In most practical cloud computing applications such as e-voting, auctions, health, and financial applications or cloud services in common, to prove the exactness of outsourced data is one of the major needs today. Most of the time, third party auditing is employed for this task. This auditing work is controlled by assigning the secret inputs to an entity trusted third party, or worker, who is liable for performing computations and hand over the result of the computation to the cloud users or clients. To verify the integrity of computations using traditional cryptographic techniques, the time required to generate and validate the proof is a major computation issue. This paper proposes an improved public auditing technique for multi-party computation to check the integrity of outsourced data using a cryptographic solution. Many researchers have given auditing protocols that generate and verify proof using a cryptographic solution. Most of these scheme uses Non-Interactive Zero-Knowledge Proof (NIZK) which are basically built on bilinear map technology. The verification time using these existing technique is computationally expensive which affect the performance of the auditing system. We propose an efficient protocol that verifies the result correctness using modern cryptographic technique Indistinguishability Obfuscation. The proposed system works in two phases, (i) auction and (ii) audit. During the auction phase, multiple clients share their encrypted bid value to the worker. The worker generates auction result and proof using Pedersen Commitment Scheme. The audit phase starts only after the completion of the auction phase which results in reduced verification time. During the Audit phase, clients can verify the integrity of results using NIZK with the IO technique. The results for reduced verification time in auction system have been presented. It is found that the performance of the proposed system has improved compared to the pertinent NIZK Proof technique. In our setting, we assumed that a worker is one of the trusted entity. By this notion, our protocol also guarantees privacy to the clients during the audit phase.
Patent ductus arteriosus (PDA) is a common finding in preterm infants. Some PDAs will close spontaneously but those that remain open can be associated with significant morbidities and mortality.1-4 The current standard of care to treat a hemodynamically significant PDA (hsPDA) is to use either intravenous (IV) ibuprofen or IV indomethacin. These medicines have a nonselective mechanism of COX inhibition which can lead to side effects.5-7 To avoid this, researchers have explored using acetaminophen, which has COX-2 selectivity.8, 9 Recent studies using enteral acetaminophen for PDA closure have suggested that it is safe and effective.5, 6, 10, 11 The diagnosis of a hsPDA is confirmed by echocardiogram which evaluates size of the PDA and stress on the heart. B-type natriuretic peptide (BNP) levels produced in the ventricles of the heart rise in response to stretch from volume overload and have been used in previous studies to help determine the efficacy of ibuprofen treatment for a hsPDA.12-14 Studies evaluating the efficacy of enteral acetaminophen for PDA closure have not reported BNP levels. The efficacy of intravenous acetaminophen for closure of a hsPDA is unknown. We developed a proof of concept study to assess whether IV acetaminophen can be effective at closing a hsPDA using echocardiogram and BNP data as outcome measures. Infants 23 0/7 weeks through 29 6/7 weeks at birth with a hsPDA diagnosed by echocardiogram within the first 2 weeks of life were recruited in the neonatal intensive care unit at the Bernard and Millie Duker Children's Hospital at Albany Medical Center in Albany, NY. Written parental consent was obtain prior to randomization. This study was approved by the Institutional Review Board and registered on clinicaltrials.gov (NCT03008876). Five infants were randomized to each treatment group (10 infants total). The IV ibuprofen group received three doses: a loading dose of 10 mg/kg/dose on the first day followed by 5 mg/kg/dose on the second and third day. The IV acetaminophen group received 12 doses: 15 mg/kg/dose administered every 6 hours (total 3 days). Infants with any of the following were excluded: sepsis and/or meningitis, necrotizing enterocolitis, intestinal perforation, major congenital heart disease, major congenital malformations or disorders, fetal hydrops, pulmonary hypertension, grade 3 or 4 intraventricular hemorrhage, evidence of acute renal injury, thrombocytopenia, prior treatment with a prostaglandin, or of their aspartate transaminase (AST) and alanine transaminase (ALT) levels were twice the upper limits of normal. The primary outcome was PDA closure. Echocardiograms were performed for initial diagnosis and then 1 day after study drug completion. The ductus was graded as large, moderate, small, or closed, taking into consideration the LA: Ao ratio, the ductal diameter, and the doppler flow pattern through the PDA. The secondary outcome was BNP level. BNP levels were obtained before and after treatment on the same day that the echocardiogram was performed and were not known to the medical team. Serum chemistries, complete blood count (CBC), AST/ALT, and bilirubin levels were performed before, during, and after the study drug was administered. If values were abnormal, the attending neonatologist could halt the medication administration. Group sizes were too small for statistical analysis of change in PDA size. BNP levels were analyzed using both a repeated measures ANOVA and Wilcoxon signed rank tests. Nineteen infants were eligible from January 2017 through May 2019. Ten infants were ultimately randomized after informed consent was obtained: five received IV acetaminophen and five received IV ibuprofen (Figure 1). Demographic characteristics were similar in each group (Table 1). PDA closure was observed in two of the five infants in the IV acetaminophen group vs zero of five infants in the IV ibuprofen group. An additional infant in the IV acetaminophen group had a PDA that became smaller post study drug and then received two additional courses of IV ibuprofen. After the third course, the PDA was still present; however, it was closed on the echocardiogram prior to discharge. Of the remaining two infants in the IV acetaminophen group, one received two additional courses without improvement and underwent a PDA ligation, and the other infant did not undergo any additional treatment and the ductus was closed on a later echocardiogram (see Table 2). In the IV ibuprofen group, two of the five infants were noted to have smaller PDAs after the initial course. However, all five infants received additional courses of medication. Three infants had two additional courses of treatment (two of those received one course each of IV acetaminophen and IV ibuprofen and the third infant received two courses of IV ibuprofen), one infant had three additional courses (two IV ibuprofen, one IV acetaminophen), and the last infant had one additional course (IV ibuprofen) (see Table 2). Five infants in the ibuprofen group and two in the acetaminophen group, required subsequent pharmacologic therapy. The hsPDA closure rate at discharge (not including those that underwent PDA ligation), for infants in the IV acetaminophen group was higher compared to the IV ibuprofen group. A repeated measures ANOVA analysis on BNP levels showed a significant decrease in BNP levels pre and post-treatment, regardless of the study group (P = .01). There was a greater decrease in median BNP level after treatment in the IV acetaminophen group as compared to the IV ibuprofen group (P = .07 vs P = .17, respectively) (Figure 2). Creatinine, AST/ALT, and fractionated bilirubin levels were all found to be within normal limits before, during, and after the study drug course in both groups. There were no cases of NEC or GI bleeding. In this study the efficacy of acetaminophen in closing a PDA was evaluated. IV acetaminophen was used in our study, in comparison to many of the previous studies which used an enteral form, as we theorized a