Reduction in the Number of Fault Injections for Blind Fault Attack on SPN Block Ciphers

In 2014, a new fault analysis called blind fault attack (BFA) was proposed, in which attackers can only obtain the number of different faulty outputs without knowing the public data. The original BFA requires 480,000 fault injections to recover a 128-bit AES key. This work attempts to reduce the number of fault injections under the same attack assumptions. We analyze BFA from an information theoretical perspective and introduce a new probability-based distinguisher. Three approaches are proposed for different attack scenarios. The best one realized a 66.8% reduction of the number of fault injections on AES

An effective simulation analysis of transient electromagnetic multiple faults

Embedded encryption devices and smart sensors are vulnerable to physical attacks. Due to the continuous shrinking of chip size, laser injection, particle radiation and electromagnetic transient injection are possible methods that introduce transient multiple faults. In the fault analysis stage, the adversary is unclear about the actual number of faults injected. Typically, the single-nibble fault analysis encounters difficulties. Therefore, in this paper, we propose novel ciphertext-only impossible differentials that can analyze the number of random faults to six nibbles. We use the impossible differentials to exclude the secret key that definitely does not exist, and then gradually obtain the unique secret key through inverse difference equations. Using software simulation, we conducted 32,000 random multiple fault attacks on Midori. The experiments were carried out to verify the theoretical model of multiple fault attacks. We obtain the relationship between fault injection and information content. To reduce the number of fault attacks, we further optimized the fault attack method. The secret key can be obtained at least 11 times. The proposed ciphertext-only impossible differential analysis provides an effective method for random multiple faults analysis, which would be helpful for improving the security of block ciphers

Application of Fault Analysis to Some Cryptographic Standards

Cryptanalysis methods can be classified as pure mathematical attacks, such as linear and differential cryptanalysis, and implementation dependent attacks such as power analysis and fault analysis. Pure mathematical attacks exploit the mathematical structure of the cipher to reveal the secret key inside the cipher. On the other hand, implementation dependent attacks assume that the attacker has access to the cryptographic device to launch the attack. Fault analysis is an example of a side channel attack in which the attacker is assumed to be able to induce faults in the cryptographic device and observe the faulty output. Then, the attacker tries to recover the secret key by combining the information obtained from the faulty and the correct outputs. Even though fault analysis attacks may require access to some specialized equipment to be able to insert faults at specific locations or at specific times during the computation, the resulting attacks usually have time and memory complexities which are far more practical as compared to pure mathematical attacks. Recently, several AES-based primitives were approved as new cryptographic standards throughout the world. For example, Kuznyechik was approved as the standard block cipher in Russian Federation, and Kalyna and Kupyna were approved as the standard block cipher and the hash function, respectively, in Ukraine. Given the importance of these three new primitives, in this thesis, we analyze their resistance against fault analysis attacks. Firstly, we modified a differential fault analysis (DFA) attack that was applied on AES and applied it on Kuzneychik. Application of DFA on Kuznyechik was not a trivial task because of the linear transformation layer used in the last round of Kuznyechik. In order to bypass the effect of this linear transformation operation, we had to use an equivalent representation of the last round which allowed us to recover the last two round keys using a total of four faults and break the cipher. Secondly, we modified the attack we applied on Kuzneychik and applied it on Kalyna. Kalyna has a complicated key scheduling and it uses modulo 264 addition operation for applying the first and last round keys. This makes Kalyna more resistant to DFA as com- pared to AES and Kuznyechik but it is still practically breakable because the number of key candidates that can be recovered by DFA can be brute-forced in a reasonable time. We also considered the case where the SBox entries of Kalyna are not known and showed how to recover a set of candidates for the SBox entries. Lastly, we applied two fault analysis attacks on Kupyna hash function. In the first case, we assumed that the SBoxes and all the other function parameters are known, and in the second case we assumed that the SBoxes were kept secret and attacked the hash function accordingly. Kupyna can be used as the underlying hash function for the construction of MAC schemes such as secret IV, secret prefix, HMAC or NMAC. In our analysis, we showed that secret inputs of Kupyna can be recovered using fault analysis. To conclude, we analyzed two newly accepted standard ciphers (Kuznyechik, Kalyna) and one newly approved standard hash function (Kupyna) for their resistance against fault attacks. We also analyzed Kalyna and Kupyna with the assumption that these ciphers can be deployed with secret user defined SBoxes in order to increase their security

