2022 14th International Conference on Computational Intelligence and Communication Networks (CICN)最新文献

Construction of Medical Big Data Processing and Service Framework for Digital Intelligent Transformation 面向数字化智能化转型的医疗大数据处理与服务框架构建

2022 14th International Conference on Computational Intelligence and Communication Networks (CICN) Pub Date : 2022-12-04 DOI: 10.1109/CICN56167.2022.10008296

Chuanyang Zhang, Yufei Pang, Yu Guo

引用次数: 0

Sentiment analysis for Algerian Dialect tweets 阿尔及利亚方言推文的情感分析

2022 14th International Conference on Computational Intelligence and Communication Networks (CICN) Pub Date : 2022-12-04 DOI: 10.1109/CICN56167.2022.10008314

Lamia Ouchene, Sadik Bessou

引用次数: 0

Comparative Analysis of Deep Fake Detection Techniques 深度造假检测技术的比较分析

2022 14th International Conference on Computational Intelligence and Communication Networks (CICN) Pub Date : 2022-12-04 DOI: 10.1109/CICN56167.2022.10008363

Fatim F. Alanazi

引用次数: 0

Malicious PDF detection Based on Machine Learning with Enhanced Feature Set 基于增强特征集的机器学习恶意PDF检测

2022 14th International Conference on Computational Intelligence and Communication Networks (CICN) Pub Date : 2022-12-04 DOI: 10.1109/CICN56167.2022.10008374

S. Yerima, A. Bashar, Ghazanfar Latif

{"title":"Malicious PDF detection Based on Machine Learning with Enhanced Feature Set","authors":"S. Yerima, A. Bashar, Ghazanfar Latif","doi":"10.1109/CICN56167.2022.10008374","DOIUrl":"https://doi.org/10.1109/CICN56167.2022.10008374","url":null,"abstract":"PDF is one of the most popular document file formats due to its flexibility, platform independence and ability to embed different types of content. Over the years, PDF has become a popular attack vector for spreading malware and compromising computer systems. Existing signature-based defense systems have extremely high recall rates, but quickly become obsolete and ineffective against zero-day attacks, which makes them easy to circumvent by malicious PDF files. Recently, Machine Learning (ML) has emerged as a viable tool to improve discovery of previously unseen attacks. Hence, in this paper we present enhanced ML-based models for the detection of malicious PDF documents. We develop an approach for ML-based detection with static features derived from PDF documents leveraging existing tools and propose new, previously unused features to enhance the performance of the ML-based classifiers. Our investigative study is conducted on the recently published Evasive-PDFMal2022 dataset, which was used to evaluate seven ML classifiers based on our proposed method. The EvasivePDFMal2022 dataset consists of 4,468 benign samples and 5,557 malicious PDF samples. The results of the experiments show that our proposed approach with the enhanced features enabled improved accuracies in five out of seven of the classifiers that were evaluated. The results demonstrate the potential of the new features to increase the robustness of feature-based PDF malware detection.","PeriodicalId":287589,"journal":{"name":"2022 14th International Conference on Computational Intelligence and Communication Networks (CICN)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126154139","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: 2

I-Light: An Improved Lighting System For Poultry Farms I-Light:改良的家禽农场照明系统

2022 14th International Conference on Computational Intelligence and Communication Networks (CICN) Pub Date : 2022-12-04 DOI: 10.1109/CICN56167.2022.10008367

Ertie Abana, Hubert Chester Damo, Ariel Lorenzo, Shedric Dimayuga, Peejay Paguirigan, Princess Gail Dineros, Korrrine Villaverde

