predict the occurrence of an output bit/byte at a specific location in the stream cipher generated keystream. The authors validate their method on stream cipher RC4 and its improved variant RC4A and discuss the results in detail. Further, the authors apply the method on two more stream ciphers namely Trivium and TRIAD. The proposed method can find bias in RC4 and shows the absence of this bias in its improved variant and other two ciphers. Focusing on RC4, the authors present a comparative analysis with some existing methods in terms of approach and observations and showed that their process is more straightforward and less complicated than the existing ones

Image Encryption using Gingerbreadman Map And RC4A Stream Cipher

Day to day increasing flow of sensitive or confidential information, such as images, audio, video, etc., over unsecured medium (like Internet) has motivated more concentration for concrete crypto algorithms. In this paper, an image encryption algorithm based on a permutation and substitution cipher has been proposed. In permutation stage, image pixels are shuffled using gingerbreadman map while in substitution stage, pixels are bit-wise XOR-ed with the keystream generated using RC4A (Rivest Cipher 4A) stream cipher algorithm. For the proposed scheme, statistical analyses, like histogram, adjacent pixels correlation coefficient, and information entropy are given. Security analyses, like key sensitivity, occlusion analysis are also given in this paper. The occlusion analysis shows that the proposed method is resistant to the occlusion attack. These statistical and security analyses support the concreteness of the proposed method

Analysing and exploiting the Mantin biases in RC4

We explore the use of the Mantin biases (Mantin, Eurocrypt 2005) to recover plaintexts from RC4-encrypted traffic. We provide a more fine-grained analysis of these biases than in Mantin\u27s original work. We show that, in fact, the original analysis was incorrect in certain cases: the Mantin biases are sometimes non-existent, and sometimes stronger than originally predicted. We then show how to use these biases in a plaintext recovery attack. Our attack targets two unknown bytes of plaintext that are located close to sequences of known plaintext bytes, a situation that arises in practice when RC4 is used in, for example, TLS. We provide a statistical framework that enables us to make predictions about the performance of this attack and its variants. We then extend the attack using standard dynamic programming techniques to tackle the problem of recovering longer plaintexts, a setting of practical interest in recovering HTTP session cookies and user passwords that are protected by RC4 in TLS. We perform experiments showing that we can successfully recover 16-byte plaintexts with 80% success rate using $2^{31}$ ciphertexts, an improvement over previous attacks

Some Words on Cryptanalysis of Stream Ciphers

In the world of cryptography, stream ciphers are known as primitives used to ensure privacy over a communication channel. One common way to build a stream cipher is to use a keystream generator to produce a pseudo-random sequence of symbols. In such algorithms, the ciphertext is the sum of the keystream and the plaintext, resembling the one-time pad principal. Although the idea behind stream ciphers is simple, serious investigation of these primitives has started only in the late 20th century. Therefore, cryptanalysis and design of stream ciphers are important. In recent years, many designs of stream ciphers have been proposed in an effort to find a proper candidate to be chosen as a world standard for data encryption. That potential candidate should be proven good by time and by the results of cryptanalysis. Different methods of analysis, in fact, explain how a stream cipher should be constructed. Thus, techniques for cryptanalysis are also important. This thesis starts with an overview of cryptography in general, and introduces the reader to modern cryptography. Later, we focus on basic principles of design and analysis of stream ciphers. Since statistical methods are the most important cryptanalysis techniques, they will be described in detail. The practice of statistical methods reveals several bottlenecks when implementing various analysis algorithms. For example, a common property of a cipher to produce n-bit words instead of just bits makes it more natural to perform a multidimensional analysis of such a design. However, in practice, one often has to truncate the words simply because the tools needed for analysis are missing. We propose a set of algorithms and data structures for multidimensional cryptanalysis when distributions over a large probability space have to be constructed. This thesis also includes results of cryptanalysis for various cryptographic primitives, such as A5/1, Grain, SNOW 2.0, Scream, Dragon, VMPC, RC4, and RC4A. Most of these results were achieved with the help of intensive use of the proposed tools for cryptanalysis

Fast and Accurate Machine Learning-based Malware Detection via RC4 Ciphertext Analysis

Malware is dramatically increasing its viability while hiding its malicious intent and/or behavior by employing ciphers. So far, many efforts have been made to detect malware and prevent it from damaging users by monitoring network packets. However, conventional detection schemes analyzing network packets directly are hardly applicable to detect the advanced malware that encrypts the communication. Cryptoanalysis of each packet flowing over a network might be one feasible solution for the problem. However, the approach is computationally expensive and lacks accuracy, which is consequently not a practical solution. To tackle these problems, in this paper, we propose novel schemes that can accurately detect malware packets encrypted by RC4 without decryption in a timely manner. First, we discovered that a fixed encryption key generates unique statistical patterns on RC4 ciphertexts. Then, we detect malware packets of RC4 ciphertexts efficiently and accurately by utilizing the discovered statistical patterns of RC4 ciphertext given encryption key. Our proposed schemes directly analyze network packets without decrypting ciphertexts. Moreover, our analysis can be effectively executed with only a very small subset of the network packet. To the best of our knowledge, the unique signature has never been discussed in any previous research. Our intensive experimental results with both simulation data and actual malware show that our proposed schemes are extremely fast (23.06±1.52 milliseconds) and highly accurate (100%) on detecting a DarkComet malware with only a network packet of 36 bytes

