Correlation Attacks Research Articles

Enhancing Image Security during Transmission using Residue Number System and k-shuffle

This paper proposes an algorithm that enhances the speed of transmission and secure images that are transmitted over internet or a network. The proposed cryptosystem uses a modified k-shuffling technique to scramble pixels of images and further decomposes them using Residue Number System. Simulations are done using two moduli sets with the modified k-shuffle technique. Analyses of results showed that both simulations could secure images without any loss of information and also the time taken for a complete encryption/decryption process is dependent on the moduli set. Among the chosen moduli sets, the even moduli set optimizes and completes execution using less time as compared to the traditional moduli set. The proposed scheme also showed resistance to statistical attacks (histogram, ciphertext, correlation attacks) and a significant reduction in the size of cipher images which enhances the speed of transmission over network.

Theory and performance analyses in quantum stream cipher based on bitwise NOT operation

Because of the realization of physical layer security, the Quantum Stream Cipher (QSC) is getting more and more attention. However, the error rate of each bit of ciphertexts is different from 0.5 for Eve in QSC. This drawback provides Eve with an opportunity to break QSC system possibly through some attacks, such as fast correlation attacks. Thus, to increase the bit error rate of ciphertexts in the higher bit positions to cope with this kind of attacks, this paper proposes a ciphertext mapping method based on Bitwise NOT Operation (BNO). According to parity of bases, BNO-based mapping performs bitwise NOT operation for some bit positions of ciphertext to expand the difference between adjacent bit positions of ciphertexts in QSC. Besides, BNO-based QSC can be directly employed in multi-bit plaintext mapping in QSC for different modulation formats, such as PSK/QSC and QAM/QSC. The security and transmission performance of QSC based on BNO are mainly investigated with different intensity ASE noises and the number of bases in optical back-to-back simulation. The simulation results demonstrate that bit error rate in each bit position of ciphertext is close to 0.5 by BNO method in QSC. Thus, BNO method can expand the impact of noise on the higher bit positions of ciphertext. In addition, BNO method has little influence on transmission performance of receiver in QSC system.

Vectorized linear approximations for attacks on SNOW 3G

SNOW 3G is a stream cipher designed in 2006 by ETSI/SAGE, serving in 3GPP as one of the standard algorithms for data confidentiality and integrity protection. It is also included in the 4G LTE standard. In this paper we derive vectorized linear approximations of the finite state machine in SNOW3G. In particular,we show one 24-bit approximation with a bias around 2−37 and one byte-oriented approximation with a bias around 2−40. We then use the approximations to launch attacks on SNOW 3G. The first approximation is used in a distinguishing attack resulting in an expected complexity of 2172 and the second one can be used in a standard fast correlation attack resulting in key recovery in an expected complexity of 2177. If the key length in SNOW 3G would be increased to 256 bits, the results show that there are then academic attacks on such a version faster than the exhaustive key search.

Privacy Preserving for Multiple Sensitive Attributes against Fingerprint Correlation Attack Satisfying c-Diversity

Privacy preserving data publishing (PPDP) refers to the releasing of anonymized data for the purpose of research and analysis. A considerable amount of research work exists for the publication of data, having a single sensitive attribute. The practical scenarios in PPDP with multiple sensitive attributes (MSAs) have not yet attracted much attention of researchers. Although a recently proposed technique (p, k)-Angelization provided a novel solution, in this regard, where one-to-one correspondence between the buckets in the generalized table (GT) and the sensitive table (ST) has been used. However, we have investigated a possibility of privacy leakage through MSA correlation among linkable sensitive buckets and named it as “fingerprint correlation fcorr attack.” Mitigating that in this paper, we propose an improved solution “c,k-anonymization” algorithm. The proposed solution thwarts the fcorr attack using some privacy measures and improves the one-to-one correspondence to one-to-many correspondence between the buckets in GT and ST which further reduces the privacy risk with increased utility in GT. We have formally modelled and analysed the attack and the proposed solution. Experiments on the real-world datasets prove the outperformance of the proposed solution as compared to its counterpart.