AB-SIFA: SIFA with Adjacent-Byte Model

Statistical Ineffective Fault Attack (SIFA) has been a threat for implementa-tions of symmetric cryptographic primitives. Unlike Differential Fault At-tacks (DFA) which takes both correct and faulty ciphertexts, SIFA can re-cover the secret key with only correct ciphertexts. The classic SIFA is only effective on fault models with non-uniform distribution of intermediate val-ue. In this paper, we present a new fault model named adjacent-byte model, which describes a non-uniform distribution of relationship between two bytes (i.e. exclusive-or). To the best of our knowledge, it is the first time that this fault model has been proposed. We also show that the adjacent-byte faults can be induced by different fault sources and easy to reproduce. Then a new SIFA attack method called AB-SIFA on symmetric cryptography is proposed. We demonstrate the effectiveness of this new attack by simulating the attack. Finally, our attacks are applied to a software implementations of AES-128 with redundant countermeasure and a hardware AES co-processor, utilizing voltage glitches and clock glitches

Electromagnetic Side-Channel Resilience against Lightweight Cryptography

Side-channel attacks are an unpredictable risk factor in cryptography. Therefore, observations of leakages through physical parameters, i.e., power and electromagnetic (EM) radiation, etc., of digital devices are essential to minimise vulnerabilities associated with cryptographic functions. Compared to costs in the past, performing side-channel attacks using inexpensive test equipment is becoming a reality. Internet-of-Things (IoT) devices are resource-constrained, and lightweight cryptography is a novel approach in progress towards IoT security. Thus, it would provide sufficient data and privacy protection in such a constrained ecosystem. Therefore, cryptanalysis of physical leakages regarding these emerging ciphers is crucial. EM side-channel attacks seem to cause a significant impact on digital forensics nowadays. Within existing literature, power analysis seems to have considerable attention in research whereas other phenomena, such as EM, should continue to be appropriately evaluated in playing a role in forensic analysis.The emphasis of this thesis is on lightweight cryptanalysis. The preliminary investigations showed no Correlation EManalysis (CEMA) of PRESENT lightweight algorithm. The PRESENT is a block cipher that promises to be adequate for IoT devices, and is expected to be used commercially in the future. In an effort to fill in this research gap, this work examines the capabilities of a correlation EM side-channel attack against the PRESENT. For that, Substitution box (S-box) of the PRESENT was targeted for its 1st round with the use of a minimum number of EM waveforms compared to other work in literature, which was 256. The attack indicates the possibility of retrieving 8 bytes of the secret key out of 10 bytes. The experimental process started from a Simple EMA (SEMA) and gradually enhanced up to a CEMA. The thesis presents the methodology of the attack modelling and the observations followed by a critical analysis. Also, a technical review of the IoT technology and a comprehensive literature review on lightweight cryptology are included

How Practical are Fault Injection Attacks, Really?

Fault injection attacks (FIA) are a class of active physical attacks, mostly used for malicious purposes such as extraction of cryptographic keys, privilege escalation, attacks on neural network implementations. There are many techniques that can be used to cause the faults in integrated circuits, many of them coming from the area of failure analysis. In this paper we tackle the topic of practicality of FIA. We analyze the most commonly used techniques that can be found in the literature, such as voltage/clock glitching, electromagnetic pulses, lasers, and Rowhammer attacks. To summarize, FIA can be mounted on most commonly used architectures from ARM, Intel, AMD, by utilizing injection devices that are often below the thousand dollar mark. Therefore, we believe these attacks can be considered practical in many scenarios, especially when the attacker can physically access the target device

My traces learn what you did in the dark: recovering secret signals without key guesses

