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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.

On the Applicability of a Cache Side-Channel Attack on ECDSA Signatures : The Flush+Reload attack on the point multiplication in ECDSA signature generation process

Josyula, Sai Prashanth January 2015 (has links)
Context. Digital counterparts of handwritten signatures are known as Digital Signatures. The Elliptic Curve Digital Signature Algorithm (ECDSA) is an Elliptic Curve Cryptography (ECC) primitive, which is used for generating and verifying digital signatures. The attacks that target an implementation of a cryptosystem are known as side-channel attacks. The Flush+Reload attack is a cache side-channel attack that relies on cache hits/misses to recover secret information from the target program execution. In elliptic curve cryptosystems, side-channel attacks are particularly targeted towards the point multiplication step. The Gallant-Lambert-Vanstone (GLV) method for point multiplication is a special method that speeds up the computation for elliptic curves with certain properties. Objectives. In this study, we investigate the applicability of the Flush+Reload attack on ECDSA signatures that employ the GLV method to protect point multiplication. Methods. We demonstrate the attack through an experiment using the curve secp256k1. We perform a pair of experiments to estimate both the applicability and the detection rate of the attack in capturing side-channel information. Results. Through our attack, we capture side-channel information about the decomposed GLV scalars. Conclusions. Based on an analysis of the results, we conclude that for certain implementation choices, the Flush+Reload attack is applicable on ECDSA signature generation process that employs the GLV method. The practitioner should be aware of the implementation choices which introduce vulnerabilities, and avoid the usage of such ECDSA implementations.

Side Channel Leakage Exploitation, Mitigation and Detection of Emerging Cryptosystems

Chen, Cong 26 March 2018 (has links)
With the emerging computing technologies and applications in the past decades, cryptography is facing tremendous challenges in its position of guarding our digital world. The advent of quantum computers is potentially going to cease the dominance of RSA and other public key algorithms based on hard problems of factorization and discrete logarithm. In order to protect the Internet at post-quantum era, great efforts have been dedicated to the design of RSA substitutions. One of them is code- based McEliece public key schemes which are immune to quantum attacks. Meanwhile, new infrastructures like Internet of Things are bringing the world enormous benefits but, due to the resource-constrained nature, require compact and still reliable cryptographic solutions. Motivated by this, many lightweight cryptographic algorithms are introduced. Nevertheless, side channel attack is still a practical threat for implementations of these new algorithms if no countermeasures are employed. In the past decades two major categories of side channel countermeasures, namely masking and hiding, have been studied to mitigate the threat of such attacks. As a masking countermeasure, Threshold Implementation becomes popular in recent years. It is sound in providing provable side channel resistance for hardware-based cryptosystems but meanwhile it also incurs significant overheads which need further optimization for constrained applications. Masking, especially for higher order masking schemes, requires low signal-to-noise ratio to be effective which can be achieved by applying hiding countermeasures. In order to evaluate side channel resistance of countermeasures, several tools have been introduced. Due to its simplicity, TVLA is being accepted by academy and industry as a one-size-fit-all leakage detection methodolgy that can be used by non-experts. However, its effectiveness can be negatively impacted by environmental factors such as temperature variations. Thus, a robust and simple evaluation method is desired. In this dissertation, we first show how differential power analysis can efficiently exploit the power consumption of a McEliece implementation to recover the private key. Then, we apply Threshold Implementation scheme in order to protect from the proposed attack. This is, to the best of our knowledge, the first time of applying Threshold Implementation in a public key cryptosystem. Next, we investigate the reduction of shares in Threshold Implementation so as to bring down its overhead for constrained applications. Our study shows that Threshold Implementation using only two shares reduces the overheads while still provides reliable first-order resistance but in the meantime it also leaks a strong second-order leakage. We also propose a hiding countermeasure, namely balanced encoding scheme based on the idea of Dual- Rail Pre-charge logic style in hardwares. We show that it is effective to mitigate the leakage and can be combined with masking schemes to achieve better resistance. Finally, we study paired t-test versus Welch's t-test in the original TVLA and show its robustness against environmental noises. We also found that using moving average in computing t statistics can detect higher-order leakage faster.