A Method of Evaluating the Security of Snow 2.0-Like Ciphers Against Correlation Attacks Over the Finite Extensions of Two Element Field

A method is proposed for evaluation of the security of SNOW 2.0-like ciphers against correlation attacks that are generated by analogy with the well-known attacks on the SNOW 2.0 cipher. Unlike the available methods, the proposed one focuses on proving the security and allows obtaining lower bounds of effectiveness of attacks of the considered class directly by the parameters of stream ciphers components in the same way as it proves the security of block ciphers against linear cryptanalysis. Application of the method to SNOW 2.0 and Strumok ciphers shows that any of the considered correlation attacks on them over the field of order 256 has an average time complexity no less than 2146 . 20 and 2249. 40 , respectively, and requires no less than 2142.77 and 2249. 38 keystream symbols, respectively.

Analysis of Y00 Protocol Under Quantum Generalization of a Fast Correlation Attack: Toward Information-Theoretic Security

In our previous work, it was demonstrated that the attacker could not pin-down the correct keys to start the Y00 protocol with a probability of one under the assistance of unlimitedly long known-plaintext attacks and optimal quantum measurements on the attacker’s quantum memory. However, there were several assumptions that the Y00 system utilized linear-feedback shift registers as pseudo-random-number generators, and a fast correlation attack was disabled by irregular mapping on the Y00 systems. This study generalizes such an attack to remove the assumptions of the previous work. The framework of the security analyses of this study reiterates two well-known results from the past: (1) Y00 systems would be cryptanalyzed when the system is not designed well; (2) the system is possibly information-theoretically secure when the system is designed well, although the attacker’s confidence in the correct key increases over time but the success probability of key recovery does not reach unity in finite time; (3) the breach probability of the shared keys increases with time. Hence, a key-refreshment procedure for the Y00 protocol is provided herein. Such security analyses are important not only in key refreshment but also in initial key agreement.

Secure key agreement based on ordered biometric features

In this work, we propose a novel secure key agreement protocol, Secure Key Agreement using Pure Ordered Biometrics (SKA-POB), in which the cryptographic keys are generated using an ordered set of biometrics, without any extra shared secret data or keys. The proposed approach is instantiated using iris biometrics. Our protocol makes use of hash functions and HMAC (Hash-based Message Authentication Code) as the only cryptographic primitives; thus, it is not cryptographically resource-hungry. We also propose and integrate a window-based comparison strategy and a window reset method in SKA-POB. This way, performance is maximized without sacrificing security. Furthermore, we propose an intelligent fake block generation and distribution strategy to hide the genuine blocks in transit, which increases the resistence of our proposed protocol against correlation attacks. SKA-POB protocol works in round manner, allowing to successfully terminate with key establishment as early as possible so that the complexity is reduced for both client and server sides. Additionally, we employ multi-criteria analyses for our proposed SKA-POB protocol and we provide verification results in terms of performance analysis together with randomness, distinctiveness and attack complexity through security analysis. Results show that highly random and computationally secure keys can be generated with almost no error and with very low complexity.

Guard Placement Attacks on Path Selection Algorithms for Tor

Abstract The popularity of Tor has made it an attractive target for a variety of deanonymization and fingerprinting attacks. Location-based path selection algorithms have been proposed as a countermeasure to defend against such attacks. However, adversaries can exploit the location-awareness of these algorithms by strategically placing relays in locations that increase their chances of being selected as a client’s guard. Being chosen as a guard facilitates website fingerprinting and traffic correlation attacks over extended time periods. In this work, we rigorously define and analyze the guard placement attack. We present novel guard placement attacks and show that three state-of-the-art path selection algorithms—Counter-RAPTOR, DeNASA, and LASTor—are vulnerable to these attacks, overcoming defenses considered by all three systems. For instance, in one attack, we show that an adversary contributing only 0.216% of Tor’s total bandwidth can attain an average selection probability of 18.22%, 84× higher than what it would be under Tor currently. Our findings indicate that existing location-based path selection algorithms allow guards to achieve disproportionately high selection probabilities relative to the cost required to run the guard. Finally, we propose and evaluate a generic defense mechanism that provably defends any path selection algorithm against guard placement attacks. We run our defense mechanism on each of the three path selection algorithms, and find that our mechanism significantly enhances the security of these algorithms against guard placement attacks with only minimal impact to the goals or performance of the original algorithms.