preterm infant's immature digestive system may alter enteral absorption and lead to lower serum concentrations and possible decreased efficacy in closing a PDA. Our results suggest that IV acetaminophen can successfully close a hsPDA. It was interesting to note that we saw no hsPDA closures from IV ibuprofen. The mean start day of treatment in this study was greater than previous studies which may explain lack of closure seen here as those infants who were treated earlier may have had a hsPDA that would have closed on its own. Since many are now using a watchful waiting approach to PDA management, the results in this study may be more reflective of the current outcomes with medical management.15 There was a decrease in cardiac stress (as measured by BNP level) in both groups, although greater in the acetaminophen group. To our knowledge, this is the first study to include BNP levels to assess the efficacy of acetaminophen on PDA closure. This study suggests that IV acetaminophen can be used as an alternative medication to close a hsPDA without adverse effects. The major limitation to this study was its small sample size and large scale studies are needed but will be challenging due to the current watchful waiting trend leading to decreased numbers of infants being treated. In addition to a larger number of patients, it would useful to address the optimal dose and duration of IV acetaminophen for PDA closure as well as the long-term safety and potential effects on neurodevelopment. Bin-Nun et al16 reported that a serum acetaminophen concentration > 20 mg/L was 100% sensitive and specific for ductal closure in their small cohort of preterm infants. However, McPherson et al17 found no correlation between serum concentration and ductal size post-treatment. The authors want to express their appreciation to James Cummings, MD, MA, and Joaquim Pinheiro, MD, MPH, for their help in preparing this manuscript. This work was funded by grants from The Gerber Foundation and Quidel, Inc. The funders did not have a role in the study design or implementation, running of the samples, analysis of the data, or writing of this manuscript. The authors declare no conflicts of interest. Conceptualization: Kate A. Tauber, Ronnelle King, Michael Colon Formal Analysis: Kate A. Tauber, Ronnelle King, Michael Colon Funding Acquisition: Kate A. Tauber Investigation: Kate A. Tauber, Ronnelle King, Michael Colon Methodology: Kate A. Tauber, Ronnelle King, Michael Colon Project Administration: Kate A. Tauber Supervision: Kate A. Tauber Visualization: Kate A. Tauber Writing – original draft preparation: Kate A. Tauber Writing – review and editing: Kate A. Tauber, Ronnelle King, Michael Colon All authors have read and approved the final version of this manuscript. Kate A. Tauber had full access to all of the data in the study and takes complete responsibility for the integrity of the data and the accuracy of the data analysis. Kate A. Tauber affirms that this manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned have been explained. Deidentified data from this study will be shared following publication with those individuals who have approval from an institutional review board (IRB) from their institution and approval from the IRB at our institution. Persons requesting data will need to sign a data access agreement. If interested in obtaining the data from this study please contact tauberk@amc.edu.
Abstract Currently, attribute-based authentication provides a feasible solution for fine-grained access control in cloud environment. However, the existing schemes can not solve the following problems at the same time, that is, how to ensure that the computation cost of the client does not depend on the size of underlying access structure, and how to introduce distributed authorities to manage and maintain the attribute universe. To solve the above problems, an efficient multi-authority attribute-based authentication scheme is proposed. The new scheme uses the technique of distributed attribute-based encryption to realize the access control of anonymous users, and reduces users’ computation burden by optimizing the standard implementation zero-knowledge proof and outsourcing users’ computing tasks in the authentication stage. Under the new definition of security, it can be proved that the new scheme is secure and satisfies many attractive properties, such as introducing distributed authorities, supporting outsourcing computation, satisfying attribute anonymity.
In this issue of Cytometry A, Zhao et al. (page 1073–1080) report on their work to diagnose leukemic B cell non-Hodgkin's Lymphoma from flow cytometry (FCM) raw data of blood and bone marrow samples using a dedicated computer approach, which would assign one of eight B-cell lymphoma diagnoses or “normal” to a sample. A remarkable of level of classification performance could be achieved in the validation set. For the “true” classification of B-cell lymphomas, conventional diagnostics had incorporated morphology, FCM and additional information from histology and genetics if needed, whereas computer diagnosis was derived from FCM data alone. In this context, uncertainty to delineate, for example, monoclonal B-cell lymphocytosis from chronic lymphocytic leukemia or to subclassify a B-cell malignancy as either mantle cell lymphoma or prolymphocytic leukemia is not an outright error, but is rather based on the limitations of FCM itself. Furthermore, cell populations tagged as abnormal by the algorithm and color-coded accordingly in conventional plots can help human diagnosticians to review and fine-tune the diagnosis. However, some lymphomas (most prominent in follicular lymphoma) were classified as normal by the algorithm. Vice versa, only few samples classified as “normal” by human diagnosticians were classified as lymphoma by the algorithm. Thus, a deficit in sensitivity exists, which is clinically relevant. Computer support is instrumental for the analysis of FCM data, because nobody is able to draw conclusions from raw list mode files. However, conventional FCM computer programs execute relative simple tasks to support the workflow of a human researcher or diagnostician. In a typical workflow, several sequential steps have to be performed (Fig. 1, left side). Fluorescence spillover compensation is calculated from control samples. One-dimensional transformation of raw data (logarithmic, logical, possibly a shift of zero and negative values to some defined minimum, etc.) is routinely performed on fluorescence channels. Data are displayed in histograms or two-dimensional plots. Starting gates are used to look for artifacts and to remove debris and cells not of interest. A considerable number of plots are necessary, if several fluorochromes are used and several populations are of interest. Data from several samples with identical panel may be displayed in parallel in an overlay. Cells are tagged according to gates in these plots and may then be displayed separately and/or color-coded. Hierarchical and/or Boolean gating strategies are used for the definition of cell populations and subpopulations of interest. Cell numbers and antigen expression of these cell populations of interest constitute the readout of a single tube. A final result or diagnosis is derived assessing this readout or the synopsis of the readout of several tubes. All of the calculations in such a manual workflow are based on straight “if A then B” logic, performing calculations on a maximum of two parameters concurrently. Conventional FCM computer support aims at displaying data in a clear manner to the human operator, especially effects of manipulation in two-parameter plots upon plots of other parameters, but not at automation. The most advanced process in standard applications is the calculation of fluorescence spillover compensation, which nowadays usually is performed in some (semi-) automated fashion. However, although every single step in this procedure is quite straightforward, due to the multitude of plots and gates from current 10 to 14 parameter FCM data, important information may be missed. In the recent decades, many attempts have been