{"title":"I-Light: An Improved Lighting System For Poultry Farms","authors":"Ertie Abana, Hubert Chester Damo, Ariel Lorenzo, Shedric Dimayuga, Peejay Paguirigan, Princess Gail Dineros, Korrrine Villaverde","doi":"10.1109/CICN56167.2022.10008367","DOIUrl":"https://doi.org/10.1109/CICN56167.2022.10008367","url":null,"abstract":"This study developed an improved lighting system called i-Light that incorporates three major factors in the growth of broilers which include color, photoperiod, and light intensity. Arduino Mega microcontroller was used to control the overall system. This system was compared to the existing traditional lighting system (TL) and LED lighting system (LL) in terms of broiler growth mortality rate and power usage. The results showed that the i-Light system performed better than both TL and LL systems. In terms of growth, the i-Light system demonstrates its ability to outperform TL and LL as seen by the fact that the i-Light system's weight gain on the final week of experimentation is 55.45% heavier than TL and 36.36% heavier than LL. It was also shown that the system logs the lowest mortality rate compared to the TL and LL system which records a 30% mortality rate which is more ideal than the 50% shown on TL and 40% for LL. The power usage results show that the i-Light used the least electricity. The i-Light system is 75.44% more efficient than the TL which saves up to 95.914 PHP monthly. On the other hand, i-Light is 63.12% more efficient than LL which saves up to 53.42 PHP per month. The i-Light system developed in the study can be a viable option for poultry farmers.","PeriodicalId":287589,"journal":{"name":"2022 14th International Conference on Computational Intelligence and Communication Networks (CICN)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114911306","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: 0

IoTZeroJar: Towards a Honeypot Architecture for Detection of Zero-Day Attacks in IoT IoTZeroJar:用于检测物联网零日攻击的蜜罐架构

2022 14th International Conference on Computational Intelligence and Communication Networks (CICN) Pub Date : 2022-12-04 DOI: 10.1109/CICN56167.2022.10008323

Mahmoud Ellouh, Mustafa Ghaleb, Muhamad Felemban

引用次数: 0

COVID-19 & Lung Disease Detection using Deep Learning 使用深度学习进行COVID-19和肺部疾病检测

2022 14th International Conference on Computational Intelligence and Communication Networks (CICN) Pub Date : 2022-12-04 DOI: 10.1109/CICN56167.2022.10008269

Manali Shukla, B. Tripathi, Malti Nagle, B. Chaurasia

引用次数: 5

Three-dimensional Reconstruction of Retinal Blood Vessels based on Binocular Vision 基于双目视觉的视网膜血管三维重建

2022 14th International Conference on Computational Intelligence and Communication Networks (CICN) Pub Date : 2022-12-04 DOI: 10.1109/CICN56167.2022.10008256

Chao-liang Wu, Zhiming Lv, Hua-zhu Liu, Xiaoqing Zhao

引用次数: 0

A Hybrid Stacked Ensemble Technique to Improve Classification Accuracy for Neurological Disorder Detection on Reddit posts 一种提高神经系统疾病检测准确率的混合堆叠集成技术

2022 14th International Conference on Computational Intelligence and Communication Networks (CICN) Pub Date : 2022-12-04 DOI: 10.1109/CICN56167.2022.10008283

Tejaswita Garg, S. K. Gupta

{"title":"A Hybrid Stacked Ensemble Technique to Improve Classification Accuracy for Neurological Disorder Detection on Reddit posts","authors":"Tejaswita Garg, S. K. Gupta","doi":"10.1109/CICN56167.2022.10008283","DOIUrl":"https://doi.org/10.1109/CICN56167.2022.10008283","url":null,"abstract":"Sentiment analysis helps in the early detection of depression as identify unpleasant mental states in people who are at risk for developing mental disorders. By utilizing both syntactic and semantic information, modelling approaches for sentiment analysis rely on machine learning algorithms. In this paper, a hybrid stacked ensemble learning approach has been used for the detection of depression as a neurological disorder. With the help of pre-trained word embeddings, the Word2Vec, GloVe and Fasttext are chosen for data preprocessing and feature extraction. Then, to identify depressed and non depressed identities, we integrate a hybrid stacked ensemble learning approach over Random Forest (RF), Support vector machines (SVM), K-Nearest Neighbor (KNN) and Catboost classifier (CBC) as base models whereas logistic regression (LR) as meta model classifier. The results of the experiments show that suggested model performs best with our proposed model than individual models. It is also found that with Word2Vec word embedding model, the proposed model achieved the higher accuracy as 99% in comparison to GloVe and Fasttext that categorizes depressed over non depressed users on the social media platforms.","PeriodicalId":287589,"journal":{"name":"2022 14th International Conference on Computational Intelligence and Communication Networks (CICN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129020862","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: 0

Exploring Narrative Court Documents for Use in Police Academic Education 探索叙事法庭文书在警察学术教育中的应用

2022 14th International Conference on Computational Intelligence and Communication Networks (CICN) Pub Date : 2022-12-04 DOI: 10.1109/CICN56167.2022.10008327

Ezdihar N. Bifari, W. Alhalabi

引用次数: 0