Address Space Layout Randomization Next Generation

Systems that are built using low-power computationally-weak devices, which force developers to favor performance over security; which jointly with its high connectivity, continuous and autonomous operation makes those devices specially appealing to attackers. ASLR (Address Space Layout Randomization) is one of the most effective mitigation techniques against remote code execution attacks, but when it is implemented in a practical system its effectiveness is jeopardized by multiple constraints: the size of the virtual memory space, the potential fragmentation problems, compatibility limitations, etc. As a result, most ASLR implementations (specially in 32-bits) fail to provide the necessary protection. In this paper we propose a taxonomy of all ASLR elements, which categorizes the entropy in three dimensions: (1) how, (2) when and (3) what; and includes novel forms of entropy. Based on this taxonomy we have created, ASLRA, an advanced statistical analysis tool to assess the effectiveness of any ASLR implementation. Our analysis show that all ASLR implementations suffer from several weaknesses, 32-bit systems provide a poor ASLR, and OS X has a broken ASLR in both 32- and 64-bit systems. This is jeopardizing not only servers and end users devices as smartphones but also the whole IoT ecosystem. To overcome all these issues, we present ASLR-NG, a novel ASLR that provides the maximum possible absolute entropy and removes all correlation attacks making ASLR-NG the best solution for both 32- and 64-bit systems. We implemented ASLR-NG in the Linux kernel 4.15. The comparative evaluation shows that ASLR-NG overcomes PaX, Linux and OS X implementations, providing strong protection to prevent attackers from abusing weak ASLRs.

Effects of Passive Negative Correlation Attack on Sensors Utilizing Physical Key Extraction in Indoor Wireless Body Area Networks

Due to the unique properties of wireless body area networks (WBANs), a strategically positioned eavesdropper can achieve a channel with negative correlation. This article demonstrates that negative correlation can be exploited and poses a significant threat for sensors utilizing key extraction techniques that rely on the physical layer and make use of channel-state information. In particular, we show that a commonly used method to improve key agreement between legitimate parties, such as moving average, boosts the confidence of the negatively correlated attacker by 23%. We also show that the quantizer parameters need to be selected carefully to avoid information leak. Interestingly, our results indicate that such an attacker can be located much farther from the legitimate party and can gain more information as compared to an adversary that is located closer but does not experience negative correlation.

Обґрунтування стійкості потокового шифру «Струмок» відносно кореляційних атак над скінченними полями характеристики 2

The stream cipher SNOW 2.0 was proposed in 2002 as an alternative to the previous (weaker) version — SNOW. This cipher is standardized today and is one of the fastest program-oriented stream ciphers.The most powerful known attacks on SNOW 2.0 are correlation attacks, the essence of which is to form and solve systems of noised linear equations, in particular, over finite fields of order greater than 2. Despite some progress in this direction, remain unresolved problems related to the development of methods for evaluation and justification the security of SNOW 2.0-like stream ciphers against correlation attacks. To date, there are no methods that can justify the security of these ciphers against known correlation attacks directly from the parameters of their components. In addition, an attempt to apply known methods for evaluating the security of SNOW 2.0 against correlation attacks to some other stream ciphers (for example, Strumok, which is a candidate for National encryption standard of Ukraine) faces the difficulties associated with the size of tasks that have been solved. Unlike SNOW 2.0, constructed above the field of order , the Strumok cipher is set over a field of order , which leads to the impossibility of practical implementation of some known algorithms, the time complexity of which increases from to bit operations.The purpose of this article is to justify the security of Strumok against a wide class of correlation attacks, including known attacks on SNOW 2.0. The main result is a theorem that establishes an analytical bound for parameter characterizing the effectiveness of correlation attacks on SNOW 2.0-like ciphers in terms of their components. This allows in practice to evaluate and justify the security of such ciphers against correlation attacks over finite fields of characteristic 2.

The Fourier spectral characterization for the correlation-immune functions over $\phantom {\dot {i}\!}\mathbb {F}_{p}$

The correlation-immune functions serve as an important metric for measuring resistance of a cryptosystem against correlation attacks. Existing literature emphasize on matrices, orthogonal arrays and Walsh-Hadamard spectra to characterize the correlation-immune functions over $\phantom {\dot {i}\!}\mathbb {F}_{p}$ (p ≥ 2 is a prime). Recently, Wang and Gong investigated the Fourier spectral characterization over the complex field for correlation-immune Boolean functions. In this paper, the discrete Fourier transform (DFT) of non-binary functions was studied. It was shown that a function f over $\phantom {\dot {i}\!}\mathbb {F}_{p}$ is m th-order correlation-immune if and only if its Fourier spectrum vanishes at a specific location under any permutation of variables. Moreover, if f is a symmetric function, f is correlation-immune if and only if its Fourier spectrum vanishes at only one location.

