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Machine learning algorithms based on neural networks have achieved remarkable results and are being extensively used in different domains. However, the machine learning algorithms requires access to raw data which is often privacy sensitive. To address this issue, we develop new techniques to provide solutions for running deep neural networks over encrypted data. In this paper, we develop new techniques to adopt deep neural networks within the practical limitation of current homomorphic encryption schemes. We focus on training and classification of the well-known neural networks and convolutional neural networks. First, we design methods for approximation of the activation functions commonly used in CNNs (i.e. ReLU, Sigmoid, and Tanh) with low degree polynomials which is essential for efficient homomorphic encryption schemes. Then, we train neural networks with the approximation polynomials instead of original activation functions and analyze the performance of the models. Finally, we implement neural networks and convolutional neural networks over encrypted data and measure performance of the models.

With the monetization of user data, data breaches have become very common these days. In the past five years, there were more than 7000 data breaches involving theft of personal information of billions of people. In the year 2020 alone, the global average cost per data breach was $3.86 million, and this number rose to $4.24 million in 2021. Therefore, the need for maintaining data security and privacy is becoming increasingly critical. Over the years, various data encryption schemes including RSA, ECC, and AES are being used to enable data security and privacy. However, these schemes are deemed vulnerable to quantum computers with their enormous processing power. As quantum computers are expected to become main stream in the near future, post-quantum secure encryption schemes are required. To this end, through NIST’s standardization efforts, code-based and lattice-based encryption schemes have emerged as one of the plausible way forward. Both code-based and lattice-based encryption schemes enable public key cryptosystems, key exchange mechanisms, and digital signatures. In addition, lattice-based encryption schemes support fully homomorphic encryption (FHE) that enables computation on encrypted data. Over the years, there have been several efforts to design efficient FPGA-based and ASIC-based solutions for accelerating the code-based and lattice-based encryption schemes. The conventional code-based McEliece cryptosystem uses binary Goppa code, which has good code rate and error correction capability, but suffers from high encoding and decoding complexity. Moreover, the size of the generated public key is in several MBs, leading to cryptosystem designs that cannot be accommodated on low-end FPGAs. In lattice-based encryption schemes, large polynomial ring operations form the core compute kernel and remain a key challenge for many hardware designers. To extend support for large modular arithmetic operations on an FPGA, while incurring low latency and hardware resource utilization requires substantial design efforts. Moreover, prior FPGA solutions for lattice-based FHE include hardware acceleration of basic FHE primitives for impractical parameter sets without the support for bootstrapping operation that is critical to building real-time privacy-preserving applications. Similarly, prior ASIC proposals of FHE that include bootstrapping are heavily memory bound, leading to large execution times, underutilized compute resources, and cost millions of dollars. To respond to these challenges, in this dissertation, we focus on the design of efficient hardware accelerators for code-based and lattice-based public key cryptosystems (PKC). For code-based PKC, we propose the design of a fully-parameterized en/decryption co-processor based on a new variant of McEliece cryptosystem. This co-processor takes advantage of the non-binary Orthogonal Latin Square Code (OLSC) to achieve a lower computational complexity along with smaller key size than that of the binary Goppa code. Our FPGA-based implementation of the co-processor is ∼3.5× faster than an existing classic McEliece cryptosystem implementation. For lattice-based PKC, we propose the design of a co-processor that implements large polynomial ring operations. It uses a fully-pipelined NTT polynomial multiplier to perform fast polynomial multiplications. We also propose the design of a highly-optimized Gaussian noise sampler, capable of sampling millions of high-precision samples per second. Through an FPGA-based implementation of this lattice-based PKC co-processor, we achieve a speedup of 6.5× while utilizing 5× less hardware resources as compared to state-of-the-art implementations. Leveraging our work on lattice-based PKC implementation, we explore the design of hardware accelerators that perform FHE operations using Cheon-Kim-Kim-Song (CKKS) scheme. Here, we first perform an in-depth architectural analysis of various FHE operations in the CKKS scheme so as to explore ways to accelerate an end-to-end FHE application. For this analysis, we develop a custom architecture modeling tool, SimFHE, to measure the compute and memory bandwidth requirements of hardware-accelerated CKKS. Our analysis using SimFHE reveals that, without a prohibitively large cache, all FHE operations exhibit low arithmetic intensity (<1 Op/byte). To address the memory bottleneck resulting from the low arithmetic intensity, we propose several