scholarly journals Analysis of Usability for the Dice CAPTCHA

Information ◽  
2019 ◽  
Vol 10 (7) ◽  
pp. 221
Author(s):  
Alessia Amelio ◽  
Ivo Rumenov Draganov ◽  
Radmila Janković ◽  
Dejan Tanikić
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Association Rule ◽  
Association Rule Mining ◽  
Internet Usage ◽  
Solution Time ◽  
The Internet ◽  
Rule Mining ◽  
Artificial Neural

This paper explores the usability of the Dice CAPTCHA via analysis of the time spent to solve the CAPTCHA, and number of tries for solving the CAPTCHA. The experiment was conducted on a set of 197 subjects who use the Internet, and are discriminated by age, daily Internet usage in hours, Internet experience in years, and type of device where a solution to the CAPTCHA is found. Each user was asked to find a solution to the Dice CAPTCHA on a tablet or laptop, and the time to successfully find a solution to the CAPTCHA for a given number of attempts was registered. Analysis was performed on the collected data via association rule mining and artificial neural network. It revealed that the time to find a solution in a given number of attempts of the CAPTCHA depended on different combinations of values of user’s features, as well as the most meaningful features influencing the solution time. In addition, this dependence was explored through prediction of the CAPTCHA solution time from the user’s features via artificial neural network. The obtained results are very helpful to analyze the combination of features having an influence on the CAPTCHA solution, and consequently, to find the CAPTCHA mostly complying to the postulate of “ideal” test.

Using Artificial Neural Network to Filter Spam for Chinese Mail

2011 ◽  
Vol 55-57 ◽  
pp. 762-766
Author(s):  
Shih Ming Pi ◽  
Hsiu Li Liao ◽  
Su Houn Liu ◽  
Ding Kang Liu
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Text Classification ◽  
False Positives ◽  
The Internet ◽  
Network Approach ◽  
Good Tool ◽  
Neural Network Approach ◽  
Artificial Neural ◽  
Computing Speed

As the Internet developed, the problem of spam has become increasingly serious. Not only caused great distress to individuals, but also have a great business costs. With improvements in computing speed, neural network is becoming a very good tool for text classification. The purpose of this study is to conduct few experiments by using neural network approach for Chinese mails’ content. The result shows that neural network approach is effective for Chinese mails’ spam-identification and the adjustments of some parameters (the number of keywords, the number of nodes, and the number of categories) also increase the accurate rate, while reducing false positives.

scholarly journals Security-Aware Routing Protocol Based on Artificial Neural Network Algorithm and 6LoWPAN in the Internet of Things

2022 ◽  
Vol 2022 ◽  
pp. 1-8
Author(s):  
Jiangdong Lu ◽  
Dongfang Li ◽  
Penglong Wang ◽  
Fen Zheng ◽  
Meng Wang
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Internet Of Things ◽  
Routing Protocols ◽  
Intelligent Systems ◽  
Smart Devices ◽  
The Internet ◽  
Routing Mechanism ◽  
Artificial Neural ◽  
The Internet Of Things

Today, with increasing information technology such as the Internet of Things (IoT) in human life, interconnection and routing protocols need to find optimal solution for safe data transformation with various smart devices. Therefore, it is necessary to provide an enhanced solution to address routing issues with respect to new interconnection methodologies such as the 6LoWPAN protocol. The artificial neural network (ANN) is based on the structure of intelligent systems as a branch of machine interference, has shown magnificent results in previous studies to optimize security-aware routing protocols. In addition, IoT devices generate large amounts of data with variety and accuracy. Therefore, higher performance and better data handling can be achieved when this technology incorporates data for sending and receiving nodes in the environment. Therefore, this study presents a security-aware routing mechanism for IoT technologies. In addition, a comparative analysis of the relationship between previous approaches discusses with quality of service (QoS) factors such as throughput and accuracy for improving routing mechanism. Experimental results show that the use of time-division multiple access (TDMA) method to schedule the sending and receiving of data and the use of the 6LoWPAN protocol when routing the sending and receiving of data can carry out attacks with high accuracy.

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