Aerial target threat assessment based on gated recurrent unit and self-attention mechanism

Aerial threat assessment is a crucial link in modern air combat, whose result counts a great deal for commanders to make decisions. With the consideration that the existing threat assessment methods have difficulties in dealing with high dimensional time series target data, a threat assessment method based on self-attention mechanism and gated recurrent unit(SAGRU) is proposed. Firstly, a threat feature system including air combat situations and capability features is established. Moreover, a data augmentation process based on fractional Fourier transform(FRFT) is applied to extract more valuable information from time series situation features. Furthermore, aiming to capture key characteristics of battlefield evolution, a bidirectional GRU and SA mechanisms are designed for enhanced features.Subsequently, after the concatenation of the processed air combat situation and capability features, the target threat level will be predicted by fully connected neural layers and the softmax classifier. Finally, in order to validate this model, an air combat dataset generated by a combat simulation system is introduced for model training and testing. The comparison experiments show the proposed model has structural rationality and can perform threat assessment faster and more accurately than the other existing models based on deep learning.

Threat Assessment Method Based on Intuitionistic Fuzzy Similarity Measurement Reasoning with Orientation

The aim of this paper is to propose a threat assessment method based on intuitionistic fuzzy measurement reasoning with orientaion to deal with the shortcomings of the method proposed in [Ying-Jie Lei et al., Journal of Electronics and Information Technology 29(9)(2007)2077-2081] and [Dong-Feng Chen et al., Procedia Engineering 29(5)(2012)3302-3306] the ignorance of the influence of the intuitionistic index's orientation on the membership functions in the reasoning, which caused partial information loss in reasoning process. Therefore, we present a 3D expression of intuitionistic fuzzy similarity measurement, make an analysis of the constraints for intuitionistic fuzzy similarity measurement, and redefine the intuitionistic fuzzy similarity measurement. Moreover, in view of the threat assessment problem, we give the system variables of attribute function and assessment index, set up the reasoning system based on intuitionistic fuzzy similarity measurement with orientation, and design the reasoning rules, reasoning algorithms and fuzzy-resolving algorithms. Finally, through the threat assessment, some typical examples are cited to verify the validity and superiority of the method.

Assessment of Meteorological Threats to the Coordinated Search and Rescue of Unmanned/Manned Aircraft

The architecture and working principle of coordinated search and rescue system of unmanned/manned aircraft,which is composed of manned/unmanned aircraft and manned aircraft,were first introduced,and they can cooperate with each other to complete a search and rescue task.Secondly,a threat assessment method based on meteorological data was proposed,and potential meteorological threats,such as storms and rainfall,can be predicted by collecting and analyzing meteorological data.Finally,an experiment was carried out to evaluate the performance of the proposed method in different scenarios.The experimental results show that the coordinated search and rescue system of unmanned/manned aircraft can be used to effectively assess meteorological threats and provide accurate search and rescue guidance.

A Novel IoT Architecture, Assessment of Threats and Their Classification withMachine Learning Solutions

The Internet of Things(IoT)will significantly impact our social and economic lives in the near future.Many Internet of Things(IoT)applications aim to automate multiple tasks so inactive physical objects can behave independently of others.IoT devices,however,are also vulnerable,mostly because they lack the essential built-in security to thwart attackers.It is essential to perform the necessary adjustments in the structure of the IoT systems in order to create an end-to-end secure IoT environment.As a result,the IoT designs that are now in use do not completely support all of the advancements that have been made to include sophisticated features in IoT,such as Cloud computing,machine learning techniques,and lightweight encryption techniques.This paper presents a detailed analysis of the security requirements,attack surfaces,and security solutions available for IoT networks and suggests an innovative IoT architecture.The Seven-Layer Architecture in IoT provides decent attack detection accuracy.According to the level of risk they pose,the security threats in each of these layers have been properly categorized,and the essential evaluation criteria have been developed to evaluate the various threats.Also,Machine Learning algorithms like Random Forest and Support Vector Machines,etc.,and Deep Learning algorithms like Artificial Neural Networks,Q Learning models,etc.,are implemented to overcome the most damaging threats posing security breaches to the different IoT architecture layers.

