FEASE: Fast and Expressive Asymmetric Searchable Encryption

Asymmetric Searchable Encryption (ASE) is a promising cryptographic mechanism that enables a semi-trusted cloud server to perform keyword searches over encrypted data for users. To be useful, an ASE scheme must support expressive search queries, which are expressed as conjunction, disjunction, or any Boolean formulas. In this paper, we propose a fast and expressive ASE scheme that is adaptively secure, called FEASE. It requires only 3 pairing operations for searching any conjunctive set of keywords independent of the set size and has linear complexity for encryption and trapdoor algorithms in the number of keywords. FEASE is based on a new fast Anonymous Key-Policy Attribute-Based Encryption (A-KP-ABE) scheme as our first proposal, which is of independent interest. To address optional protection against keyword guessing attacks, we extend FEASE into the first expressive Public-Key Authenticated Encryption with Keyword Search (PAEKS) scheme. We provide implementations and evaluate the performance of all three schemes, while also comparing them with the state of the art. We observe that FEASE outperforms all existing expressive ASE constructions and that our A-KP-ABE scheme offers anonymity with efficiency comparable to the currently fastest yet non-anonymous KP-ABE schemes FAME (ACM CCS 2017) and FABEO (ACM CCS 2022)

Soil Moisture Determines Horizontal and Vertical Root Extension in the Perennial Grass Lolium perenne L. Growing in Karst Soil

Karst regions are characterized by heterogeneous soil habitats, with shallow wide soil (SW) on hilly slopes and deep narrow soil (DN) in rocky trenches. To make full use of limited water and nutrients, plants have therefore developed a number of root extension strategies. This study investigated the effect of soil moisture on horizontal root extension in SW and vertical root extension in DN by assessing root growth responses, biomass allocation, and root distribution. A full two-way factorial blocked design of soil dimensions by water availability was followed. The perennial grass Lolium perenne L. was grown in SW and DN under high (W100%), moderate (W50%), and low (W30%) water availability, respectively. The main results were as follows: (1) The total biomass of L. perenne was not influenced either by soil habitat or by water application. Root length, root surface area, root biomass and root to shoot ratio all decreased with decreasing water application in SW, but not in DN soil. (2) With decreasing water application, the cumulative percentage of root length, root surface area and root biomass in 4 rings from the center out to 12 cm of SW soil showed a trend of W50% > W30% > W100% in SW, however, the cumulative percentage of root biomass in 4 layers from the surface to a depth of 36 cm was not significantly different between different water treatments in DN. (3) Under all three water treatments, specific root length showed an increase but root length density showed a decreasing trend from the center outward in SW soil or from the surface to bottom in DN soil. Overall, these results suggest that in SW habitat, soil moisture determines horizontal expansion of the roots in L. perenne, although the overall expansion ability was limited in severe drought. However, due to the relatively strong water retention ability, soil moisture changes were less obvious in DN, resulting in no significant vertical extension of the root system. The root response of L. perenne helps our understanding of how herbaceous plants can adjust their belowground morphology to support their growth in harsh karst soil environments

Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy

The Endoscopy Computer Vision Challenge (EndoCV) is a crowd-sourcing initiative to address eminent problems in developing reliable computer aided detection and diagnosis endoscopy systems and suggest a pathway for clinical translation of technologies. Whilst endoscopy is a widely used diagnostic and treatment tool for hollow-organs, there are several core challenges often faced by endoscopists, mainly: 1) presence of multi-class artefacts that hinder their visual interpretation, and 2) difficulty in identifying subtle precancerous precursors and cancer abnormalities. Artefacts often affect the robustness of deep learning methods applied to the gastrointestinal tract organs as they can be confused with tissue of interest. EndoCV2020 challenges are designed to address research questions in these remits. In this paper, we present a summary of methods developed by the top 17 teams and provide an objective comparison of state-of-the-art methods and methods designed by the participants for two sub-challenges: i) artefact detection and segmentation (EAD2020), and ii) disease detection and segmentation (EDD2020). Multi-center, multi-organ, multi-class, and multi-modal clinical endoscopy datasets were compiled for both EAD2020 and EDD2020 sub-challenges. The out-of-sample generalization ability of detection algorithms was also evaluated. Whilst most teams focused on accuracy improvements, only a few methods hold credibility for clinical usability. The best performing teams provided solutions to tackle class imbalance, and variabilities in size, origin, modality and occurrences by exploring data augmentation, data fusion, and optimal class thresholding techniques. [Abstract copyright: Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.

Cryptanalysis of a Pseudorandom Generator for Cross-Border E-Commerce

In this paper, we study ciphertext-only cryptanalysis of a cascade of pseudorandom sequence generators employing linear feedback shift registers (LFSRs) with so-called irregular clocking. The cascade of LFSRs is a well-known pseudorandom generator scheme that produces sequences with good cryptographic characteristics (long period, high linear complexity, good statistical properties, etc.) A method of cryptanalysis of cascades containing two such LFSRs is well known. We generalize this method to cryptanalysis of a cascade with an arbitrary number of LFSRs. We reconstruct a set of candidate clock control sequences at each stage of the cascade, instead of enumerating all the possible initial states of the corresponding subcascade. The reconstruction is performed by means of an independent search through the edit distance matrix associated with every stage of the cascade. The experimental results show that such a generalized method of cryptanalysis is feasible. This topic is of great significance to the study of the security of such schemes applied to digital communications of cross-border e-commerce