memory-aware design (MAD) techniques, including caching and algorithmic optimizations, to reduce the memory requirements of CKKS-based application execution. We show that the use of our MAD techniques can yield an ASIC design that is at least 5-10× cheaper than the large-cache proposals, but only ∼2-3× slower. We also design FAB, an FPGA-based accelerator for bootstrappable FHE. FAB, for the first time ever, accelerates bootstrapping (along with basic FHE primitives) on an FPGA for a secure and practical parameter set. FAB tackles the memory-bounded nature of bootstrappable FHE through judicious datapath modification, smart operation scheduling, and on-chip memory management techniques to maximize the overall FHE-based compute throughput. FAB outperforms all prior CPU/GPU works by 9.5× to 456× and provides a practical performance for our target application: secure training of logistic regression models. / 2025-01-16T00:00:00Z

Over the recent decades, an increasing amount of new traders has entered the securities markets in order to trade securities such as stocks and bonds on electronic and physical exchanges. This increase in trader activity can largely be attributed to a simpler trading process including the growth of the electronic securities exchanges allowing for more dynamic and global trading platforms. Ever since their introduction, electronic exchanges have grown in terms of volume traded. The underlying trading mechanisms have mostly stayed the same over the years with some additions and improvements. However, over the recent decade, high-frequency traders (HFT) using algorithmic trading have shifted the playing field using practices that many consider unethical. Furthermore, insider trading continues to cause trust issues in certain trading platforms. Multiple solutions to these kinds of unethical trading behaviors have been proposed. Homomorphic encryption has been proposed as a potential preventative mechanism among the proposed solutions. This thesis analyses the properties and effects of a privacy-preserving framework for trading securities on an electronic stock exchange. The method used to evaluate the effects on trading was to implement a framework for handling trading and matching encrypted orders. The framework was then evaluated against its unencrypted counterpart to compare their performance properties in terms of volume handled, amount of orders matched, and timings of certain instructions. Finally, their security properties were analyzed to understand the proposed solution's potential impact on transparency, fairness, and opportunities for financial crime in an electronic securities exchange. The implementation was evaluated on its privacy-preserving properties by evaluating its ability to prevent information disclosure in trading processes. Furthermore, the performance of the implementation was evaluated using a generated trading session to simulate the market with sample trade data. Finally, from the proposed framework and the findings from this evaluation regarding privacy preservation and performance, a conclusion regarding its applicability as an alternative to off-exchange trading and preventative method against unfair practices and financial crime in trading is presented. The evaluation showed that the privacy-preserving and cryptographic properties of the suggested encrypted exchange were reasonably strong and were able to fulfill its goal of preventing unfair advantages in trading stemming from access to plaintext order information. However, the performance of the suggested implementation shows that more work needs to be performed for it to be viable in public electronic stock exchanges, although the solution could be suitable for small scale trading and privacy-preserving auctions.

Homomorphic encryption (HE) enables computations on encrypted data making it possible to perform calculations on a server without sharing the secret key for decryption. HE is relatively new and has seen significant improvements in recent years in terms of speed of encryption, decryption, operations, and the number of operations possible to perform in a row without damaging the ciphertext. These improvements open up new possibilities, such as using HE in voice over IP (VoIP) and still being able to mix audio streams at the server without decrypting them, creating a scalable and secure application.  This thesis evaluates the performance of three HE schemes, BGV, BFV, and CKKS, implemented by the open-source library Palisade and compares their performance to a non-HE scheme AES in terms of encryption time, decryption time and end-to-end latency. Furthermore, the performance of mixing with HE-encrypted audio files is evaluated. The work is a proof-of-concept that allows the user to send audio files of different sample rates and batch sizes to compare the performance. It also investigates the Quality of Experience by measuring the audio quality after the mixing, using PESQ and POLQA. The results show that BGV performs almost as good as AES for higher batch sizes, while BFV performs almost as good in most cases and trails behind in others. CKKS, on the other hand, is the slowest scheme but is still fast enough in some cases to be considered a possible encryption scheme. Furthermore, the tests show that the HE schemes do not decrease the listening quality much according to PESQ and POLQA, as all tests concluded a result that is considered good or excellent. The number of files being mixed had a negative impact on narrowband and wideband audio streams, while it did not affect superwideband and fullband.