reported to introduce more advanced computation methods into histology, cytopathology, image cytometry and conventional FCM analysis (1, 2). These algorithms will be called artificial intelligence (AI) from here, although some of them do not deserve this name in its strict sense. Two strategies, sometimes overlapping, are applied in these attempts: firstly, AI may be used to automatize conventional data processing and analysis as described above in order to reduce the workload for the investigator, reduce bias using standardized procedures, and speed up analyses. To this end, regarding FCM, algorithms search for minimal values in distributions to define optimal positions for gates to divide populations or search for appropriate cut off values to gate out debris. Furthermore, normalization algorithms can be applied to level out differences due to instrument settings or biological variations in sets of multiple similar data. Many of these algorithms are available in the Bioconductor “flow Core” FCM package implemented in R (3). Secondly, new methods were introduced that go beyond the sequential analysis of two-dimensional plots and base calculations on more parameters of the higher-dimensional space in parallel, which is a crucial need nowadays, when standard cytometers report 10 to 14 parameters per cell and dedicated research instruments up to over 100 parameters. Such algorithms can either substitute conventional strategies, for example, to gate cell populations and read out antigen expression levels or they can be used to extract information from the raw data that is not accessible by conventional gating (4). One of the prominent tasks within an FCM workflow is to define cell populations within a mixture of different cells (“clustering”) that may be of interest for research or diagnosis. AI can directly use higher dimensional data as input for cell clustering or it can perform dimensionality reduction and data visualization, for example, by tSNE or one of its variants (5, 6) or SOM (7), the latter already including some clustering of the data. After dimensionality reduction, population clustering can be added by separate AI algorithms or a human operator can take over for this task, integrating the output of the dimensionality reduction and conventional gating. Many different algorithms are able to solve the task of clustering in an automated fashion either performing a two-step procedure integrating dimension reduction and subsequential clustering or direct clustering of higher dimensional data; however, as shown in the FlowCAP challenges, results are not unequivocal, especially, if the number of clusters is not defined a priori, and differences remain between different algorithms and human experts. Up to now, no perfect automatic solution for cell clustering exists, although many solutions perform quite well (7). Furthermore, clustering revealing further information on relatedness between populations has been suggested for a multitude of different research questions, for example, cellular developmental trajectories, and has been optimized according to these special tasks (further Ref. in 4). Furthermore, metadata extracted from raw FCM data may also be clustered, for example, in order to define diagnostic or prognostic subgroups (8). Whereas unsupervised clustering can be helpful for many exploratory research questions to identify cell populations and subpopulations, for medical diagnostic purposes supervised AI methods have been described, that use external information such as diagnoses or outcome to train the AI, for example, using support vector machines or neural networks. All of these strategies rely on a large dataset for training and may incorporate more or less steps from a conventional workflow (4, 9, 10). Manual gating and tagging of cell populations may be used for training of the AI (11) or AI may be trained using only the final results, that is, diagnosis, as described, for example, in Ref. (12) or in the work by Zhao et al. discussed here. Several AI strategies have been able to discern overt acute myeloid leukemia (AML) from normal samples with a high success rate in the second FlowCap challenge (7), however, this can be a considered a quite simple task, since overt AML is easily characterized by a large abnormal population of blast or sometimes monocytic cells. In contrast, separation of AML from myelodysplastic syndromes or from acute lymphoblastic leukemia, everyday questions in diagnostics, is less trivial. In contrast to simplified “yes or no” tasks, Zhao et al. tackled a much more realistic question: to deduce a specific diagnosis from FCM panels as they are used in conventional diagnostics. They achieved this goal without an attempt to mimic a conventional human FCM workflow. They transformed the FCM data by self-organizing maps (SOM) and classified these representations by a convolutional neural network (CNN), dealing with each tube separately first and finally with data from all three tubes. The researchers took advantage of a very large database of patient sample FCM data. Data from more than 18,000 samples analyzed in a uniform fashion with identical antibody combinations and more than 200 samples of the rarest subtype of lymphoma could be used to train the CNN. In order to get some insight into the CNN “black box,” they checked, which markers were of most importance for the AI to classify a specific diagnosis correctly and they had cell populations tagged that were detected to be abnormal and discriminative by the algorithm for the respective disease in a way to understand the AI's decision (and to use this assignment for a possible refinement by a human diagnostician in practical diagnostic use in the future). As described above, the results of their approach are remarkable, but a problem in sensitivity to detect all true lymphoma cases remains, which is most prominent for follicular lymphoma. Maybe the CNN could be trained in a way, that the correct distinction B-NHL of any type versus normal is assigned a higher weight compared to B-NHL subtyping. If we inspect the importance of single markers for AI performance in Supporting Figure 5, we note that some diagnosis assignments rely heavily on a few markers, whereas other diagnoses seem to rather depend on the distribution of many markers. Interestingly, the latter diagnoses without dependence on dominant markers have the highest rate of falsely being categorized as normal (follicular lymphoma, marginal zone lymphoma, lymphoplasmactic lymphoma). Furthermore, for a human diagnostician, an imbalance of kappa versus lambda light chain expression on B cells is a very important clue for a diagnosis of B-cell lymphoma, whereas the CNN of Zhao et al. does not seem to rely heavily on this information. In a different approach, to detect minimal residual disease in childhood acute leukemia, conventional gating was used to train a machine learning algorithm based on Gaussian mixture models (11). Thus, for the non-AI expert the idea comes up, if some information of a conventional workflow, collected by an automated application, could be “injected” into a CNN algorithm. If we assume that the problem of sensitivity will be tackled by improved versions in the near future, the AI solution of Zhao et al. will in fact be able to perform at “hematologist-level” and may even deliver B-NHL subtyping competence exceeding the results of conventional FCM alone. However, further problems have to be solved for a broader uptake of such a method: different laboratories work with different antibody panels and even antibodies recognizing the same cluster of differentiation antigen behave differently due to different antibody clones, different fluorochromes and different spillover from other fluorochromes in the panel. Thus, some methods of knowledge transfer are needed, if we want to avoid starting again with a training sample of more than 10,000 cases for every new antibody panel. If researchers will be able to solve these problems, AI for diagnostic FCM may finally leave the “proof of concept” stage and enter routine diagnostics. Open access funding enabled and organized by Projekt DEAL.
