Confidential Boosting with Random Linear Classifiers for Outsourced User-generated Data

User-generated data is crucial to predictive modeling in many applications. With a web/mobile/wearable interface, a data owner can continuously record data generated by distributed users and build various predictive models from the data to improve their operations, services, and revenue. Due to the large size and evolving nature of users data, data owners may rely on public cloud service providers (Cloud) for storage and computation scalability. Exposing sensitive user-generated data and advanced analytic models to Cloud raises privacy concerns. We present a confidential learning framework, SecureBoost, for data owners that want to learn predictive models from aggregated user-generated data but offload the storage and computational burden to Cloud without having to worry about protecting the sensitive data. SecureBoost allows users to submit encrypted or randomly masked data to designated Cloud directly. Our framework utilizes random linear classifiers (RLCs) as the base classifiers in the boosting framework to dramatically simplify the design of the proposed confidential boosting protocols, yet still preserve the model quality. A Cryptographic Service Provider (CSP) is used to assist the Cloud's processing, reducing the complexity of the protocol constructions. We present two constructions of SecureBoost: HE+GC and SecSh+GC, using combinations of homomorphic encryption, garbled circuits, and random masking to achieve both security and efficiency. For a boosted model, Cloud learns only the RLCs and the CSP learns only the weights of the RLCs. Finally, the data owner collects the two parts to get the complete model. We conduct extensive experiments to understand the quality of the RLC-based boosting and the cost distribution of the constructions. Our results show that SecureBoost can efficiently learn high-quality boosting models from protected user-generated data

RESPIRATORY SYNDROME: A MAJOR THREAT TO THE LIVESTOCK FARMERS AND ITS ECONOMIC IMPACT

Epidemiology of a respiratory syndrome was studied at Landhi Dairy Colony (LDC), Karachi, Pakistan and its economic impact was estimated. Among 5889 buffaloes examined, 2.3% animals were suffering from this syndrome. From some of the sick animals, Pasteurella multocida, the causative agent of haemorrhagic septicaemia, was isolated. In the present study, an average loss of Rs. 0.2 million per farm was calculated and the extrapolated values for 0.2 and 0.8 million animals present in LDC and other dairy colonies in Karachi were Rs. 225.6 and Rs. 1128.1 million, respectively

Multi-scale computational homogenisation to predict the long-term durability of composite structures

A coupled hygro-thermo-mechanical computational model is proposed for fibre reinforced polymers, formulated within the framework of Computational Homogenisation (CH). At each macrostructure Gauss point, constitutive matrices for thermal, moisture transport and mechanical responses are calculated from CH of the underlying representative volume element (RVE). A degradation model, developed from experimental data relating evolution of mechanical properties over time for a given exposure temperature and moisture concentration is also developed and incorporated in the proposed computational model. A unified approach is used to impose the RVE boundary conditions, which allows convenient switching between linear Dirichlet, uniform Neumann and periodic boundary conditions. A plain weave textile composite RVE consisting of yarns embedded in a matrix is considered in this case. Matrix and yarns are considered as isotropic and transversely isotropic materials respectively. Furthermore, the computational framework utilises hierarchic basis functions and designed to take advantage of distributed memory high performance computing

EPIDEMIOLOGICAL INVESTIGATIONS OF A PESTE DES PETITS RUMINANTS (PPR) OUTBREAK IN AFGHAN SHEEP IN PAKISTAN

Epidemiological and virological investigations were carried out during an outbreak of Peste des petits ruminants (PPR) in Afghan (Bulkhi) sheep in Pakistan. The overall morbidity, mortality and case fatality rates were 41.0, 1.2 and 3.0%, respectively. The epidemic curve was plotted and the values for basic reproductive number (R0) and herd immunity threshold (HIT) for the affected flock were estimated to be 6.85 and 85.4%, respectively. The morbid material analysis by immuno-capture ELISA (Ic-ELISA) and haemagglutination assay (HA) revealed the presence of PPR virus. The PPR virus was isolated and identified through cytopathic effects, Ic-ELISA and transmission electron microscopy (TEM)

On Multiparty Garbling of Arithmetic Circuits

We initiate a study of garbled circuits that contain both Boolean and arithmetic gates in secure multiparty computation. In particular, we incorporate the garbling gadgets for arithmetic circuits recently presented by Ball, Malkin, and Rosulek (ACM CCS 2016) into the multiparty garbling paradigm initially introduced by Beaver, Micali, and Rogaway (STOC \u2790). This is the first work that studies arithmetic garbled circuits in the multiparty setting. Using mixed Boolean-arithmetic circuits allows more efficient secure computation of functions that naturally combine Boolean and arithmetic computations. Our garbled circuits are secure in the semi-honest model, under the same hardness assumptions as Ball et al., and can be efficiently and securely computed in constant rounds assuming an honest majority. We first extend free addition and multiplication by a constant to the multiparty setting. We then extend to the multiparty setting efficient garbled multiplication gates. The garbled multiplication gate construction we show was previously achieved only in the two-party setting and assuming a random oracle. We further present a new garbling technique, and show how this technique can improve efficiency in garbling selector gates. Selector gates compute a simple ``if statement in the arithmetic setting: the gate selects the output value from two input integer values, according to a Boolean selector bit; if the bit is $0$ the output equals the first value, and if the bit is $1$ the output equals the second value. Using our new technique, we show a new and designated garbled selector gate that reduces by approximately $33\%$ the evaluation time, for any number of parties, from the best previously known constructions that use existing techniques and are secure based on the same hardness assumptions. On the downside, we find that testing equality and computing exponentiation by a constant are significantly more complex to garble in the multiparty setting than in the two-party setting