<p>Fully homomorphic encryption allows computations to be made on encrypted data without decryption, while preserving data integrity. This feature is desirable in a variety of applications such as banking, search engine and database querying, and some cloud computing services. Despite not knowing the plaintext content of the data, a remote server performing the computation would still be aware of the functions being applied to the data. To address the issue, this thesis proposes a method of encrypting circuits and executing encrypted instructions, by combining fully homomorphic encryption and digital logic theory. We use the classic RISC Archtecture as a foundation of our work, and the result of our algorithm is essentially an encrypted programming language, where a remote server is capable of executing program code that was written and encrypted by a local client.</p> / Master of Science (MS)

Yes / With the advent of Wireless Sensor Networks (WSN) and its immense popularity in a wide range of applications, security has been a major concern for these resource-constraint systems. Alongside security, WSNs are currently being integrated with existing technologies such as the Internet, satellite, Wi-Max, Wi-Fi, etc. in order to transmit data over long distances and hand-over network load to more powerful devices. With the focus currently being on the integration of WSNs with existing technologies, security becomes a major concern. The main security requirement for WSN-integrated networks is providing end-to-end security along with the implementation of in-processing techniques of data aggregation. This can be achieved with the implementation of Homomorphic encryption schemes which prove to be computationally inexpensive since they have considerable overheads. This paper addresses the ID-issue of the commonly used Castelluccia Mykletun Tsudik (CMT) [12] homomorphic scheme by proposing an ID slotting mechanism which carries information pertaining to the security keys responsible for the encryption of individual sensor data. The proposed scheme proves to be 93.5% lighter in terms of induced overheads and 11.86% more energy efficient along with providing efficient WSN scalability compared to the existing scheme. The paper provides analytical results comparing the proposed scheme with the existing scheme thus justifying that the modification to the existing scheme can prove highly efficient for resource-constrained WSNs.

Nachhaltige und ethisch vertretbare Beschaffung und Produktion gehören zu den großen Herausforderungen, die aus dem rasanten Klimawandel und der wachsenden Weltbevölkerung resultieren. Die Erneuerbare-Energien-Richtlinie II der EU und das deutsche Lieferkettensorgfaltspflichtengesetz sind nur zwei Beispiele für die Vielzahl von Gesetzen und Vorschriften, die Standards für nachhaltige und ethisch vertretbare Beschaffung und Produktion vorgeben. Sie implizieren einen Bedarf an Transparenz, Rückverfolgbarkeit und Verifizierbarkeit von Lieferketten und Transaktionen. Öffentliche Verifikationen von Transaktionen entlang von Lieferketten ermöglichen es Dritten, die Einhaltung von Standards und Richtlinien und den Wahrheitsgehalt von Nachhaltigkeitsversprechen zu überprüfen. Folglich kann die öffentliche Überprüfbarkeit Kunden, öffentlichen Stellen und Nichtregierungsorganisationen dabei helfen, Verstöße und Betrug in Lieferketten aufzudecken. Dies wiederum kann dazu beitragen, den Druck zur Einhaltung geltender Standards und Vorschriften zu erhöhen. Transaktionen in Lieferketten basieren oft auf vertraulichen Informationen, wie beispielsweise Mengen und Preise. Die Transparenz derartiger Daten könnte auf Geschäftsgeheimnisse schließen lassen, was direkten Einfluss auf die Wettbewerbsvorteile der beteiligten Firmen hätte. Die Vereinbarkeit von Transparenz und Vertraulichkeit scheint jedoch auf den ersten Blick widersprüchlich zu sein. Diese Dissertation stellt sich der Herausforderung, die öffentliche Verifizierbarkeit von Transaktionen in Lieferketten unter Wahrung der Vertraulichkeit zu ermöglichen. Ausgehend von zwei Fallbeispielen für Lieferketten-Verifikationen werden zunächst Anforderungen an Lösungen untersucht und fünf Forschungsfragen abgeleitet. Anschließend wird eine universelle Lösung entworfen, welche Transparenz und Vertraulichkeit in Einklang bringt. Das vorgestellte Systemmodell ermöglicht sichere