Post Quantum Succinct Arguments

We prove that Kilian’s four-message succinct argument system is post-quantumsecure in the standard model . At the heart of our proof is a new “measure-and-repair” quantum rewinding procedure that achieves asymptotically optimal knowledge error .…

Compositional Security for Reentrant Applications

We do not know how to write code that is secure in composition with malicious code . We formalize a generaldefinition of reentrancy and introduce a security condition that allows modules like smart contracts to protect their key invariants . We present a security type system that provably enforces secure information flow .…

Take a Bite of the Reality Sandwich Revisiting the Security of Progressive Message Authentication Codes

Message authentication guarantees the integrity of messages exchanged overuntrusted channels . However, the required per-message authentication tagsconsiderably expand packet sizes . We propose R2-D2, which relies on (i)optimal message dependencies, (ii) parametrizable security guarantees, (iii)randomized bit dependencies, and (iv) optional immediate protection bits to address this problem .…

Beyond ANN Exploiting Structural Knowledge for Efficient Place Recognition

Many approaches in the literature perform computationally inefficient full image comparisons between queries and all database images . In this paper, we propose a novel fast sequence-based method for efficient place recognition that can be applied online . It uses relocalization to recover from sequence losses, and exploits usually available but often unused intra-database similarities for potential detection of all matching database images for each query in case of loops or stops in the database .…

I Nema A Biological Image Dataset for Nematode Recognition

Nematode worms are one of most abundant metazoan groups on the earth,occupying diverse ecological niches . Accurate recognition or identification of Nematodes is of great importance for pest control, soil ecology and soil ecology . We propose animage dataset consisting of diverse nematodes (both laboratory cultured andnaturally isolated), which, to our knowledge, is the first time in the community .…

Automatically Lock Your Neural Networks When You re Away

The smartphone and laptop can be unlocked by face or fingerprint recognition, while neural networks which confront numerous requests every day have littlecapability to distinguish between untrustworthy and credible users . In this paper, we propose Model-Lock (M-LOCK) to realize an end-to-endneural network with local dynamic access control, which is similar to the automatic locking function of the smartphone to prevent malicious attackers from obtaining available performance actively when you are away .…

BLOFF A Blockchain based Forensic Model in IoT

Cybercriminals of today have the tools and the technology to deploy millions of sophisticated attacks . Digital forensics comes into play, but it is not easy to conduct a forensic investigation in IoT systems because of the heterogeneous nature of the IoT environment .…

Multi view Subword Regularization

Multilingual pretrained representations generally rely on subwordsegmentation algorithms to create a shared multilingual vocabulary . Standard heuristic algorithms often lead to sub-optimal segmentation, especially for languages with limited amounts of data . We propose Multi-view Subword Subword Regularization (MVR), a method that enforces the consistencybetween predictions of using inputs tokenized by the standard and probabilisticsegmentations .…

Metric Learning for Anti Compression Facial Forgery Detection

Forgery images and videos are usually compressed to different formats such as JPEG and H264 when circulating on the Internet . Existing forgery-detection methods trained on uncompressed data often havesignificantly decreased performance in identifying them . To solve this problem, we propose a novel anti-compression facial forgery detection framework, whichlearns a compression-insensitive embedding feature space utilizing bothoriginal and compressed forgeries .…

Return Oriented Programming on RISC V

This paper provides the first analysis on the feasibility of Return-OrientedProgramming (ROP) on RISC-V . We show the existence of a new class of gadgets, usingseveral Linear Code Sequences And Jumps (LCSAJ) undetected by currentGalileo-based ROP gadget searching tools . We argue that this class is rich enough on Risc-V to mount complex ROP attacks, bypassing traditionalmitigation like DEP, ASLR, stack canaries, G-Free, as well as somecompiler-based backward-edge CFI, by jumping over any guard inserted by acompiler to protect indirect jump instructions .…

Electronic Structure in a Fixed Basis is QMA complete

Finding the ground state energy of electrons subject to an external electricfield is a fundamental problem in computational chemistry . Schuch and Verstraete haveshown hardness for the electronic-structure problem with an additionalsite-specific external magnetic field, but without the restriction to a fixedbasis .…

Rectilinear Steiner Trees in Narrow Strips

A rectilinear Steiner tree for a set $P$ of points in $mathbb{R}^2$ is atree that connects the points using horizontal and vertical linesegments . We present an algorithm with running time $n^{O(\sqrt{\delta) n$ for sparse point sets, that is, point sets where each$1\times\delta$ rectangle inside the strip contains $O(1)$ points .…

Quantum Private Distributed Learning Through Blind Quantum Computing

Private distributed learning studies the problem of how multiple distributedentities collaboratively train a shared deep network with their private data . With the security provided by the protocols of blind quantumcomputation, the cooperation between quantum physics and machine learning maylead to unparalleled prospect for solving private distributed learning tasks .…

Learning Frequency aware Dynamic Network for Efficient Super Resolution

Deep learning based methods, especially convolutional neural networks (CNNs) have been successfully applied in the field of single image super-resolution(SISR) To obtain better fidelity and visual quality, most of existing networksare of heavy design with massive computation . To this end, this paper explores a novel frequency-awaredynamic network for dividing input into multiple parts according to itscoefficients in the discrete cosine transform (DCT) domain .…

3D FFS Faster 3D object detection with Focused Frustum Search in sensor fusion based networks

3D-FFS is a novel approach to make sensor fusion based3D object detection networks significantly faster using a class ofcomputationally inexpensive heuristics . Compared to F-ConvNet, we achieve improvements in training andinference times by up to 62.84% and 56.46% . We achieve 0.59%, 2.03% and 3.34%improvements in accuracy for the Car, Pedestrian and Cyclist classes,respectively.…