Side-Channel-Attack Resistant AES Design Based on Finite Field Construction Variation

Shvartsman, Phillip 29 August 2019 (has links)
No description available.

Side Channels in the Frequency Domain / Méthodes d'attaques avancées de systèmes cryptographiques par analyse des émissions EM

Tiran, Sébastien 11 December 2013 (has links)
De nos jours, l'emploi de la cryptographie est largement répandu et les circuits intègrent des primitives cryptographiques pour répondre à des besoins d'identification, de confidentialité, ... dans de nombreux domaines comme la communication, la PayTV, ...La sécurisation de ces circuits est donc un enjeu majeur. Les attaques par canaux cachés consistent à espionner ces circuits par différents biais comme le temps de calcul, la consommation en courant ou les émanations électromagnétiques pour obtenir des informations sur les calculs effectués et retrouver des secrets comme les clefs de chiffrement. Ces attaques ont l'avantage d'être indétectables, peu couteuses et ont fait l'objet des nombreuses études. Dans le cadre des attaques par analyse de la consommation en courant ou des émanations électromagnétiques l'acquisition de bonnes courbes est un point crucial. Malgré la forte utilisation de techniques de prétraitement dans la littérature, personne n'a tenté d'établir un modèle de fuite dans le domaine fréquentiel. Les travaux effectués durant cette thèse se concentrent donc sur cet aspect avec pour intérêt d'améliorer l'efficacité des attaques. De plus, de nouvelles attaques dans le domaine fréquentiel sont proposées, sujet peu étudié malgré l'intérêt de pouvoir exploiter plus efficacement la fuite éparpillée dans le temps. / Nowadays, the use of cryptography is widely spread, and a lot of devices provide cryptographic functions to satisfy needs such as identification, confidentiality, ... in several fields like communication, PayTV, ...Security of these devices is thus a major issue.Side Channel Attacks consist in spying a circuit through different means like the computation time, power consumption or electromagnetic emissions to get information on the performed calculus and discover secrets such as the cipher keys.These attacks have the advantage to be cheap and undetectable, and have been studied a lot.In the context of attacks analysing the power consumption or the electromagnetic emissions, the acquisition of good traces is a crucial point.Despite the high use of preprocessing techniques in the literature, nobody has attempted to model the leakage in the frequency domain.The works performed during this thesis are focusing on this topic with the motivation of improving the efficiency of attacks.What's more, new frequency domain attacks are proposed, subject poorly studied despite the advantage of better exploiting the leakage spread in time.

Differential Power Analysis In-Practice for Hardware Implementations of the Keccak Sponge Function

Graff, Nathaniel 01 June 2018 (has links)
The Keccak Sponge Function is the winner of the National Institute of Standards and Technology (NIST) competition to develop the Secure Hash Algorithm-3 Standard (SHA-3). Prior work has developed reference implementations of the algorithm and described the structures necessary to harden the algorithm against power analysis attacks which can weaken the cryptographic properties of the hash algorithm. This work demonstrates the architectural changes to the reference implementation necessary to achieve the theoretical side channel-resistant structures, compare their efficiency and performance characteristics after synthesis and place-and-route when implementing them on Field Programmable Gate Arrays (FPGAs), publish the resulting implementations under the Massachusetts Institute of Technology (MIT) open source license, and show that the resulting implementations demonstrably harden the sponge function against power analysis attacks.

An Automatable Workflow to Analyze and Secure Integrated Circuits Against Power Analysis Attacks

Perera, Kevin 02 June 2017 (has links)
No description available.

