Privacy-Aware Processing of Biometric Templates by Means of Secure Two-Party Computation

The use of biometric data for person identification and access control is gaining more and more popularity. Handling biometric data, however, requires particular care, since biometric data is indissolubly tied to the identity of the owner hence raising important security and privacy issues. This chapter focuses on the latter, presenting an innovative approach that, by relying on tools borrowed from Secure Two Party Computation (STPC) theory, permits to process the biometric data in encrypted form, thus eliminating any risk that private biometric information is leaked during an identification process. The basic concepts behind STPC are reviewed together with the basic cryptographic primitives needed to achieve privacy-aware processing of biometric data in a STPC context. The two main approaches proposed so far, namely homomorphic encryption and garbled circuits, are discussed and the way such techniques can be used to develop a full biometric matching protocol described. Some general guidelines to be used in the design of a privacy-aware biometric system are given, so as to allow the reader to choose the most appropriate tools depending on the application at hand

Using Online Services in Untrusted Environments: A Privacy Preserving Architecture

While online service providers are sometimes accused of forwarding identifying customer information as name and address to untrusted third parties, comparatively little attention is paid to the input data that customers provide explicitly to the service. If the input data is sensitive but the service provider is not completely trustworthy, this constitutes a serious privacy problem. From a privacy-defending point of view, the most desirable situation would be for the service not to require any kind of sensitive information at any time, while still yielding useful results for the customer. This paper presents a service architecture that allows for the use of a restricted number of services without requiring the transmission of unencrypted customer data to the service provider. The supported services include the execution of basic database and arithmetic operations that can be combined in numerous useful ways. The basic idea of this architecture is to transform sensitive data on the client side before transferring it to the service provider. The latter processes the transformed data without being able to draw any further conclusions from it. The pseudo-result obtained is returned to the customer who applies a special retransformation to obtain the actual result

Efficient Computation and FPGA implementation of Fully Homomorphic Encryption with Cloud Computing Significance

Homomorphic Encryption provides unique security solution for cloud computing. It ensures not only that data in cloud have confidentiality but also that data processing by cloud server does not compromise data privacy. The Fully Homomorphic Encryption (FHE) scheme proposed by Lopez-Alt, Tromer, and Vaikuntanathan (LTV), also known as NTRU(Nth degree truncated polynomial ring) based method, is considered one of the most important FHE methods suitable for practical implementation. In this thesis, an efficient algorithm and architecture for LTV Fully Homomorphic Encryption is proposed. Conventional linear feedback shift register (LFSR) structure is expanded and modified for performing the truncated polynomial ring multiplication in LTV scheme in parallel. Novel and efficient modular multiplier, modular adder and modular subtractor are proposed to support high speed processing of LFSR operations. In addition, a family of special moduli are selected for high speed computation of modular operations. Though the area keeps the complexity of O(Nn^2) with no advantage in circuit level. The proposed architecture effectively reduces the time complexity from O(N log N) to linear time, O(N), compared to the best existing works. An FPGA implementation of the proposed architecture for LTV FHE is achieved and demonstrated. An elaborate comparison of the existing methods and the proposed work is presented, which shows the proposed work gains significant speed up over existing works

