2019 IEEE 2nd International Conference on Information and Computer Technologies (ICICT)最新文献

Anomaly Identification in A Liquid-Coffee Vending Machine Using Electrical Current Waveforms 基于电流波形的液体咖啡自动售货机异常识别

2019 IEEE 2nd International Conference on Information and Computer Technologies (ICICT) Pub Date : 2019-03-14 DOI: 10.1109/INFOCT.2019.8711414

Y. Ishii, Eisuke Saneyoshi, Mitsuru Sendoda, Reishi Kondo

引用次数: 4

On the Top Threats to Cyber Systems 网络系统面临的主要威胁

2019 IEEE 2nd International Conference on Information and Computer Technologies (ICICT) Pub Date : 2019-03-14 DOI: 10.1109/INFOCT.2019.8711324

H. Kettani, Polly Wainwright

{"title":"On the Top Threats to Cyber Systems","authors":"H. Kettani, Polly Wainwright","doi":"10.1109/INFOCT.2019.8711324","DOIUrl":"https://doi.org/10.1109/INFOCT.2019.8711324","url":null,"abstract":"The technological innovation of cyber systems and increase dependence of individuals, societies and nations on them has brought new, real and everchanging threat landscapes. In fact, the threats evolving faster than they can be assessed. The technological innovation that brought ease and efficiency to our lives, has been met by similar innovation to take advantage of cyber systems for other gains. More threat actors are noted to be sponsored by nation-states and the skills and capabilities of organizations to defend against these attacks are lagging. This warrants an increase in automation of threat analysis and response as well as increased adoption of security measures by at-risk organizations. Thus, to properly prepare defenses and mitigations to the threats introduced by cyber, it is necessary to understand these threats. Accordingly, this paper provides an overview of top cyber security threats in together with current and emerging trends. The analyses include general trends in the complexity of attacks, actors, and the maturity of skills and capabilities of organizations to defend against attacks. Top threats are discussed with regard to instances of attacks and strategies for mitigation within the kill chain. A brief discussion of threat agents and attack vectors adds context to the threats.","PeriodicalId":369231,"journal":{"name":"2019 IEEE 2nd International Conference on Information and Computer Technologies (ICICT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125280801","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 28

Two Adaptive Schemes for Image Sharpening 图像锐化的两种自适应方案

2019 IEEE 2nd International Conference on Information and Computer Technologies (ICICT) Pub Date : 2019-03-14 DOI: 10.1109/INFOCT.2019.8711269

Jian-ao Lian

引用次数: 2

Research on Personal Identity Verification Based on Convolutional Neural Network 基于卷积神经网络的个人身份验证研究

2019 IEEE 2nd International Conference on Information and Computer Technologies (ICICT) Pub Date : 2019-03-14 DOI: 10.1109/INFOCT.2019.8711104

Jia Wu, Chao Liu, Qiyu Long, Weiyan Hou

{"title":"Research on Personal Identity Verification Based on Convolutional Neural Network","authors":"Jia Wu, Chao Liu, Qiyu Long, Weiyan Hou","doi":"10.1109/INFOCT.2019.8711104","DOIUrl":"https://doi.org/10.1109/INFOCT.2019.8711104","url":null,"abstract":"In this paper, we propose a Personal Identity Verification (PIV) method based on 2-D convolutional neural network (CNN) by using electrocardiosignal (ECG singles). CNN shows outstanding performance in the field of image recognition nowadays, in order to make better use of this advantage, we innovatively convert electrocardiosignal into 2-D grayscale instead of traditional ECG. While ensuring that the image contains a complete cardiac cycle, it also enables the network to fully learn both the characteristics of the electrocardiosignal period and characteristics between each electrocardiosignal period. Optimization of the proposed CNN classifier includes various deep learning techniques such as batch normalization, data augmentation, Xavier initialization, and dropout. As a result, our classifier achieved 99.90% average accuracy. To precisely validate our CNN classifier, 10-fold cross-validation was performed at the evaluation which involves every ECG recording as a test data. Our experimental results have successfully validated that the proposed CNN classifier with the transformed ECG images can achieve excellent identification accuracy.","PeriodicalId":369231,"journal":{"name":"2019 IEEE 2nd International Conference on Information and Computer Technologies (ICICT)","volume":"os-39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127779478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Social Media Messages During Disasters in Japan : An Empirical Study of 2018 Osaka North Earthquake in Japan 日本灾害期间的社交媒体信息:2018年日本大阪北地震的实证研究