Algorithms and Frameworks for Accelerating Security Applications on HPC Platforms

Yu, Xiaodong 09 September 2019 (has links)
Typical cybersecurity solutions emphasize on achieving defense functionalities. However, execution efficiency and scalability are equally important, especially for real-world deployment. Straightforward mappings of cybersecurity applications onto HPC platforms may significantly underutilize the HPC devices' capacities. On the other hand, the sophisticated implementations are quite difficult: they require both in-depth understandings of cybersecurity domain-specific characteristics and HPC architecture and system model. In our work, we investigate three sub-areas in cybersecurity, including mobile software security, network security, and system security. They have the following performance issues, respectively: 1) The flow- and context-sensitive static analysis for the large and complex Android APKs are incredibly time-consuming. Existing CPU-only frameworks/tools have to set a timeout threshold to cease the program analysis to trade the precision for performance. 2) Network intrusion detection systems (NIDS) use automata processing as its searching core and requires line-speed processing. However, achieving high-speed automata processing is exceptionally difficult in both algorithm and implementation aspects. 3) It is unclear how the cache configurations impact time-driven cache side-channel attacks' performance. This question remains open because it is difficult to conduct comparative measurement to study the impacts. In this dissertation, we demonstrate how application-specific characteristics can be leveraged to optimize implementations on various types of HPC for faster and more scalable cybersecurity executions. For example, we present a new GPU-assisted framework and a collection of optimization strategies for fast Android static data-flow analysis that achieve up to 128X speedups against the plain GPU implementation. For network intrusion detection systems (IDS), we design and implement an algorithm capable of eliminating the state explosion in out-of-order packet situations, which reduces up to 400X of the memory overhead. We also present tools for improving the usability of Micron's Automata Processor. To study the cache configurations' impact on time-driven cache side-channel attacks' performance, we design an approach to conducting comparative measurement. We propose a quantifiable success rate metric to measure the performance of time-driven cache attacks and utilize the GEM5 platform to emulate the configurable cache. / Doctor of Philosophy / Typical cybersecurity solutions emphasize on achieving defense functionalities. However, execution efficiency and scalability are equally important, especially for the real-world deployment. Straightforward mappings of applications onto High-Performance Computing (HPC) platforms may significantly underutilize the HPC devices’ capacities. In this dissertation, we demonstrate how application-specific characteristics can be leveraged to optimize various types of HPC executions for cybersecurity. We investigate several sub-areas, including mobile software security, network security, and system security. For example, we present a new GPU-assisted framework and a collection of optimization strategies for fast Android static data-flow analysis that achieve up to 128X speedups against the unoptimized GPU implementation. For network intrusion detection systems (IDS), we design and implement an algorithm capable of eliminating the state explosion in out-of-order packet situations, which reduces up to 400X of the memory overhead. We also present tools for improving the usability of HPC programming. To study the cache configurations’ impact on time-driven cache side-channel attacks’ performance, we design an approach to conducting comparative measurement. We propose a quantifiable success rate metric to measure the performance of time-driven cache attacks and utilize the GEM5 platform to emulate the configurable cache.

SCA-Resistant and High-Performance Embedded Cryptography Using Instruction Set Extensions and Multi-Core Processors

Chen, Zhimin 28 July 2011 (has links)
Nowadays, we use embedded electronic devices in almost every aspect of our daily lives. They represent our electronic identity; they store private information; they monitor health status; they do confidential communications, and so on. All these applications rely on cryptography and, therefore, present us a research objective: how to implement cryptography on embedded systems in a trustworthy and efficient manner. Implementing embedded cryptography faces two challenges - constrained resources and physical attacks. Due to low cost constraints and power budget constraints, embedded devices are not able to use high-end processors. They cannot run at extremely high frequencies either. Since most embedded devices are portable and deployed in the field, attackers are able to get physical access and to mount attacks as they want. For example, the power dissipation, electromagnetic radiation, and execution time of embedded cryptography enable Side-Channel Attacks (SCAs), which can break cryptographic implementations in a very short time with a quite low cost. In this dissertation, we propose solutions to efficient implementation of SCA-resistant and high-performance cryptographic software on embedded systems. These solutions make use of two state-of-the-art architectures of embedded processors: instruction set extensions and multi-core architectures. We show that, with proper processor micro-architecture design and suitable software programming, we are able to deliver SCA-resistant software which performs well in security, performance, and cost. In comparison, related solutions have either high hardware cost or poor performance or low attack resistance. Therefore, our solutions are more practical and see a promising future in commercial products. Another contribution of our research is the proper partitioning of the Montgomery multiplication over multi-core processors. Our solution is scalable over multiple cores, achieving almost linear speedup with a high tolerance to inter-core communication delays. We expect our contributions to serve as solid building blocks that support secure and high-performance embedded systems. / Ph. D.


