24 research outputs found
Introduction to sugar technology; rev. ed.
No full textDocument uit de collectie Chemische ProcestechnologieDelftChemTechApplied Science
NFTs For 3D Models: Sustaining Ownership In Industry 4.0
No full text© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. This article was originally published in IEEE Consumer Electronics Magazine. The version of record is available at: https://doi.org/10.1109/MCE.2022.3164221.Digital manufacturing (DM) is actively adopted to the production lifecycles of a variety of critical industries, and this rapid growth has resulted in exponential increase of 3D computer-aided design (CAD) models. Unfortunately, counterfeiting of intellectual property becomes a prominent threat as many 3D designs are accessible online, combined with the proliferation of cheap consumer 3D printers that enable malicious actors to produce non-authentic parts. State-of-the-art techniques to secure manufacturing processes mostly rely on watermarking, which embeds hidden information inside CAD models to prove ownership and authenticity. Nevertheless, such techniques tamper with the model itself, while existing attacks allow removing such watermarks altogether. To address these shortcomings, we integrate signal processing and cryptographic techniques and describe a tailored solution for CAD model ownership and supply chain management. Our approach generates unique identifiers for 3D designs using frequency-domain transforms and employs non-fungible tokens (NFTs) that persist on public distributed ledgers. Our NFTs are implemented on the Ethereum blockchain using smart contracts and their functionality is twofold: (a) authenticate the owner of a CAD model, and (b) enable ownership transfer. To validate our technique, we deployed our smart contract on Ethereum's proof-of-work Ropsten network and demonstrated the applicability of our methodology.This article is based upon work supported by the National Science Foundation (NSF) under Grant CMMI-1931916. Any opinions, findings, and conclusions or recommendations expressed in this article are those of the authors and do not necessarily reflect the views of NSF
Masquerade: Verifiable Multi-Party Aggregation with Secure Multiplicative Commitments
No full textIn crowd-sourced data aggregation over the Internet, participants share their data points with curators. However, a lack of strong privacy guarantees may discourage participation, which motivates the need for privacy-preserving aggregation protocols. Moreover, existing solutions remain limited with respect to public auditing without revealing the participants\u27 data. In realistic applications, however, there is an increasing need for public verifiability (i.e., verifying the protocol correctness) while preserving the privacy of the participants\u27 inputs, since the participants do not always trust the data curators. At the same time, while publicly distributed ledgers may provide public auditing, these schemes are not designed to protect sensitive information.
In this work, we introduce two protocols, dubbed Masquerade and zk-Masquerade, for computing private statistics, such as sum, average, and histograms, without revealing anything about participants\u27 data. We propose a tailored multiplicative commitment scheme to ensure the integrity of data aggregations and publish all the participants\u27 commitments on a ledger to provide public verifiability. zk-Masquerade detects malicious participants who attempt to poison the aggregation results by adopting two zero-knowledge proof protocols that ensure the validity of shared data points before being aggregated and enable a broad range of numerical and categorical studies. In our experiments, we use homomorphic ciphertexts and commitments for a variable number of participants and evaluate the runtime and the communication cost of our protocols
Zilch: A Framework for Deploying Transparent Zero-Knowledge Proofs
No full textAs cloud computing becomes more popular, research has focused on usable solutions to the problem of verifiable computation (VC), where a computationally weak device (Verifier) outsources a program execution to a powerful server (Prover) and receives guarantees that the execution was performed faithfully. A Prover can further demonstrate knowledge of a secret input that causes the Verifier’s program to satisfy certain assertions, without ever revealing which input was used. State-of-the-art Zero-Knowledge Proofs of Knowledge (ZKPK) methods encode a computation using arithmetic circuits and preserve the privacy of Prover’s inputs while attesting the integrity of program execution. Nevertheless, developing, debugging and optimizing programs as circuits remains a daunting task, as most users are unfamiliar with this programming paradigm.