öffentliche Verifikationen durch den Einsatz von Fully Homomorphic Encryption (FHE) und Proxy Re-Encryption (PRE). Um die Eignung des Systemmodells für eine Vielzahl realer Szenarien zu verdeutlichen, werden in dieser Dissertation Protokolle für verschiedene Verifikationsfunktionen entworfen. Dies umfasst die Verifikation von Bilanzen, motiviert durch den Handel mit nachhaltigem Palmöl, sowie die Verifikation von Verhältnissen, veranschaulicht durch die Verarbeitung verschiedener Arten von Kobalt. Durch theoretische und empirische Untersuchungen wird nachgewiesen, dass die Protokolle sichere öffentliche Verifikationen für realitätsnahe Szenarien in praktikabler Zeit ermöglichen. Im Weiteren werden die Sicherheitseigenschaften und -implikationen des vorgeschlagenen Systemmodells und der Protokolle untersucht. Dies beinhaltet eine formale Analyse des Risikos, vertrauliche Informationen im Falle wiederholter, gleicher Verifikationen preiszugeben. Aufgrund der Anfälligkeit gegenüber derartigen Angriffen beim Verwenden probabilistischer Output Obfuscation, wird das Paradigma der Data-Dependent Deterministic Obfuscation (D3O) vorgestellt. D3O ist ein universelles Konzept und damit unabhängig vom Anwendungsfall der Lieferketten-Verifikation. Daher kann es in einer Vielzahl weiterer Protokolle für sichere Berechnungen eingesetzt werden, um das Abfließen vertraulicher Informationen zu reduzieren. / Sustainable and ethical sourcing and production are major challenges that arise from rapid climate change and our growing world population. The EU's Renewable Energy Directive II and the German Supply Chain Act are just two examples of the multitude of laws and regulations that define standards for sustainable and ethical sourcing and production. They imply a need for supply chain transparency, traceability, and verification. Public verification of supply chain transactions gives any third-party verifier the chance to evaluate compliance and the correctness of claims based on supply chain transaction details. Therefore, public verification can help customers, buyers, regulators, and non-governmental organizations uncover non-compliance and fraud committed by supply chain actors. This, in turn, can help increase the pressure to comply with applicable standards and regulations. Supply chain transactions often involve confidential data like amounts or prices. Transparency of such data could leak trade secrets and affect companies' competitive advantages. However, reconciling transparency with confidentiality seems contradictory at first glance. This thesis takes up the challenge of enabling privacy-preserving public verification of confidential supply chain transactions. Given two exemplary real-world use cases for supply chain verification, the thesis first investigates requirements for valid solutions and infers five research questions. It then designs a universal solution that combines transparency with confidentiality. The proposed system model achieves privacy-preserving public verification by employing the cryptographic techniques of fully homomorphic encryption (FHE) and proxy re-encryption (PRE). To demonstrate the suitability of the system model for a large variety of lifelike supply chain verification scenarios, the thesis designs privacy-preserving protocols for different verification functions. This includes the verification of balances, using the trade in sustainable palm oil as an example, as well as the verification of ratios, motivated by different forms of cobalt sourcing. These protocols are evaluated both theoretically and empirically. Through extensive empirical evaluation, the proposed protocols prove to enable privacy-preserving public verification for the mentioned supply chain scenarios in practical time. Additionally, this thesis investigates the security implications of the proposed system model and protocols and formally analyzes the risk of leaking information through repeated similar verifications. Based on the identified vulnerability to such attacks in the case of probabilistically obfuscated protocol outputs, the thesis introduces and investigates the paradigm of data-dependent deterministic obfuscation (D3O). D3O is a universal concept that is independent of the field of supply chain verification. It can reduce the leakage of confidential information in a large class of privacy-preserving protocols.

