Computer threat information filtering algorithm based on fusion difference

2022 ◽  
Vol 20 (1) ◽  
pp. 34
Author(s):  
Liang Qian
Keyword(s):  
Information Filtering ◽  
Filtering Algorithm

scholarly journals An Enhanced Trust Mechanism with Consensus-Based False Information Filtering Algorithm against Bad-Mouthing Attacks and False-Praise Attacks in WSNs

Electronics ◽  
2019 ◽  
Vol 8 (11) ◽  
pp. 1359 ◽  
Author(s):  
Suh ◽  
Cho
Keyword(s):  
Sensor Node ◽  
Information Filtering ◽  
Human Society ◽  
False Information ◽  
Security Vulnerabilities ◽  
Trust Mechanism ◽  
Filtering Algorithm ◽  
Software Modules ◽  
Neighbor List ◽  
Local Storage

To defend against insider attacks in wireless sensor networks (WSNs), trust mechanisms (TMs) using the notion of trust in human society have been proposed and are still actively researched. In the WSN with a trust mechanism (TM), each sensor node evaluates the trustworthiness of its neighbor sensors based on their behaviors, for example packet forwarding, and collaborates only with trustworthy neighbors while removing untrustworthy neighbor from its neighbor list. The reputation system (RS) is an advanced type of trust mechanism that evaluates the trustworthiness of a node by additionally considering neighbor nodes’ observations or evaluations about it. However, intelligent inside attackers in WSNs can discover the security vulnerabilities of trust mechanisms by examining the operations of TM (or RS), because the software modules of the TM (or RS) are installed and operating in their local storage and memory, and thus, they can avoid detection by the trust mechanisms. Bad-mouthing attacks and false-praise attacks are well-known examples of such intelligent insider attacks. We observed that existing trust mechanisms do not have effective countermeasures to defend against such attacks. In this paper, we propose an enhanced trust mechanism with a consensus-based false information filtering algorithm (TM-CFIFA) that can effectively defend against bad-mouthing attacks and false-praise attacks. According to our experiment results, compared with an existing representative RS model, our TM-CFIFA shortened the detection time of a packet drop attacker, which is supported by a false-praise attacker by at least 83%, and also extended the lifetime of a victim sensor node that is under bad-mouthing attacks by at least 15.8%.

Research and Application of Filtering Algorithm in Internet of Things

2013 ◽  
Vol 330 ◽  
pp. 1028-1031
Author(s):  
Jian Yi Li ◽  
Hui Juan Wang ◽  
Quan Bo Yuan
Keyword(s):  
Internet Of Things ◽  
Information Filtering ◽  
The Internet ◽  
Distributed Network ◽  
Intelligent Monitoring ◽  
Network Information ◽  
Filtering Algorithm ◽  
Algorithm Efficiency ◽  
Multiple Components ◽  
Monitoring Platform

This paper analyzes the problems of Research and application of filtering algorithm in internet of things.Internet of things is composed of multiple components, to form a distributed network in the Internet, the purpose of this distributed network information filtering algorithm is increasing filter algorithm efficiency, and combinating the laboratory intelligent monitoring platform,it can effectively solve the problem caused by defects of filtering algorithm in internet of things.

Web Information Filtering Technology Based on Mutual Information

2014 ◽  
Vol 687-691 ◽  
pp. 2224-2228 ◽  
Author(s):  
Li Zhu ◽  
Lan Bai
Keyword(s):  
Mutual Information ◽  
Information Filtering ◽  
Culture Industry ◽  
Web Page ◽  
Healthy Development ◽  
Filtering Algorithm ◽  
Model Study ◽  
Series Of Experiments ◽  
The Impact ◽  
Negative Factors

The popularity of Internet application makes web page illegal information filtering an important work. Based on mutual information model study of illegal information filtering in web page, this article first elaborated the theoretical basis of mutual information filtering algorithm, then designed a mutual information filtering algorithm based on improved formula, and designed and implemented illegal web page filtering system by using the algorithm and related technology and did a series of experiments, which effectively reduced the impact of negative factors on healthy development of network culture industry, and it is advantageous to the purification of social morality and social stability.

Cooperative detection based on the adaptive interacting multiple model-information filtering algorithm

2019 ◽  
Vol 93 ◽  
pp. 105310 ◽  
Author(s):  
Shuai Zhang ◽  
Yang Guo ◽  
Zhaoxing Lu ◽  
Shicheng Wang ◽  
Zhiguo Liu
Keyword(s):  
Information Filtering ◽  
Interacting Multiple Model ◽  
Multiple Model ◽  
Filtering Algorithm ◽  
Cooperative Detection

Information Filtering Algorithm Based on Semantic Understanding

2010 ◽  
Vol 32 (10) ◽  
pp. 2324-2330 ◽  
Author(s):  
Bo Zhang ◽  
Yang Xiang ◽  
Jian Wang
Keyword(s):  
Information Filtering ◽  
Filtering Algorithm
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