Counterfactual quantum key distribution with untrusted detectors.

Compared with the traditional BB84 protocol, the counterfactual quantum key distribution (QKD) does not rely on any signal travelling in the quantum channel, and therefore can present a security advantage where Eve cannot fully access signal. However, the practical system may be damaged in a scenario where the devices are untrusted. In this paper, we analyze the security of counterfactual QKD in untrusted detectors scenario.

Self-Triggered Consensus of Vehicle Platoon System With Time-Varying Topology.

This paper focuses on the consensus problem of a vehicle platoon system with time-varying topology via self-triggered control. Unlike traditional control methods, a more secure event-triggered controller considering the safe distance was designed for the vehicle platoon system. Then, a Lyapunov function was designed to prove the stability of the platoon system.

A Cognitive Method for Automatically Retrieving Complex Information on a Large Scale.

Modern retrieval systems tend to deteriorate because of their large output of useless and even misleading information, especially for complex search requests on a large scale. Complex information retrieval (IR) tasks requiring multi-hop reasoning need to fuse multiple scattered text across two or more documents. However, there are two challenges for multi-hop retrieval.

TAP: A static analysis model for PHP vulnerabilities based on token and deep learning technology.

With the widespread usage of Web applications, the security issues of source code are increasing. The exposed vulnerabilities seriously endanger the interests of service providers and customers. There are some models for solving this problem.

Self Multi-Head Attention-based Convolutional Neural Networks for fake news detection.

With the rapid development of the internet, social media has become an essential tool for getting information, and attracted a large number of people join the social media platforms because of its low cost, accessibility and amazing content. It greatly enriches our life. However, its rapid development and widespread also have provided an excellent convenience for the range of fake news, people are constantly exposed to fake news and suffer from it all the time.

Kernel Mixture Correntropy Conjugate Gradient Algorithm for Time Series Prediction.

Kernel adaptive filtering (KAF) is an effective nonlinear learning algorithm, which has been widely used in time series prediction. The traditional KAF is based on the stochastic gradient descent (SGD) method, which has slow convergence speed and low filtering accuracy. Hence, a kernel conjugate gradient (KCG) algorithm has been proposed with low computational complexity, while achieving comparable performance to some KAF algorithms, e.

Mention effect in information diffusion on a micro-blogging network.

Micro-blogging systems have become one of the most important ways for information sharing. Network structure and users' interactions such as forwarding behaviors have aroused considerable research attention, while mention, as a key feature in micro-blogging platforms which can improve the visibility of a message and direct it to a particular user beyond the underlying social structure, is seldom studied in previous works. In this paper, we empirically study the mention effect in information diffusion, using the dataset from a population-scale social media website.