Improving the Privacy of IoT with Decentralised Identifiers (DIDs)

When IoT devices operate not only with the owner of the device but also with third parties, identifying the device using a permanent identifier, e.g., a hardware identifier, can present privacy problems due to the identifier facilitating tracking and correlation attacks. A changeable identifier can be used to reduce the risk on privacy. This paper looks at using decentralised identifiers (DIDs), an upcoming standard of self-sovereign identifiers with multiple competing implementations, with IoT devices. The paper analyses the resource requirements of running DIDs on the IoT devices and finds that even quite small devices can successfully deploy DIDs and proposes that the most constrained devices could rely on a proxy approach. Finally, the privacy benefits and limitations of using DIDs are analysed, with the conclusion that DIDs significantly improve the users’ privacy when utilised properly.

Privacy-preserving model and generalization correlation attacks for 1:M data with multiple sensitive attributes

Preserved privacy and enhanced utility are two competing requirements in data publishing. For maintaining a trade-off between the two; a plethora of research work exist in 1:1 scenario (each individual has a single record) with a single sensitive attribute (SA). However, some practical scenarios i.e., data having 1:M records (an individual can have multiple records) with multiple sensitive attributes (MSAs), have been relatively understudied. In our current interconnected and digitalized society, the capability to deal with such scenarios is increasingly important due to the ever-increasing sources of data that could be drawn together and infer one's information (e.g. profile and lifestyle) and consequently, compromising one's privacy. In this paper, we present a new type of attack on 1:M records with MSAs, coined as MSAs generalization correlation attacks and perform formal modeling and analysis of these attacks. Then, we propose a privacy-preserving technique “(p, l)-Angelization” for 1:M–MSAs data publication. Extensive experiments over real-world datasets advocate the outperformance of our technique over its counterparts.

A Distributed Flow Correlation Attack to Anonymizing Overlay Networks Based on Wavelet Multi-resolution Analysis

Government agencies rely more and more heavily on the availability of flexible and intelligent solutions for the interception and analysis of Internet-based telecommunications. Unfortunately, the global lawful interception market has been recently put into a corner by the emerging sophisticated encryption, obfuscation and anonymization technologies provided by modern overlay communication infrastructures. To face this challenge, this work proposes a novel strategy for defeating the anonymity of traffic flows, collected within and at the exit of these anonymizing networks, relying on distributed flow-capture, characterization and correlation attacks driven by wavelet-based multi-resolution analysis. Such a strategy, starting from a properly formalized attack model, results in an effective and promising framework that can be easily deployed on real-life network equipment and can potentially scale by working according to different distribution/parallelization scenarios.

Another look at success probability of linear cryptanalysis

This work studies the success probability of key recovery attacks based on using a single linear approximation. Previous works had analysed success probability under different hypotheses on the distributions of correlations for the right and wrong key choices. This work puts forward a unifying framework of general key randomisation hypotheses. All previously used key randomisation hypotheses as also zero correlation attacks can be seen as special cases of the general framework. Derivations of expressions for the success probability are carried out under both the settings of the plaintexts being sampled with and without replacements. Compared to previous analysis, we uncover several new cases which have not been considered in the literature. For most of the cases which have been considered earlier, we provide complete expressions for the respective success probabilities. Finally, the full picture of the dependence of the success probability on the data complexity is revealed. Compared to the extant literature, our work provides a deeper and more thorough understanding of the success probability of single linear cryptanalysis.