Cherukupalli Veda Vyasa Aditya, Rajesh Kannan Megalingam
Zero knowledge proof is a powerful cryptographic protocol that is utilized to establish data security whilst ensuring and maintaining user anonymity. ZKP has relatively less complex computational requirements as compared to the other protocols for authentication. Conventional authentication schemes are susceptible to attacks such as MiTM, IP spoofing, DoS, replay and other eavesdropping based attacks, when the data is shared across an untrusted network. This paper shows an approach to ensure authentication of a device over an untrusted network whilst maintaining and safeguarding user credentials, by using the concepts of ZKP protocol.
Driverless parking, an influential application of Mobility as a Service (MaaS) model, is one of the clear early benefits for autonomous vehicles, given often narrow spaces and multiple potential hazards (such as pedestrians stepping out from in between other vehicles). In recent years, real momentum has been building up for designing automated parking models for vehicles. However, in such an autonomous parking design, location privacy and identity privacy issues are always overlapping due to the improper sharing of data. Most existing studies barely investigate and poorly address such privacy issues. Motivated by this, we develop (and evaluate) an experience-driven, secure and privacy-aware framework of parking reservations for automated cars. Our idea of using differential privacy with zero-knowledge proof provides both security and privacy guarantees to users. Furthermore, the performance of the developed model is enhanced by exploiting reinforcement learning approach such that the utility of the system and the parking reservation rate can be maximized. Extensive evaluation demonstrates the superiority of the proposed model.
A fundamental requirement for all democratic governments is a secure voting system.In recent years some countries, like Estonia and Switzerland, have adopted internet voting (i-voting) and many more have experimented (e.g., Norway and Australia) or have plans to adopt it in the future (e.g., Lithuania and Russia).Ivoting has the potential to offer better convenience, lower administrative costs, and higher voter turnout, but this comes with increased security concerns and significant technical challenges.Consider the simple procedure of shaking the ballot box to mix the order of the ballots.It is far from obvious how to achieve an equivalent result with encrypted digital ballots.Who should perform the mixing procedure?How to guarantee that it was performed correctly?Is it possible that no one can trace the ballots?This problem can be solved with a distributed system called a mix-network.The idea is to let each peer in the mix-network shuffle (permute and rerandomize) the ciphertexts.This makes it computationally hard to trace the input ciphertexts to the output ciphertexts given that at least one peer is honest.However, each peer should also give a proof that the shuffling was done correctly to avoid substitution attacks.The proof has to be hard to forge (sound) and should leak nothing but the truth of the statement (zero-knowledge).Such proofs are called zero-knowledge shuffle arguments, and in this thesis, we study their constructions.Importantly, we avoid the heuristic security model, used in many of the previous works, which (incorrectly) treats a cryptographic hash function as a truly random function.We show that it possible to construct shuffle arguments, that are efficient enough for large-scale elections, in other security models than the random oracle model.First, we construct a very efficient non-interactive shuffle argument that avoids the random oracle model and instead uses the generic group model.This is achieved by combining several recent tools like quasi-adaptive zero-knowledge arguments and SNARKs.We implement it and observe practical efficiency for large-scale elections: the proving time for 100,000 ciphertexts is less than a minute, and verification time is less than 1.5 minutes on modest hardware.Unfortunately, security requires that the prover and the verifier have access to a trusted common reference string (CRS).Secondly, we study how to reduce trust assumptions.There are efficient multiparty computation (MPC) protocols for generating CRSs for a large class of arguments, but they require the random oracle model.We improve upon one such protocol and, among other results, remove the requirement for the random oracle.We prove the security of this protocol in the universal composability setting.Thirdly, we modify our shuffle argument to be applicable to the above MPC protocol.This guarantees both soundness and zero-knowledge as long as at least one peer in the MPC protocol is honest.We go one step further and show how to get zero knowledge even if all the peers are malicious.Additionally, we simplify the argument construction and prove its security based on weaker assumptions.
Sylvain Chatel, Apostolos Pyrgelis, Juan Ramón Troncoso-Pastoriza, Jean‐Pierre Hubaux
In the digital era, users share their personal data with service providers to obtain some utility, e.g., access to high-quality services. Yet, the induced information flows raise privacy and integrity concerns. Consequently, cautious users may want to protect their privacy by minimizing the amount of information they disclose to curious service providers. Service providers are interested in verifying the integrity of the users' data to improve their services and obtain useful knowledge for their business. In this work, we present a generic solution to the trade-off between privacy, integrity, and utility, by achieving authenticity verification of data that has been encrypted for offloading to service providers. Based on lattice-based homomorphic encryption and commitments, as well as zero-knowledge proofs, our construction enables a service provider to process and reuse third-party signed data in a privacy-friendly manner with integrity guarantees. We evaluate our solution on different use cases such as smart-metering, disease susceptibility, and location-based activity tracking, thus showing its versatility. Our solution achieves broad generality, quantum-resistance, and relaxes some assumptions of state-of-the-art solutions without affecting performance.