On Fully Homomorphic Encryption

Täielikult homomorfne krüpteerimine on krüptosüsteem, mille puhul üks osapool saab enda valdusesse krüpteeritud andmed ning saab nende andmetega tõhusalt sooritada erinevaid operatsioone. Operatsioone saab teha hoolimata sellest, et andmed jäävad krüpteerituks ning seega ei ole ka vajalik teada dekrüpteerimisvõtit. Selline süsteem oleks äärmiselt kasulik, näiteks tagades andmete privaatsuse, mis on saadetud kolmanda osapoole teenusele. Täielikult homomorfne krüpteerimine on vastandiks krüptosüsteemidele nagu Paillier, kus ei ole võimalik teostada krüpteeritud andmete peal korrutamist ilma neid enne dekrüpteerimata, või ElGamal, kus ei saa sooritada krüpteeritud andmete liitmist enne andmete dekrüpteerimist. Täielikult homomorfne krüpteerimine on väga uus uurimisala: esimese taolise süsteemi lõi Gentry aastal 2009. Gentry läbimurdest alates on olnud palju tema tööst inspireeritud edasiminekuid. Kõik viimased täielikult homomorfsed krüptosüsteemid kasutavad avaliku võtmega krüptograafiat ja põhinevad võredel. Võre-põhine krüptograafia äratab üha enam huvi oma turvalisuse püsimisega kvantarvutites ning oma halvima juhu turvagarantiidega. Siiski jääb püsima peamine probleem: süsteemidel ei ole veel tõhusat teostust, mis säilitaks adekvaatsed turvalisuse nõuded. Selles valguses vaadatuna, viimased edasiminekud täielikult homomorfses krüpteerimises kas täiendavad eelnevate süsteemide tõhusust või pakuvad välja uue parema efektiivsusega skeemi. Antud uurimus on ülevaade hiljutistest täielikult homomorfsetest krüptosüsteemidest. Õpime tundma mõningaid viimaseid täielikult homomorfseid krüptosüsteeme, analüüsime ning võrdleme neid. Neil süsteemidel on teatud ühised elemendid: 1. Tõhus võre-põhine krüptosüsteem turvalisusega, mis põhineb üldteada võreprobleemide keerulisusel. 2. Arvutusfunktsioon definitsioonidega homomorfsele liitmisele ja korrutamisele müra kasvu piiramiseks. 3. Meetodid, et muuta süsteem täielikult homomorfseks selle arvutusfunktsiooniga. Niipea kui võimalik, kirjutame nende süsteemide peamised tulemused ümber detailsemas ja loetavamas vormis. Kõik skeemid, mida me arutame, välja arvatud Gentry, on väga uued. Kõige varasem arutletav töö avaldati oktoobris aastal 2011 ning mõningad tööd on veel kättesaadavad ainult elektroonilisel kujul. Loodame, et käesolev töö aitab lugejail olla kursis täielikult homomorfse krüpteerimisega, rajades teed edasistele arengutele selles vallas

Harnessing the Power of Distributed Computing: Advancements in Scientific Applications, Homomorphic Encryption, and Federated Learning Security

Data explosion poses lot of challenges to the state-of-the art systems, applications, and methodologies. It has been reported that 181 zettabytes of data are expected to be generated in 2025 which is over 150\% increase compared to the data that is expected to be generated in 2023. However, while system manufacturers are consistently developing devices with larger storage spaces and providing alternative storage capacities in the cloud at affordable rates, another key challenge experienced is how to effectively process the fraction of large scale of stored data in time-critical conventional systems. One transformative paradigm revolutionizing the processing and management of these large data is distributed computing whose application requires deep understanding. This dissertation focuses on exploring the potential impact of applying efficient distributed computing concepts to long existing challenges or issues in (i) a widely data-intensive scientific application (ii) applying homomorphic encryption to data intensive workloads found in outsourced databases and (iii) security of tokenized incentive mechanism for Federated learning (FL) systems.The first part of the dissertation tackles the Microelectrode arrays (MEAs) parameterization problem from an orthogonal viewpoint enlightened by algebraic topology, which allows us to algebraically parametrize MEAs whose structure and intrinsic parallelism are hard to identify otherwise. We implement a new paradigm, namely Parma, to demonstrate the effectiveness of the proposed approach and report how it outperforms the state-of-the-practice in time, scalability, and memory usage.The second part discusses our work on introducing the concept of parallel caching of secure aggregation to mitigate the performance overhead incurred by the HE module in outsourced databases. The key idea of this optimization approach is caching selected radix-ciphertexts in parallel without violating existing security guarantees of the primitive/base HE scheme. A new radix HE algorithm was designed and applied to both batch and incremental HE schemes, and experiments carried out on six workloads show that the proposed caching boost state-of-the-art HE schemes by high orders of magnitudes.In the third part, I will discuss our work on leveraging the security benefit of blockchains to enhance or protect the fairness and reliability of tokenized incentive mechanism for FL systems. We designed a blockchain-based auditing protocol to mitigate Gaussian attacks and carried out experiments with multiple FL aggregation algorithms, popular data sets and a variety of scales to validate its effectiveness