Ramesh, Chethan 10 April 2020 (has links)
As FPGA use becomes more diverse, the shared use of these devices becomes a security concern. Multi-tenant FPGAs that contain circuits from multiple independent sources or users will soon be prevalent in cloud and embedded computing environments. The recent discovery of a new attack vector using neighboring long wires in Xilinx SRAM FPGAs presents the possibility of covert information leakage from an unsuspecting user's circuit. The work makes two contributions that extend this finding. First, we rigorously evaluate several Intel SRAM FPGAs and confirm that long wire information leakage is also prevalent in these devices. Second, we present the first successful attack on an unsuspecting circuit in an FPGA using information passively obtained from neighboring long-lines. Information obtained from a single AES S-box input wire combined with analysis of encrypted output is used to rapidly expose an AES key. This attack is performed remotely without modifying the victim circuit, using electromagnetic probes or power measurements, or modifying the FPGA in any way. We show that our approach is effective for three different FPGA devices. Our results demonstrate that the attack can recover encryption keys from AES circuits running at 50MHz. Finally, we present results from the AES attack performed using a cloud FPGA in a Microsoft Project Catapult cluster. These experiments show the effect can be used to attack a remotely-accessed cloud FPGA.

Side-Channel Analysis of AES Based on Deep Learning

Wang, Huanyu January 2019 (has links)
Side-channel attacks avoid complex analysis of cryptographic algorithms, instead they use side-channel signals captured from a software or a hardware implementation of the algorithm to recover its secret key. Recently, deep learning models, especially Convolutional Neural Networks (CNN), have been shown successful in assisting side-channel analysis. The attacker first trains a CNN model on a large set of power traces captured from a device with a known key. The trained model is then used to recover the unknown key from a few power traces captured from a victim device. However, previous work had three important limitations: (1) little attention is paid to the effects of training and testing on traces captured from different devices; (2) the effect of different power models on the attack’s efficiency has not been thoroughly evaluated; (3) it is believed that, in order to recover all bytes of a key, the CNN model must be trained as many times as the number of bytes in the key.This thesis aims to address these limitations. First, we show that it is easy to overestimate the attack’s efficiency if the CNN model is trained and tested on the same device. Second, we evaluate the effect of two common power models, identity and Hamming weight, on CNN-based side-channel attack’s efficiency. The results show that the identity power model is more effective under the same training conditions. Finally, we show that it is possible to recover all key bytes using the CNN model trained only once. / Sidokanalattacker undviker komplex analys av kryptografiska algoritmer, utan använder sig av sidokanalssignaler som tagits från en mjukvara eller en hårdvaruimplementering av algoritmen för att återställa sin hemliga nyckel. Nyligen har djupa inlärningsmodeller, särskilt konvolutionella neurala nätverk (CNN), visats framgångsrika för att bistå sidokanalanalys. Anfallaren tränar först en CNN-modell på en stor uppsättning strömspår som tagits från en enhet med en känd nyckel. Den utbildade modellen används sedan för att återställa den okända nyckeln från några kraftspår som fångats från en offeranordning. Tidigare arbete hade dock tre viktiga begränsningar: (1) Liten uppmärksamhet ägnas åt effekterna av träning och testning på spår som fångats från olika enheter; (2) Effekten av olika kraftmodeller på attackerens effektivitet har inte utvärderats noggrant. (3) man tror att CNN-modellen måste utbildas så många gånger som antalet byte i nyckeln för att återställa alla bitgrupper av en nyckel.Denna avhandling syftar till att hantera dessa begränsningar. Först visar vi att det är lätt att överskatta attackens effektivitet om CNN-modellen är utbildad och testad på samma enhet. För det andra utvärderar vi effekten av två gemensamma kraftmodeller, identitet och Hamming-vikt, på CNN-baserad sidokanalangrepps effektivitet. Resultaten visar att identitetsmaktmodellen är effektivare under samma träningsförhållanden. Slutligen visar vi att det är möjligt att återställa alla nyckelbyte med hjälp av CNN-modellen som utbildats en gång.

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