Abstract Round complexity is one of the fundamental problems in zero-knowledge (ZK) proof systems. Non-malleable zero-knowledge (NMZK) protocols are ZK protocols that provide security even when man-in-the-middle adversaries interact with a prover and a verifier simultaneously. It is known that the first constant-round public-coin NMZK arguments for NP can be constructed by assuming the existence of collision-resistant hash functions (Pass, R. and Rosen, A. (2005) New and Improved Constructions of Non-Malleable Cryptographic Protocols. In Gabow, H.N. and Fagin, R. (eds) Proc. 37th Annual ACM Symposium on Theory of Computing, Baltimore, MD, USA, May 2224, 2005, pp. 533542. ACM) and has relatively high round complexity; the first four-round private-coin NMZK arguments for NP can be constructed in the plain model by assuming the existence of one-way functions (Goyal, V., Richelson, S., Rosen, A. and Vald, M. (2014) An Algebraic Approach to Non-Malleability. In 55th IEEE Annual Symposium on Foundations of Computer Science, FOCS 2014, Philadelphia, PA, USA, October 1821, 2014, pp. 4150. IEEE Computer Society and Ciampi, M., Ostrovsky, R., Siniscalchi, L. and Visconti, I. (2017) Delayed-Input Non-Malleable Zero Knowledge and Multi-Party Coin Tossing in Four Rounds. In Kalai, Y. and Reyzin, L. (eds) Theory of Cryptography15th Int. Conf., TCC 2017. Lecture Notes in Computer Science, Baltimore, MD, USA, November 1215, 2017, Part I, Vol. 10677, pp. 711742. Springer). In this paper, we present a six-round public-coin NMZK argument of knowledge system assuming the existence of collision-resistant hash functions and a three-round private-coin NMZK argument system from multi-collision resistance of hash functions assumption in the keyless setting.
This paper will give both the necessary and sufficient conditions required to find a counter-example to the Goldbach Conjecture by using an algebraic approach where no knowledge of the gaps between prime numbers is needed. To eliminate ambiguity the set of natural numbers, $\mathbb{N}$, will include zero throughout this paper. Also, for any sufficiently large $a \in \mathbb{N}$ the set $\mathcal{P}$ is the set of all primes $p_i \leq a$. It will be shown there exists a counter-example to the Goldbach Conjecture, given by $2a$ where $a \in \mathbb{N}_{> 3}$, if and only if for each prime $p_i \in \mathcal{P}$ there exists some unique $q_i, \alpha_i \in \mathbb{N}$ where $a < q_i < 2a$ and $2a = q_i + p_i$ along with the condition that $\prod_{p_i \in \mathcal{P}}q_i = \prod_{p_i \in \mathcal{P}}p_i^{\alpha_i}$.A substitution of $q_i = 2a - p_i$ for each $q_i$ from each sum gives the product relationship $\prod_{p_i \in \mathcal{P}}(2a - p_i) = \prod_{p_i \in \mathcal{P}}p_i^{\alpha_i}$.Therefore, if a counter-example exists to the Goldbach Conjecture, then there exists a mapping $\mathcal{G}_-:\mathbb{C} \to \mathbb{C}$ where $$\mathcal{G}_-(z) = \prod_{p_i \in \mathcal{P}}(z - p_i) - \prod_{p_i \in \mathcal{P}}p_i^{\alpha_i}$$ and $\mathcal{G}_-(2a) = 0$. A proof of the Goldbach Conjecture will be given utilizing Hensel's Lemma to show $2a$ must be of the form $2a = p_i^{\alpha_i} + p_i$ for all primes up to $a$ when $a > 3$. However, this leads to contradiction since $2a < a\#$ for all $a > 4$.A similar method will be employed to give the necessary and sufficient conditions when an even number is not the difference of two primes with one prime being less than that even number. To begin, let $a \in \mathbb{N}_{> 3}$ with the condition that the function $\gamma(a + 1)$ is equal to one if $a + 1$ is prime and zero otherwise. $2a$ is a counter-example if and only if for each prime $p_i \in \mathcal{P}$ there exists some unique $u_i, \beta_i \in \mathbb{N}$ where $2a < u_i \leq 3a$ and $2a = u_i - p_i$ along with product relationship $\prod_{p_i \in \mathcal{P}}u_i = (a + 1)^{\gamma(a + 1)}\prod_{p_i \in \mathcal{P}}p_i^{\beta_i}$. A substitution of $u_i = 2a + p_i$ for each $u_i$ from each sum gives $\prod_{p_i \in \mathcal{P}}(2a + p_i) = (a + 1)^{\gamma(a + 1)}\prod_{p_i \in \mathcal{P}}p_i^{\beta_i}.$ Therefore, if a counter-example exists, it is possible to define the mapping $\mathcal{G}_+ : \mathbb{C} \to \mathbb{C}$ where $$\mathcal{G}_+(z) = \prod_{p_i \in \mathcal{P}}(z + p_i) - (a + 1)^{\gamma(a +1)} \prod_{p_i \in \mathcal{P}}p_i^{\beta_i}$$ and $\mathcal{G}_+(2a) = 0$. A proof will then be given that every even number is the difference of two primes by showing $2a$ must be of the form $2a = p_i^{\beta_i} - p_i$ for all odd primes up to $a$ when $a > 3$ to the equation above, leading to the same contradiction as the Goldbach Conjecture since $2a < a\#$ for $a > 4$. These proofs will have implications for proving the Polignac Conjecture.