Dependence in IV-related bytes of RC4 key enhances vulnerabilities in WPA

The first three bytes of the RC4 key in WPA are public as they are derived from the public parameter IV, and this derivation leads to a strong mutual dependence between the first two bytes of the RC4 key. In this paper, we provide a disciplined study of RC4 biases resulting specifically in such a scenario. Motivated by the work of AlFardan et al. (2013), we first prove the interesting sawtooth distribution of the first byte in WPA and the similar nature for the biases in the initial keystream bytes towards zero. As we note, this sawtooth characteristics of these biases surface due to the dependence of the first two bytes of the RC4 key in WPA, both derived from the same byte of the IV. Our result on the nature of the first keystream byte provides a significantly improved distinguisher for RC4 used in WPA than what had been presented by Sepehrdad et al. (2011-12). Further, we revisit the correlation of initial keystream bytes in WPA to the first three bytes of the RC4 key. As these bytes are known from the IV, one can obtain new as well as significantly improved biases in WPA than the absolute biases exploited earlier by AlFardan et al. or Isobe et al. We notice that the correlations of the keystream bytes with publicly known IV values of WPA potentially strengthen the practical plaintext recovery attack on the protocol

Cryptanalysis of symmetric key primitives

Block ciphers and stream ciphers are essential building blocks that are used to construct computing systems which have to satisfy several security objectives. Since the security of these systems depends on the security of its parts, the analysis of these symmetric key primitives has been a goal of critical importance. In this thesis we provide cryptanalytic results for some recently proposed block and stream ciphers. First, we consider two light-weight block ciphers, TREYFER and PIFEA-M. While TREYFER was designed to be very compact in order to fit into constrained environments such as smart cards and RFIDs, PIFEA-M was designed to be very fast in order to be used for the encryption of multimedia data. We provide a related-key attack on TREYFER which recovers the secret key given around 2 11 encryptions and negligible computational effort. As for PIFEA-M, we provide evidence that it does not fulfill its design goal, which was to defend from certain implementation dependant differential attacks possible on previous versions of the cipher. Next. we consider the NGG stream cipher, whose design is based on RC4 and aims to increase throughput by operating with 32-bit or 64-bit values instead of with 8-bit values. We provide a distinguishing attack on NGG which requires just one keystream word. We also show that the first few kilobytes of the keystream may leak information about the secret key which allows the cryptanalyst to recover the secret key in an efficient way. Finally, we consider GGHN, another RC4-like cipher that operates with 32-bit words. We assess different variants of GGHN-Iike algorithms with respect to weak states, in which all internal state words and output elements are even. Once GGHN is absorbed in such a weak state, the least significant bit of the plaintext words will be revealed only by looking at the ciphertext. By modelling the algorithm by a Markov chain and calculating the chain absorption time, we show that the average number of steps required by these algorithms to enter this weak state can be lower than expected at first glance and hence caution should be exercised when estimating this numbe

Design of Stream Ciphers and Cryptographic Properties of Nonlinear Functions

Block and stream ciphers are widely used to protect the privacy of digital information. A variety of attacks against block and stream ciphers exist; the most recent being the algebraic attacks. These attacks reduce the cipher to a simple algebraic system which can be solved by known algebraic techniques. These attacks have been very successful against a variety of stream ciphers and major efforts (for example eSTREAM project) are underway to design and analyze new stream ciphers. These attacks have also raised some concerns about the security of popular block ciphers. In this thesis, apart from designing new stream ciphers, we focus on analyzing popular nonlinear transformations (Boolean functions and S-boxes) used in block and stream ciphers for various cryptographic properties, in particular their resistance against algebraic attacks. The main contribution of this work is the design of two new stream ciphers and a thorough analysis of the algebraic immunity of Boolean functions and S-boxes based on power mappings. First we present WG, a family of new stream ciphers designed to obtain a keystream with guaranteed randomness properties. We show how to obtain a mathematical description of a WG stream cipher for the desired randomness properties and security level, and then how to translate this description into a practical hardware design. Next we describe the design of a new RC4-like stream cipher suitable for high speed software applications. The design is compared with original RC4 stream cipher for both security and speed. The second part of this thesis closely examines the algebraic immunity of Boolean functions and S-boxes based on power mappings. We derive meaningful upper bounds on the algebraic immunity of cryptographically significant Boolean power functions and show that for large input sizes these functions have very low algebraic immunity. To analyze the algebraic immunity of S-boxes based on power mappings, we focus on calculating the bi-affine and quadratic equations they satisfy. We present two very efficient algorithms for this purpose and give new S-box constructions that guarantee zero bi-affine and quadratic equations. We also examine these S-boxes for their resistance against linear and differential attacks and provide a list of S-boxes based on power mappings that offer high resistance against linear, differential, and algebraic attacks. Finally we investigate the algebraic structure of S-boxes used in AES and DES by deriving their equivalent algebraic descriptions