Stacked Garbling for Disjunctive Zero-Knowledge Proofs

Zero-knowledge (ZK) proofs receive wide attention, especially with respect to non-interactivity, small proof size, and fast verification. We instead focus on fast total proof time, in particular for large Boolean circuits. Under this metric, Garbled Circuit (GC)-based ZK, originally proposed by Jawurek et al. ([JKO], CCS 2013), remains state-of-the-art due to the low-constant linear scaling of garbling. We improve GC-ZK for proof statements with conditional clauses. Our communication is proportional to the longest clause rather than to the entire proof statement. This is most useful when the number of branches $m$ is large, resulting in up to $m\times$ communication improvement over JKO. In our proof-of-concept illustrative application, the prover demonstrates knowledge of a bug in a codebase consisting of any number of snippets of C code. Our computation cost is linear in the size of the codebase and communication is constant in the number of snippets. That is, we require only enough communication for the single largest snippet! Our conceptual contribution is stacked garbling for ZK, a privacy-free circuit garbling scheme that, when used with the JKO GC-ZK protocol, constructs efficient ZK proofs. Given a Boolean circuit $C$ and computational security parameter $\kappa$, our garbling is $L\kappa$ bits long, where $L$ is the length of the longest execution path in $C$. All prior concretely efficient garbling schemes produce garblings of size $|C|\kappa$. The computational cost of our scheme is not increased over prior state-of-the-art. We implemented our technique and demonstrate significantly improved performance. For functions with branching factor $m$, we improve communication by $m\times$ compared to JKO. Compared with recent systems (STARK, Libra, KKW, Ligero, Aurora, Bulletproofs), our scheme offers better proof times for large circuits: $35-1000\times$ or more, depending on circuit size and on the compared scheme. For our illustrative application, we consider four C code snippets. Each snippet has 30-50 LOC; one snippet allows an invalid memory dereference. The entire proof takes 0.15 seconds and communicates 1.5 MB

Cut-and-Choose for Garbled RAM

Garbled RAM, introduced by Lu and Ostrovsky (Eurocrypt 2013), provides a novel method for secure computation on RAM (Random Access Machine) programs directly. It can be seen as a RAM analogue of Yao\u27s garbled circuits such that the computational complexity and communication complexity only grow with the running time of the RAM program, avoiding the inefficient process of first converting it into a circuit. It allows for executing multiple RAM programs on a persistent database, but is secure only against semi-honest adversaries. In this work we provide a cut-and-choose technique for garbled RAM. This gives the first constant-round two-party RAM computation protocol secure against malicious adversaries which allows for multiple RAM programs being executed on a persistent database. Our protocol makes black-box use of the one-way functions, and security of our construction is argued in the random oracle model

Adaptive Security of Practical Garbling Schemes

A garbling scheme enables one to garble a circuit C and an input x in a way that C(x) can be evaluated, but nothing else is revealed. Since the first construction by Yao, there have been tremendous practical efficiency improvements for selectively secure garbling schemes, where the adversary is forced to choose both input and circuit to be garbled at the same time. However, in the more realistic setting of adaptive security --where an adversary can choose the input adaptively based on the garbled circuit-- not much is known about practical efficiency improvements. In this work, we initiate the study of practical garbling schemes that are both more efficient than Yao\u27s construction and adaptively secure. We provide insights into characteristics of these schemes and highlight the limitations of current techniques for proving adaptive security in this regime. Furthermore, we present an adaptively secure garbling scheme that garbles XOR gates with 2 and AND gates with 3 ciphertexts per gate, thus providing the first practical garbling scheme with adaptive security based on PRFs whose garbled circuit size is smaller than that of Yao\u27s construction

Concretely Efficient Large-Scale MPC with Active Security (or, TinyKeys for TinyOT)

In this work we develop a new theory for concretely efficient, large-scale MPC with active security. Current practical techniques are mostly in the strong setting of all-but-one corruptions, which leads to protocols that scale badly with the number of parties. To work around this issue, we consider a large-scale scenario where a small minority out of many parties is honest and design scalable, more efficient MPC protocols for this setting. Our results are achieved by introducing new techniques for information-theoretic MACs with short keys and extending the work of Hazay et al. (CRYPTO 2018), which developed new passively secure MPC protocols in the same context. We further demonstrate the usefulness of this theory in practice by analyzing the concrete communication overhead of our protocols, which improve upon the most efficient previous works

Covert Security with Public Verifiability: Faster, Leaner, and Simpler

The notion of covert security for secure two-party computation serves as a compromise between the traditional semi-honest and malicious security definitions. Roughly, covert security ensures that cheating behavior is detected by the honest party with reasonable probability. It provides more realistic guarantees than semi-honest security with significantly less overhead than is required by malicious security. The rationale for covert security is that it dissuades cheating by parties that care about their reputation and do not want to risk being caught. Further thought, however, shows that a much stronger disincentive is obtained if the honest party can generate a publicly verifiable certificate of misbehavior when cheating is detected. While the corresponding notion of publicly verifiable covert (PVC) security has been explored, existing PVC protocols are complex and less efficient than the best-known covert protocols, and have impractically large certificates. We propose a novel PVC protocol that significantly improves on prior work. Our protocol uses only ``off-the-shelf\u27\u27 primitives (in particular, it avoids signed oblivious transfer) and, for deterrence factor 1/2, has only 20-40% overhead (depending on the circuit size and network bandwidth) compared to state-of-the-art semi-honest protocols. Our protocol also has, for the first time, constant-size certificates of cheating (e.g., 354 bytes long at the 128-bit security level). As our protocol offers strong security guarantees with low overhead, we suggest that it is the best choice for many practical applications of secure two-party computation