Activity-tracking applications and location-based services using short-range communication (SRC) techniques have been abruptly demanded in the COVID-19 pandemic, especially for automated contact tracing. The attention from both public and policy keeps raising on related practical problems, including \textit{1) how to protect data security and location privacy? 2) how to efficiently and dynamically deploy SRC Internet of Thing (IoT) witnesses to monitor large areas?} To answer these questions, in this paper, we propose a decentralized and permissionless blockchain protocol, named \textit{Bychain}. Specifically, 1) a privacy-preserving SRC protocol for activity-tracking and corresponding generalized block structure is developed, by connecting an interactive zero-knowledge proof protocol and the key escrow mechanism. As a result, connections between personal identity and the ownership of on-chain location information are decoupled. Meanwhile, the owner of the on-chain location data can still claim its ownership without revealing the private key to anyone else. 2) An artificial potential field-based incentive allocation mechanism is proposed to incentivize IoT witnesses to pursue the maximum monitoring coverage deployment. We implemented and evaluated the proposed blockchain protocol in the real-world using the Bluetooth 5.0. The storage, CPU utilization, power consumption, time delay, and security of each procedure and performance of activities are analyzed. The experiment and security analysis is shown to provide a real-world performance evaluation.
The celebrated result of Fischer, Lynch and Paterson is the fundamental lower\nbound for asynchronous fault tolerant computation: any 1-crash resilient\nasynchronous agreement protocol must have some (possibly measure zero)\nprobability of not terminating. In 1994, Ben-Or, Kelmer and Rabin published a\nproof-sketch of a lesser known lower bound for asynchronous fault tolerant\ncomputation with optimal resilience against a Byzantine adversary: if $n\\le 4t$\nthen any t-resilient asynchronous verifiable secret sharing protocol must have\nsome non-zero probability of not terminating.\n Our main contribution is to revisit this lower bound and provide a rigorous\nand more general proof. Our second contribution is to show how to avoid this\nlower bound. We provide a protocol with optimal resilience that is almost\nsurely terminating for a strong common coin functionality. Using this new\nprimitive we provide an almost surely terminating protocol with optimal\nresilience for asynchronous Byzantine agreement that has a new fair validity\nproperty. To the best of our knowledge this is the first asynchronous Byzantine\nagreement with fair validity in the information theoretic setting.\n
Yanhong Xu, Reihaneh Safavi–Naini, Khoa Nguyen, Huaxiong Wang
Policy-based signatures (PBS) were proposed by Bellare and Fuchsbauer (PKC 2014) to allow an {\em authorized} member of an organization to sign a message on behalf of the organization. The user's authorization is determined by a policy managed by the organization's trusted authority, while the signature preserves the privacy of the organization's policy. Signing keys in PBS do not include user identity information and thus can be passed to others, violating the intention of employing PBS to restrict users' signing capability. In this paper, we introduce the notion of {\em traceability} for PBS by including user identity in the signing key such that the trusted authority will be able to open a suspicious signature and recover the signer's identity should the needs arise. We provide rigorous definitions and stringent security notions of traceable PBS (TPBS), capturing the properties of PBS suggested by Bellare-Fuchsbauer and resembling the "full traceability" requirement for group signatures put forward by Bellare-Micciancio-Warinschi (Eurocrypt 2003). As a proof of concept, we provide a modular construction of TPBS, based on a signature scheme, an encryption scheme and a zero-knowledge proof system. Furthermore, to demonstrate the feasibility of achieving TPBS from concrete, quantum-resistant assumptions, we give an instantiation based on lattices.
Zero-Knowledge Proofs (ZKPs) have emerged as a revolutionary cryptographic technique that enables one party to prove knowledge of a statement without revealing any underlying information. ZKPs play a crucial role in enhancing cybersecurity by enabling privacy-preserving authentication, secure transactions, and data integrity verification. This paper explores the fundamentals of zero-knowledge proofs, including their classifications—interactive, non-interactive, and succinct proofs—along with real-world applications in secure communications, blockchain security, and identity verification. Furthermore, we discuss the challenges of implementing ZKPs and the potential future advancements in this cryptographic field
—In this paper, a sampled-data model predictive tracking control method is presented for mobile robots which is modeled as constrained continuous-time linear parameter varying (LPV) systems. The presented sampled-data predictive controller is designed by linear matrix inequality approach. Based on the input delay approach, a controller design condition is derived by constructing a new Lyapunov function. Finally, a numerical example is given to demonstrate the effectiveness of the presented method. Keywords—Model predictive control, sampled-data control, linear parameter varying systems, LPV I. INTRODUCTION OBILE robots nowadays move autonomously by recognizing external environment and determining the situation through the remote control. With the development of network communication, implementation employing wireless & wired network is widespread [1]. Though control through network is advantageous in maintenance, installation, flexibility and cost, it has to be carefully designed in reality. It may cause instability and performance degradation without considering network induced delay or data packet losses. Therefore, the design of control scheme should consider with aspects and performances of whole systems. Model predictive control (MPC) scheme is very useful since it provides good tracking performance and the MPC tuning parameters are explicitly related to the key characteristics safety, comfort, and fuel economy. But if the model is not accurate, the control technique does not guarantee the stability and performance [2]. Also, an important issue in the implementation of MPC algorithm is the discretization. A continuous-time model is much more natural and accurate in terms of describing the behavior of a system, Also, in network control systems, choosing proper sampling interval is very important for designing suitable controllers. It is clear that a longer sampling period will lead to lower communication channel occupation, few actuation of the controller, and less signal transmission. Thus, it is very important to consider the stabilizing control design problem under a bigger sampling period [5]. For sampled-data systems, the input delay approach