A New Hybrid Image Encryption Algorithm Based on 2D-CA, FSM-DNA Rule Generator, and FSBI

Image encryption is an efficient and vital way to protect classified and secret images. With the advancement of the processing power of the computer, AES, DES, or chaotic series type just alike image encryption schemes are not as secure as before. Therefore, in this paper, we present a new hybrid image encryption method for protecting secret and imperative images by employing logistic sine system (LSS) together with two-dimensional cellular automata and FSM-based DNA rule generator. The secure hash (SHA-256) algorithm is used to generate a secret key and to compute initial values for the LSS. In our proposed method, there are three stages and each stage has its own rule. After the scrambling process, the first stage is the Feistel structure-based bit inversion (FSBI) to change the pixels’ value. The second stage is 2D-CA with Moore neighborhood structure-based local rules. The third is DNA conversion based on finite-state machine (FSM-DNA) rule generator. The proposed encryption scheme is robust against the well-known attacks, such as statistical attacks, brute force attacks, differential attacks, and pixel correlation attacks, and also possesses strong key sensitivity. The results show that our three-layer hybrid image encryption technique is robust against many well-known attacks and can be applied directly to all types of classified gray-scale images to make them more secure from such cryptography attacks.

KIST

Tor’s growing popularity and user diversity has resulted in network performance problems that are not well understood, though performance is understood to be a significant factor in Tor’s security. A large body of work has attempted to solve performance problems without a complete understanding of where congestion occurs in Tor. In this article, we first study congestion in Tor at individual relays as well as along the entire end-to-end Tor path and find that congestion occurs almost exclusively in egress kernel socket buffers. We then analyze Tor’s socket interactions and discover two major contributors to Tor’s congestion: Tor writes sockets sequentially, and Tor writes as much as possible to each socket. To improve Tor’s performance, we design, implement, and test KIST: a new socket management algorithm that uses real-time kernel information to dynamically compute the amount to write to each socket while considering all circuits of all writable sockets when scheduling cells. We find that, in the medians, KIST reduces circuit congestion by more than 30%, reduces network latency by 18%, and increases network throughput by nearly 10%. We also find that client and relay performance with KIST improves as more relays deploy it and as network load and packet loss rates increase. We analyze the security of KIST and find an acceptable performance and security tradeoff, as it does not significantly affect the outcome of well-known latency, throughput, and traffic correlation attacks. KIST has been merged and configured as the default socket scheduling algorithm in Tor version 0.3.2.1-alpha (released September 18, 2017) and became stable in Tor version 0.3.2.9 (released January 9, 2018). While our focus is Tor, our techniques and observations should help analyze and improve overlay and application performance, both for security applications and in general.

Studying the relationship between linguistic variables and the degrees of primitive polynomials used in pseudo-random number generator based on fuzzy logic

In this paper we study the relation between linguistic variables and the degree of characteristic primitive polynomial of used LFSR in previously suggested fuzzy pseudorandom number generator FRNG, keeping the out pseudorandom series secure. This means that we should take into account two important properties: the randomness of the output and the security against correlation attacks. The first property mainly depends on selection of primitive polynomials used in constructing FRNG. The second property can be realized by making the output series balanced in sense that the probability of appearing the bits of each used LFSR approximately equal to others in the output stream.

Feature Selection Based Correlation Attack on HTTPS Secure Searching

Search engine plays an irreplaceable role in web information organizing and accessing. It is very common for Internet users to query a search engine when retrieving web information. Sensitive data about search engine user’s intentions or behavior can be inferred from his query phrases, the returned results pages, and the webpages he visits subsequently. In order to protect contents of communications from being eavesdropped, some search engines adopt HTTPS by default to provide bidirectional encryption. This only provides an encrypted channel between user and search engine, the majority of webpages indexed in search engines’ results pages are still on HTTP enabled websites and the contents of these webpages can be observed by attackers once the user click on these links. Imitating attackers, we propose a novel approach for attacking secure search through correlating analysis of encrypted search with unencrypted webpages. We show that a simple weighted TF–DF mechanism is sufficient for selecting guessing phrase candidates. Imitating search engine users, by querying these candidates and enumerating webpages indexed in results pages, we can hit the definite query phrases and meanwhile reconstruct user’s web-surfing trails through DNS-based URLs comparison and flow feature statistics-based network traffic analysis. In the experiment including 28 search phrases, we achieved 67.86% hit rate at first guess and 96.43% hit rate within three guesses. Our empirical research shows that HTTPS traffic can be correlated and de-anonymized through HTTP traffic and secured search of search engines are not always secure unless HTTPS by default enabled everywhere.