2019 IEEE 2nd International Conference on Information and Computer Technologies (ICICT) Pub Date : 2019-03-14 DOI: 10.1109/INFOCT.2019.8711036

Kemachart Kemavuthanon, O. Uchida

引用次数: 3

A Random Forest Approach for Predicting the Microwave Drying Process of Amaranth Seeds 用随机森林方法预测苋菜种子微波干燥过程

2019 IEEE 2nd International Conference on Information and Computer Technologies (ICICT) Pub Date : 2019-03-14 DOI: 10.1109/INFOCT.2019.8711122

S. Bravo, Ángel H. Moreno

引用次数: 2

A Survey of Formal Specification Application to Safety Critical Systems 形式规范在安全关键系统中的应用综述

2019 IEEE 2nd International Conference on Information and Computer Technologies (ICICT) Pub Date : 2019-03-14 DOI: 10.1109/INFOCT.2019.8711369

S. P. Nanda, Emanuel S. Grant

引用次数: 6

TFDroid: Android Malware Detection by Topics and Sensitive Data Flows Using Machine Learning Techniques TFDroid: Android恶意软件检测的主题和敏感数据流使用机器学习技术

2019 IEEE 2nd International Conference on Information and Computer Technologies (ICICT) Pub Date : 2019-03-14 DOI: 10.1109/INFOCT.2019.8711179

Songhao Lou, Shaoyin Cheng, J. Huang, Fan Jiang

引用次数: 27

Creation of Adversarial Examples with Keeping High Visual Performance 创造具有高视觉表现的对抗性示例

2019 IEEE 2nd International Conference on Information and Computer Technologies (ICICT) Pub Date : 2019-03-14 DOI: 10.1109/INFOCT.2019.8710918

Tomoka Azakami, Chihiro Shibata, R. Uda, T. Kinoshita

{"title":"Creation of Adversarial Examples with Keeping High Visual Performance","authors":"Tomoka Azakami, Chihiro Shibata, R. Uda, T. Kinoshita","doi":"10.1109/INFOCT.2019.8710918","DOIUrl":"https://doi.org/10.1109/INFOCT.2019.8710918","url":null,"abstract":"The accuracy of the image classification by the convolutional neural network is exceeding the ability of human being and contributes to various fields. However, the improvement of the image recognition technology gives a great blow to security system with an image such as CAPTCHA. In particular, since the character string CAPTCHA has already added distortion and noise in order not to be read by the computer, it becomes a problem that the human readability is lowered. Adversarial examples is a technique to produce an image letting an image classification by the machine learning be wrong intentionally. The best feature of this technique is that when human beings compare the original image with the adversarial examples, they cannot understand the difference on appearance. However, Adversarial examples that is created with conventional FGSM cannot completely misclassify strong nonlinear networks like CNN. Osadchy et al. have researched to apply this adversarial examples to CAPTCHA and attempted to let CNN misclassify them. However, they could not let CNN misclassify character images. In this research, we propose a method to apply FGSM to the character string CAPTCHAs and to let CNN misclassified them.","PeriodicalId":369231,"journal":{"name":"2019 IEEE 2nd International Conference on Information and Computer Technologies (ICICT)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132431152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

ITIKI Plus: A Mobile Based Application for Integrating Indigenous Knowledge and Scientific Agro-Climate Decision Support for Africa’s Small-Scale Farmers ITIKI Plus:为非洲小农整合本土知识和科学农业气候决策支持的移动应用程序

2019 IEEE 2nd International Conference on Information and Computer Technologies (ICICT) Pub Date : 2019-03-14 DOI: 10.1109/INFOCT.2019.8711059

M. Masinde, Portia Naledi Thothela

引用次数: 5