has been widely used [4], which is based on the representation of the sampled-data system as a continuous-time system Fig. 1 Mobile robot in X-Y coordination with a delayed control input. Then, the Lyapunov Krasovskii functional (LKF) method can be used to establish the stability conditions. Recently, based on the input delay approach, the sampled-data control problem of dynamical systems with time-varying delay has been investigated in [3], [4]. In this paper, we consider a continuous-time LPV model to handle mobile robot systems and present a model predictive control method for the systems with sampled-data. To the best of authors' knowledge, there are no approaches considering sampled-data MPC for mobile robots. The presented synthesis condition is formulated by construction of a suitable Lyapunov-Krasovskii's functional and control inputs are obtained by minimizing the upper bound of the cost function satisfying the cost monotonicity. Finally, we demonstrate the effectiveness of the proposed approach via numerical simulation. II. DESCRIPTION OF MOBILE ROBOT The dynamics of mobile robot with a rigid body and wheels can be described as follows [1] , (1) where [x,y,θ] denotes the position and orientation of the center with respect to a global frame, v is the translational velocity, and w is the angular velocity. For the given mobile robot, the reference trajectory is set to , (2) where xr, yr, θr are references in Cartesian coordination, vr is the reference translational velocity, and ωr is the reference angular velocity. Considering local coordinate frame, define From (1)-(3), the error dynamics is obtained as In general, systems represented by nonlinear systems can be transformed into Linear Parameter Varying (LPV) systems X˙ (t) = A(¯v(t),ω¯(t),vr(t))X(t) + BU(t), where A(·) is system matrices containing a time varying parameter vector v¯(t),ω¯(t),vr(t), X = [xe,ye,θe] − [¯xe,y¯e,θ¯e], and U = [v − v,ω¯ − ω¯]. By computing Jacobian matrix, the system matrices are given as . For a given sampling rates, the matrix A(¯v(t),ω¯(t),vr(t)) is subject to a polytope set Ω. (5) where Ω = {A1,A2,...,AL} is the convex hull. In the typical system architecture, control signals are conveyed through network communication. In network environments, the control signals pass through zero-order-hold (ZOH) which generate functions with a sequence of hold times 0 ≤ t0 < t1 < ··· < tk ··· < lim tk = +∞. Taking k→∞ consideration of ZOH, the control input is U(t) = KX(tk), t ∈ [tk,tk+1). (6) where K is the control gain matrix. Without loss of generality, it is assumed that the sampled time interval is bounded by h(t) ≤ hM where h(t) = tk+1 − tk, and hM is the maximum sampled delay. Using sampled signals, the systems are expressed as delayed LPV systems X˙ (t) = AiX(t) + BU(t − h(t)). (7) Lemma 1. [5] For given matrices Λ1,Λ2,Ψ, and a scalar 0 ≤ Lemma 2. [6] For given matrices H,N,R > 0 and a continuously differentiable function x(t) in [a,b] ∈ Rn, the following inequality is ensured. (10) (11) , where is any vector,, and x(s) . −b−a a III. MAIN RESULTS The main purpose of this paper is to design a proper sampled-data model predictive controller. Model Predictive Control is used to approximately obtain optimal trajectories. Therefore, choosing the following performance index is reasonable: (12) where Q, R are coefficients. For the given performance index, if the following condition is satisfied . (13) where · denotes 2-norm, then the upper bound of the performance index can be derived instead of directly minimizing performance index. By integrating (13) from i = 1 to i = ∞, one can notice the upper bound of the performance index is less than the Lyapunov function. Before presenting main results, we employed the following representations for simplicity. The matrices ei = R4n×n for i = 1,2,...,4 are matrices composed of nth zero elements with ith identity matrix. (For example, e1 = [I 0 0 0] and e3 = [0 0 I 0]). . With predefined Lemmas and notations, we present design methodology of model predictive control for delayed LPV systems by deriving a set of linear matrix inequality conditions. Theorem 1. For a given parameter hM and a vector X(tk), if U¯ U¯ there exist positive matrices G, 0,V >¯ 0, Y , Z¯1,Z¯2, satisfying the following LMI conditions, the control input at time instant tk guarantees the performance index (12) with γ . (14) (15) (16) (17) (18) where , with then, the state feedback gains are given as K = Y G−1. Proof. Choosing the following Lyapunov-Krasovskii functional (LKF) for t ∈ [tk,tk+1) yields V (xt) = V1(t) + V2(t) + V3(t) (19) where , Differentiate the LKF From Lemma 2, the following holds (23) where Z1,Z2 are auxiliary variables. Taking into account system dynamics (7), (24) Summing up from (20) to (24) leads to V˙ + XT(t)QX(t) + UT(t)RU(t) ≤ ζ(tk)Σ¯ζ(tk) (25) where Pre-and post-multiplying with a matrix γ1/2 × diag{G,G,G,G}, the followings are satisfied with Lemma 1. , (26) Σ1 + hMΣ3 < 0 (27) time (sec) Fig. 2 error response of the system in Example 1 where U¯ = GUG, V¯ = GV G, Z¯1 = GZ1G, Z¯2 = GZ2G, and K = Y G−1. Using Schur complement, The equations in (25) and (26) are equivalent to those of (16) and (17). For every sampling instance, V2 and V3 vanish. Then, the upper bound of LKF is expressed in terms of V1. XT(tk)GP¯1GX(tk) ≤ γ, (28) where γ denotes the bound of optimal performance index. The effect of input saturation is considered similar to the method in [7]. This ends the proof. IV. NUMERICAL EXAMPLE Example 1 This example considered the dynamical equations of the system represented from error dynamics. X˙ (t) = AiX(t) + BU(t − h(t)) (29) where ⎡ −0 ωr − 0.05 0 ⎤⎦ A1 =ω 0.05 0 vr(t) , 0 0 0 ⎡ 0 ωr + 0.05 0 ⎤ A2 =ω + 0.05 0 vr(t) , 0 0 0 ⎦ ⎡−1 0 ⎤ B = 0 0 . ⎣ 0 −1⎦ The model parameters are calculated with a sampling time 0.1s. The sampling time h(t) is less than 0.1 s. Along the reference trajectory, the input is constrained to −0.1 ≤ u(1) ≤ 0.1 and −0.05 ≤ u(2) ≤ 0.05. The corresponding controller gain matrix is Fig. 2 shows the simulation result which is obtained with the above controller gain, taking Q = I, R = I,α = 0.1. V. CONCLUSION The sampled-data MPC method for mobile robot systems have been investigated by considering constrained polytopic LPV model. Based on the input delay model, sufficient conditions for the sampled-data MPC controller design are obtained by constructing a new Lyapunov functional. The effectiveness of the presented method has been verified by illustrating numerical simulation. REFERENCES W. Lucia, F. Tedesco. "A networked-based receding horizon scheme for constrained LPV systems," European Journal of Control, vol. 25, pp. 69-75, 2015. S. Lee, Ju H. Park, D. Ji, S. Won, "Robust model predictive control for LPV systems using relaxation matrices," IET. Control Theory Appl., vol. 1, no. 6, pp. 1567-1573, 2007. A. Seuret, F. Gouaisbaut, Wirtinger-based integral inequality: application to time-delay systems, Automatica, vol. 49, no. 8, pp. 2860-2866, 2013. S. Lee, O. Kwon, Quantised MPC for LPV systems by using new LyapunovKrasovskii functional, IET. Control Theory Appl., vol. 11, no. 3, pp. 439-445, 2017. D. Yue, E. Tian, Y. Zhang, and C. Peng, "Delay-distribution-dependent stability and stabilization of T-S fuzzy systems with probabilistic interval delay," IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), vol. 39, no. 2, pp. 503–516, 2009. C.K. Zhang, Y. He, L. Jiang, W. Lin, M. Wu, "Delay-dependent stability analysis of neural networks with time-varying delay: A generalized free-weighting-matrix," Applied Mathematics and Computation, vol. 294, no. 1, pp. 102-120, 2017. E. Fridman and M. Dambrine, "Control under quantization, saturation and delay: An LMI approach," Automatica, vol. 45, no. 10, pp. 2258–2