In the Master’s thesis were described privacy protection problems while using cloud technologies. Some of the problems can be solved with help of homomorphic encryption, data splitting or searchable encryption. These techniques were described and compared by provided security, privacy protection and efficiency. The data splitting technique was chosen and implemented in the C language. Afterwards a performance of the implemented solution was compared to AES encryption/decryption performance. An application for secured data storing in cloud was designed and implemented. This application is using the implemented data splitting technique and third-party application CloudCross. The designed application provides command line interface (CLI) and graphical user interface (GUI). GUI extends the capabilities of CLI with an ability to register cloud and with an autodetection of registered clouds. The process of uploading/downloading the data to/from cloud storage is transparent and it does not overload the user with technical details of used data splitting technique.

L’avènement de l’ère digitale a changé la façon dont les individus communiquent à travers le monde, et a amené de nouvelles problématiques en terme de vie privée. La notion d’anonymat la plus répandue pour les communications sur Internet consiste à empêcher tout acteur du réseau de connaître à la fois l’expéditeur d’un message et son destinataire. Bien que ce niveau de protection soit adéquat pour l’utilisateur d’Internet moyen, il est insuffisant lorsqu’un individu peut être condamné pour le simple envoi de documents à une tierce partie. C’est le cas en particulier des lanceurs d’alerte, prenant des risques personnels pour informer le public de pratiques illégales ou antidémocratiques menées par de grandes organisations. Dans cette thèse, nous envisageons un niveau d’anonymat plus fort, où l’objectif est de dissimuler le fait même qu’un utilisateur envoie ou reçoive des données. Pour cela, nous délaissons l’architecture client-serveur couramment utilisée dans les réseaux anonymes, en faveur d’une architecture entièrement distribuée et homogène, où chaque utilisateur remplit également le rôle de serveur relai, lui permettant de dissimuler son propre trafic dans celui qu’il relai pour les autres. Dans cette optique, nous proposons un nouveau protocole pour les communications pairs à pairs sur Internet. À l’aide de récents outils de preuves cryptographiques, nous prouvons que ce protocole réalise les propriétés d’anonymat désirées. De plus, nous montrons par une étude pratique que, bien que le protocole induise une grande latence dans les communications, il assure un fort anonymat, même pour des réseaux de petite taille. / With the development of online communications in the past decades, new privacy concerns have emerged. A lot of research effort have been focusing on concealing relationships in Internet communications. However, most works do not prevent particular network actors from learning the original sender or the intended receiver of a communication. While this level of privacy is satisfactory for the common citizen, it is insufficient in contexts where individuals can be convicted for the mere sending of documents to a third party. This is the case for so-called whistle-blowers, who take personal risks to alert the public of anti-democratic or illegal actions performed by large organisations. In this thesis, we consider a stronger notion of anonymity for peer-to-peer communications on the Internet, and aim at concealing the very fact that users take part in communications. To this end, we deviate from the traditional client-server architecture endorsed by most existing anonymous networks, in favor of a homogeneous, fully distributed architecture in which every user also acts as a relay server, allowing it to conceal its own traffic in the traffic it relays for others. In this setting, we design an Internet overlay inspired from previous works, that also proposes new privacy-enhancing mechanisms, such as the use of relationship pseudonyms for managing identities. We formally prove with state-of-the-art cryptographic proof frameworks that this protocol achieves our privacy goals. Furthermore, a practical study of the protocol shows that it introduces high latency in the delivery of messages, but ensures a high anonymity level even for networks of small size.