Assessment and sequencing of air target threat based on intuitionistic fuzzy entropy and dynamic VIKOR

In view of the fact that traditional air target threat assessment methods are difficult to reflect the combat characteristics of uncertain, dynamic and hybrid formation, an algorithm is proposed to solve the multi-target threat assessment problems. The target attribute weight is calculated by the intuitionistic fuzzy entropy(IFE) algorithm and the time series weight is gained by the Poisson distribution method based on multi-times data. Finally,assessment and sequencing of the air multi-target threat model based on IFE and dynamic Vlse Kriterijumska Optimizacija I Kompromisno Resenje(VIKOR) is established with an example which indicates that the method is reasonable and effective.

Cooperative Threat Assessment of Multi-aircrafts Based on Synthetic Fuzzy Cognitive Map

Threat assessment is one of the most important parts of the tactical decisions,and it has a very important influence on task allocation.An application of fuzzy cognitive map(FCM) for target threat assessment in the air combat is introduced.Considering the fact that the aircrafts participated in the cooperation may not have the same threat assessment mechanism,two different FCM models are established.Using the method of combination,the model of cooperative threat assessment in air combat of multi-aircrafts is established.Simulation results show preliminarily that the method is reasonable and effective.Using FCM for threat assessment is feasible.

A Fuzzy Knowledge Based System in Situation and Threat Assessment

This paper examines the use in assisting naval operators in managing the of a fuzzy knowledge-based system （KBS） situation and threat assessment problem in a littoral environment. Under the scenario created involving air contacts in a littoral environment, the assessment of the KBS model is conducted and the results show that the correlation between assessment and human operation officers＇ judgment was high. The fuzzy KBS with its corresponding toolkits is much more flexible to be integrated with other components of a command and control system, while the fine-tuning of membership functions and fuzzy inference rules are intensive, this makes any further modification a non-trivial task.

Blockchain Security Threats and Collaborative Defense:A Literature Review

As a distributed database,the system security of the blockchain is of great significance to prevent tampering,protect privacy,prevent double spending,and improve credibility.Due to the decentralized and trustless nature of blockchain,the security defense of the blockchain system has become one of the most important measures.This paper comprehensively reviews the research progress of blockchain security threats and collaborative defense,and we first introduce the overview,classification,and threat assessment process of blockchain security threats.Then,we investigate the research status of single-node defense technology and multi-node collaborative defense technology and summarize the blockchain security evaluation indicators and evaluation methods.Finally,we discuss the challenges of blockchain security and future research directions,such as parallel detection and federated learning.This paper aims to stimulate further research and discussion on blockchain security,providing more reliable security guarantees for the use and development of blockchain technology to face changing threats and challenges through continuous updating and improvement of defense technologies.

An adaptive dwell time scheduling model for phased array radar based on three-way decision

Real-time resource allocation is crucial for phased array radar to undertake multi-task with limited resources,such as the situation of multi-target tracking,in which targets need to be prioritized so that resources can be allocated accordingly and effectively.A three-way decision-based model is proposed for adaptive scheduling of phased radar dwell time.Using the model,the threat posed by a target is measured by an evaluation function,and therefore,a target is assigned to one of the three possible decision regions,i.e.,positive region,negative region,and boundary region.A different region has a various priority in terms of resource demand,and as such,a different radar resource allocation decision is applied to each region to satisfy different tracking accuracies of multi-target.In addition,the dwell time scheduling model can be further optimized by implementing a strategy for determining a proper threshold of three-way decision making to optimize the thresholds adaptively in real-time.The advantages and the performance of the proposed model have been verified by experimental simulations with comparison to the traditional twoway decision model and the three-way decision model without threshold optimization.The experiential results demonstrate that the performance of the proposed model has a certain advantage in detecting high threat targets.

Game Theory Based Sensor Management in Reducing Target Threat Level Assessment Risk

Sensor management schemes are calculated to reduce target threat level assessment risk in this paper.Hidden Markov model and risk theory are combined to build the target threat level model firstly.Then the target threat level estimation risk is defined.And the sensor management schemes are optimized with the smallest target threat level assessment risk.What’s more,the game theory is applied to calculate the optimal sensor management scheme.Some simulations are conducted to prove that the proposed sensor management method is effective.