How someone can get health insurance without sharing his health information? How you can get a loan without disclosing your credit score? There is a method to certify certain attributes of various data, either this is health metrics or finance information, without revealing the data itself or any other kind of personal data. This method is known as zero-knowledge proofs. Zero-Knowledge techniques are mathematical methods used to verify things without sharing or revealing underlying data. Zero-Knowledge protocols have vast applications from simple identity schemes and blockchains to defense research programs and nuclear arms control
Learning from data owned by several parties, as in federated learning, raises challenges regarding the privacy guarantees provided to participants and the correctness of the computation in the presence of malicious parties. We tackle these challenges in the context of distributed averaging, an essential building block of federated learning algorithms. Our first contribution is a scalable protocol in which participants exchange correlated Gaussian noise along the edges of a network graph, complemented by independent noise added by each party. We analyze the differential privacy guarantees of our protocol and the impact of the graph topology under colluding malicious parties, showing that we can nearly match the utility of the trusted curator model even when each honest party communicates with only a logarithmic number of other parties chosen at random. This is in contrast with protocols in the local model of privacy (with lower utility) or based on secure aggregation (where all pairs of users need to exchange messages). Our second contribution enables users to prove the correctness of their computations without compromising the efficiency and privacy guarantees of the protocol. Our verification protocol relies on standard cryptographic primitives like commitment schemes and zero knowledge proofs.
Public blockchains can be abused to covertly store and disseminate potentially harmful digital content which poses a serious regulatory issue. In this work, we show the severity of the problem by demonstrating that blockchains can be exploited to surreptitiously distribute arbitrary content. More specifically, all major blockchain systems use randomized cryptographic primitives, such as digital signatures and non-interactive zero-knowledge proofs; we illustrate how the uncontrolled randomness in such primitives can be maliciously manipulated to enable covert communication and hidden persistent storage. To clarify the potential risk, we design, implement and evaluate our technique against the widely-used ECDSA signature scheme, the CryptoNote's ring signature scheme, and Monero's ring confidential transactions. Importantly, the significance of the demonstrated attacks stems from their undetectability, their adverse effect on the future of decentralized blockchains, and their serious repercussions on users' privacy and crypto funds. Finally, we present a generic framework to immunize blockchains against these attacks.
Open access
Advanced Steganography and Watermarking Techniques
With the development of precise positioning technology, a growing number of location-based services (LBSs) facilitate people's life. Most LBSs require proof of location (PoL) to prove that the user satisfies the service requirement, which exposes the user's privacy. In this paper, we propose a zero-knowledge proof of location (zk-PoL) protocol to better protect the user's privacy. With the zk-PoL protocol, the user can choose necessary information to expose to the server, so that hierarchical privacy protection can be achieved. The evaluation shows that the zk-PoL has excellent security to resist main attacks, moreover the computational efficiency is independent of input parameters and the zk-PoL is appropriate to delay-tolerant LBSs.
Current cloud and network infrastructures do not employ privacy-preserving methods to protect their assets. Anonymous credential schemes are a cryptographic building block that enables the certification of data structures and prove properties over their representations without disclosing the innards of their data structures in zero-knowledge. The GRaph Signature (GRS) scheme enables the certification and proof methods to sign infrastructure topologies represented as graph data structures and use zero-knowledge to prove properties over their certificates. As such, they represent a powerful privacy-preserving method that proves properties over a signed topology graph to another party without disclosing the blueprint of its topology. In this paper, we report our efforts in designing, implementing and benchmarking a Graph Signature Library (GSL). GSL is a cryptographic library realized in Java that implements the graph signature scheme.
This paper describes techniques to help with COVID-19 automated contact tracing, and with the restoration efforts. We describe a decentralized protocol for ``proof-of-contact'' in zero knowledge where a person can publish a short cryptographic proof attesting to the fact that they have been infected and that they have come in contact with a set of people without revealing any information about any of the people involved. More importantly, we describe how to compose these proofs to support broader functionality such as proofs of $n$th-order exposure which can further speed up automated contact tracing. The cryptographic proofs are publicly verifiable, and places the burden on the person proving contact and not on third parties or healthcare providers rendering the system more decentralized, and accordingly more scalable.
In 2009, Gradwohl, Naor, Pinkas, and Rothblum proposed physical zero-knowledge proof protocols for Sudoku. That is, for a puzzle instance of Sudoku, their excellent protocols allow a prover to convince a verifier that there is a solution to the Sudoku puzzle and the prover knows it, without revealing any information about the solution. The possible drawback is that the existing protocols have an extractability error with a non-zero probability, or need special cards (such as scratch-off cards). Thus, in this study, we propose new protocols to perform zero-knowledge proof of knowledge for Sudoku using a normal deck of playing cards with no extractability error. Our protocols can be easily implemented by humans with a reasonable number of playing cards.