In side channel attack (SCA) studies, it is widely believed that unprotected implementations leak information about the intermediate states of the internal cryptographic process. However, directly recovering the intermediate states is not common practice in today\u27s SCA study. Instead, most SCAs exploit the leakages in a guess-and-determine way, where they take a partial key guess, compute the corresponding intermediate states, then try to identify which one fits the observed leakages better. In this paper, we ask whether it is possible to take the other way around---directly learning the intermediate states from the side channel leakages. Under certain circumstances, we find that the intermediate states can be efficiently recovered with the well-studied Independent Component Analysis (ICA). Specifically, we propose several methods to convert the side channel leakages into effective ICA observations. For more robust recovery, we also present a specialized ICA algorithm which exploits the specific features of circuit signals. Experiments confirm the validity of our analysis in various circumstances, where most intermediate states can be correctly recovered with only a few hundred traces. To our knowledge, this is the first attempt to directly recover the intermediate states in a completely non-profiled setting. Our approach brings new possibilities to the current SCA study, including building an alternative SCA distinguisher, directly attacking the middle encryption rounds and reverse engineering with fewer restrictions. Considering its potential in more advanced applications, we believe our ICA-based SCA deserves more research attention in the future study

Modelling Delay-based Physically Unclonable Functions through Particle Swarm Optimization

Recent advancements in low-cost cryptography have converged upon the use of nanoscale level structural variances as sources of entropy that is unique to each device. Consequently, such delay-based Physically Unclonable Functions or (PUFs) have gained traction for several cryptographic applications. In light of recent machine learning (ML) attacks on delay-based PUFs, the common trend among PUF designers is to either introduce non-linearity using XORs or input transformations applied on the challenges in order to harden the security of delay-based PUFs. Such approaches make machine learning modelling attacks hard by destroying the linear relationship between challenge-response pairs of a PUF. However, we propose to perceive PUFs, which are fundamentally viewed as Boolean functional mapping, as a set of delay parameters drawn from normal distribution. Using this newfound perception, we propose an alternative attack strategy in this paper. We show that instead of trying to learn the exact functional relationship between challenge-response pairs from a PUF, one can search through the search space of all PUFs to find alternative PUF delay parameter set that exhibits similar behaviour as the target PUF. The core intuition behind this strategy is that one can consider a PUF as a set of stages wherein, depending on the corresponding input challenge bit, one of the several signals within a PUF\u27s stage win a race condition. To utilize this idea, we develop a novel Particle Swarm Optimization based framework inspired by the biomimicry of amoebic reproduction. The proposed algorithm avoids the pitfalls of textbook Genetic Algorithms and demonstrates complete break of existing delay-based PUFs which are based on arbiter chains. More specifically, we are able to model higher-rder $k$-XOR PUF variants which are resistant to all-known ML modelling techniques, including $k=13, 15$ and $20$, without the knowledge of reliability values. In addition to that, we also model PUFs that incorporate input transformation, like variants of IPUF and LP-PUF. Furthermore, we take forward this idea across different search spaces in order to learn a higher order PUF using a lower order (and simpler) PUF architecture. This allows us to explore a novel class of attacks, including modelling a $k$-XOR PUF using a $(k-1)$-XOR PUF as well as bypassing input transformations based PUF designs

Cryptographic key management for the vehicles of tomorrow

The automotive industry is undergoing a major transformation process in which nearly every part of the vehicle is becoming digital and connected. Modern vehicles are often connected to the internet, feature several wireless interfaces and will soon communicate directly with surrounding vehicles and roadside infrastructure using V2X technology. However, this transformation has not yet been paralleled by the development of techniques or standards which address the cyber security challenges posed by these systems. The automotive industry has historically failed to use secure cryptography or appropriate key management techniques and there is no sign that things have improved. In this thesis, we present several new cryptographic and key management flaws in an existing automotive immobiliser system and we develop two new V2X architectures for improving the safety and privacy of tomorrow’s connected and autonomous vehicles. Specifically, we study the AUT64 automotive block cipher and its associated authentication protocol in a real-world immobiliser system. Despite having a 120~bit key, we find a number of flaws in the system which we combine to present several practical key-recovery attacks. Our first new V2X architecture, IFAL, provides a practical and secure improvement to the leading European standard for V2X. IFAL introduces a new certificate issuance mechanism that eliminates the trade-off between pseudonym duration and bandwidth. Our second architecture, VDAA, addresses the need for efficient techniques that preserve vehicle privacy despite dishonest or colluding certificate authorities