XLST Cross lingual Self training to Learn Multilingual Representation for Low Resource Speech Recognition

Cross-lingual self-training (XLST) is able toutilize a small amount of annotated data from high-resource languages to improve representation learning on multilingual un-annotated data . XLST uses a supervised trained model to produce initial representations and another model to learn from them, by maximizing thesimilarity between output embeddings of these two models .…

BLOWN A Blockchain Protocol for Wireless Networks under Adversarial SINR

Blockchain can empower wireless networks with identity management, data integrity, access control, and high-level security . We formalizeBLOWN with the universal composition framework and prove its securityproperties, namely persistence and liveness, against adversarial jamming, double-spending, and Sybil attacks . We propose a novel consensusprotocol named Proof-of-Channel (PoC) leveraging the natural properties ofwireless networks, and a BLOWN protocol (BLOckchain protocol for WirelessNetworks) for wireless networks under an adversarial SINR model .…

Rotation Coordinate Descent for Fast Globally Optimal Rotation Averaging

Rotationaveraging satisfies strong duality, which enables global solutions to be obtained via semidefinite programming (SDP) relaxation . However, genericsolvers for SDP are rather slow in practice, even on rotation averaging instances of moderate size . In this paper, we present a fast algorithm that achieves global optimality calledrotation coordinate descent (RCD) Unlike block coordinate descent, RCD maintains and updates all valid rotations throughout the iterations .This…

Get Your Vitamin C Robust Fact Verification with Contrastive Evidence

Typical fact verification models use retrieved written evidence to verify claims . Evidence sources often change over time as more information is gathered and revised . In order to adapt, models must be sensitive to subtledifferences in supporting evidence . We present VitaminC, a benchmark infused with challenging cases that require models to discern and adjust to slight factual changes .…

Uncertainty Based Biological Age Estimation of Brain MRI Scans

Current BA estimation approaches are restricted to skeletal images or rely on non-imaging modalities that yield a whole-body BA assessment . Various organ systems may exhibit different aging characteristics due to lifestyle and genetic factors . In thisinitial study, we propose a new framework for organ-specific BA estimation using 3D magnetic resonance image (MRI) scans .…

Enclosing Depth and other Depth Measures

We study families of depth measures defined by natural sets of axioms . Weshow that any such depth measure is a constant factor approximation of Tukeydepth . We further investigate the dimensions of depth regions, showing that theCascade conjecture, introduced by Kalai for Tverberg depth, holds for all depthmeasures .…

Efficient Intrusion Detection Using Evidence Theory

Intrusion Detection Systems (IDS) are now an essential element when it comesto securing computers and networks . Despite the huge research efforts done inthe field, handling sources’ reliability remains an open issue . To address thisproblem, this paper proposes a novel contextual discounting method based on reliability and their distinguishing ability between normal andnormal behavior .…

Margin Preserving Self paced Contrastive Learning Towards Domain Adaptation for Medical Image Segmentation

A novel marginpreserving self-paced contrastive Learning (MPSCL) model for cross-modal medical image segmentation . MPSCL significantlyimproves semantic segmentation performance, and outperforms a wide variety of state-of-the-art methods by a large margin . Unlike the conventional construction of contrastivepairs in contrastive learning, the domain-adaptive category prototypes are used to constitute the positive and negative sample pairs .…

A novel approach for the efficient modeling of material dissolution in electrochemical machining

This work presents a novel approach to efficiently model anodic dissolution in electrochemical machining . Earlier modeling approaches employ a strict spacediscretization of the anodic surface that is associated with a remeshingprocedure at every time step . This inner variable allows the modeling of the complex dissolution process without the necessity of computationally expensiveremeshing by controlling the effective material parameters .…

Online Learning with Radial Basis Function Networks

We investigate the benefits of feature selection, nonlinear modelling and online learning with forecasting in financial time series . We also find that, in the subset of models we use,sequential learning in time with online Ridge regression, provides the best multi-step ahead forecasts, and continual learning with an online radial basisfunction network .…

Computing the Multicover Bifiltration

Given a finite set $A\subset\mathbb{R}^d, let Cov$_{_{r,k}$ denote the set ofall points within distance $r$ to at least $k$ points of $A$. Allowing $r and$k$ to vary, we obtain a 2-parameter family of spaces that grow larger when $r# increases or $k# decreases .…

Selfish Mining Attacks Exacerbated by Elastic Hash Supply

Several attacks have been proposed against Proof-of-Work blockchains . decreasing the profitability of mining forhonest nodes incentivizes them to stop mining or to leave the attacked chain . The departure of honest nodes exacerbates the attack and may further decrease profitability and incentivize more honest nodes to leave .…

On Planar Visibility Counting Problem

For a set $S$ of $n$ disjoint line segments in $\mathbb{R}^{2}$, thevisibility counting problem is to preprocess $S $S such that the number ofvisible segments in $S# can be computed quickly . Therehave been approximation algorithms for this problem with trade off betweenspace and query time .…

A Systematic Review of Reproducibility Research in Natural Language Processing

The NLP field is becoming increasingly interested in, and conscientious about, the reproducibility of its results . The past few years have seen an impressive range of new initiatives, events and active research inthe area . However, the field is far from reaching a consensus about howreproducibility should be defined, measured and addressed, with diversity of views currently increasing rather than converging .…

SemVLP Vision Language Pre training by Aligning Semantics at Multiple Levels

Vision-language pre-training (VLP) on large-scale image-text pairs has witnessed rapid progress for learning cross-modal representations . SemVLP jointly aligns both the low-level and high-level semantics between image and text representations . An extensive set of experiments have been conducted on four well-established vision-language understanding tasks todemonstrate the effectiveness of the proposed model .…