In this work we present Zilch, a framework that accelerates and simplifies the deployment of VC and ZKPK for any application transparently, i.e., without the need of trusted setup. Zilch uses traditional instruction sequences rather than static arithmetic circuits that would need to be regenerated for each different computation. Towards that end we have implemented ZMIPS: a MIPS-like processor model that allows verifying each instruction independently and compose a proof for the execution of the target application. To foster usability, Zilch incorporates a novel cross-compiler from an object-oriented Java-like language tailored to ZKPK and optimized our ZMIPS model, as well as a powerful API that enables integration of ZKPK within existing C/C++ programs. In our experiments, we demonstrate the flexibility of Zilch using two real-life applications, and evaluate Prover and Verifier performance on a variety of benchmarks
Quantum Enhanced Accelerometer using NV Centres in Diamond
No full textSilicon accelerometers used in the automotive industry should be improved in resolution and accuracy. Exploiting quantum effects in diamond to improve sensing accuracy is a popular technique for nanoscale sensing applications. This thesis will present a new design concept for an accelerometer using these quantum effects for sensing on a macroscopic scale. This sensor can sense these forces with a resolution of 6g and a range of 120g. In measurement time it is slower than current sensors, but our sensor can still serve as a prototype to be improved in the future
Zebro Drive System
No full textDit document beschrijft de ontwerpkeuzes die gemaakt zijn bij het ontwerpen van het systeem dat zorgt voor de voortbeweging van de Zebro. De 'Zebro Explorer' is een robot die gemaakt wordt om mee te doen aan de European Rover Challenge. Voor deze wedstrijd dient een Mars rover equivalent gebouwd te worden die verschillende taken kan uitvoeren, zoals het nemen van grondmonsters, het vervoeren daarvan en het instellen en in werking stellen van een reactor. De beschreven ontwerpkeuzes betreffen de motor met bijbehorende motorbesturing, zowel de hardware als de software.ElectronicaElectronicaElectrical Engineering, Mathematics and Computer Scienc
Privacy-Preserving IP Verification
No full textThe rapid growth of the globalized integrated circuit (IC) supply chain has drawn the attention of numerous malicious actors that try to exploit it for profit. One of the most prominent targets of such parties is the third-party intellectual property (3PIP) vendors and their circuit designs. With the increasing number of transactions between vendors and system integrators, the threat of IP reuse and piracy has become a significant consideration for the IC industry. What is more, the correctness of 3PIP designs should be verified before integration, imposing another challenge for 3PIP vendors since they have to prove the functionality of their designs to system integrators while protecting the privacy of the circuit implementations. To eliminate this deadlock, we utilize the cryptographic technique of \u27zero-knowledge proofs\u27 to enable 3PIP vendors to convince system integrators about various functional properties of a circuit (e.g., area, power, frequency) without disclosing its netlist (i.e., in zero-knowledge). Our approach comprises a circuit compiler that transforms arbitrary netlists into a zero knowledge-friendly format and a library of modules that provide cryptographic guarantees for various properties of the netlist while hiding the actual gates. We evaluate our method using combinational and sequential circuits from the ISCAS and ITC benchmark suites
TERMinator Suite: Benchmarking Privacy-Preserving Architectures
No full textSecurity and privacy are fundamental objectives characterizing contemporary cloud computing. Despite the wide adoption of encryption for protecting data in transit and at rest, data in use remains unencrypted inside cloud processors and memories, as computation is not applicable on encrypted values. This limitation introduces security risks, as unencrypted values can be leaked through side-channels or hardware Trojans. To address this problem, encrypted architectures have recently been proposed, which leverage homomorphic encryption to natively process encrypted data using datapaths of thousands of bits. In this case, additional security protections are traded for higher performance penalties, which drives the need for more efficient architectures. In this work, we develop benchmarks specifically tailored to encrypted computers, to enable comparisons across different architectures. Our benchmark suite, dubbed TERMinator, is unique as it avoids \u27termination problems\u27 that prohibit making control-flow decisions and evaluating early termination conditions based on encrypted data, as these can leak information. Contrary to generic suites that ignore the fundamental challenges of encrypted computation, our algorithms are tailored to the security primitives of the target encrypted architecture, such as the existence of branching oracles. In our experiments, we compiled our benchmarks for the Cryptoleq architecture and evaluated their performance for a range of security parameters
: Privacy-Preserving IP Verification Using Logic Locking and Secure Multiparty Computation
No full textThe global supply chain involves multiple independent entities, and potential adversaries can exploit different attack vectors to steal proprietary designs and information. As a result, intellectual property (IP) owners and consumers have reasons to keep their designs private. Without a trusted third party, this mutual mistrust can lead to a deadlock where IP owners are unwilling to disclose their IP core before a financial agreement is reached, while consumers need assurance that the proprietary design will meet their integration needs without compromising the confidentiality of their test vectors. To address this challenge, we introduce an efficient framework called MPloC that resolves this deadlock by allowing owners and consumers to jointly evaluate the target design with consumer-supplied test vectors while preserving the privacy of both the IP core and the inputs. MPloC is the first work that combines secure multiparty computation (MPC) and logic-locking techniques to accomplish these goals. Our approach supports both semi-honest and malicious security models to allow users to balance stronger security guarantees with performance. We compare our approach to existing state-of-the-art works that utilize homomorphic encryption across several benchmarks and report runtime improvements of more than two orders of magnitude
