2022 10th International Symposium on Digital Forensics and Security (ISDFS)最新文献_第2页

Text Clustering of COVID-19 Vaccine Tweets COVID-19疫苗推文的文本聚类

2022 10th International Symposium on Digital Forensics and Security (ISDFS) Pub Date : 2022-06-06 DOI: 10.1109/ISDFS55398.2022.9800754

David Okore Ukwen, M. Karabatak

{"title":"Text Clustering of COVID-19 Vaccine Tweets","authors":"David Okore Ukwen, M. Karabatak","doi":"10.1109/ISDFS55398.2022.9800754","DOIUrl":"https://doi.org/10.1109/ISDFS55398.2022.9800754","url":null,"abstract":"The advent of the novel coronavirus disease (COVID-19) in late December 2019 led to the dramatic loss of human life worldwide and presented an unprecedented challenge to public health, education, social life, world economics, and the world of work. Equal access to safe and effective vaccines is very vital to ending the coronavirus pandemic. This research paper aims to perform text clustering on COVID-19 vaccine tweets. It investigates the optimal number of clusters prevalent in the COVID-19 vaccine corpus using deep learning techniques and machine learning algorithms. The study also investigates how using word embeddings can improve the accuracy of the proposed models by evaluating unsupervised learning methods. Machine learning clustering algorithms such as k-means and HDBSCAN, deep learning-based clustering techniques, and UMAP a dimensionality reduction algorithm were employed to perform text clustering. The results of this research showed the optimal clusters obtained by using deep learning clustering techniques and machine-learning algorithms for text clustering. HDBSCAN clustering algorithm showed better clustering results based on features learned while k-means performed better clustering based on various evaluation metrics.","PeriodicalId":114335,"journal":{"name":"2022 10th International Symposium on Digital Forensics and Security (ISDFS)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123524479","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

An Automated Framework for Generating Attack Graphs Using Known Security Threats 使用已知安全威胁生成攻击图的自动框架

2022 10th International Symposium on Digital Forensics and Security (ISDFS) Pub Date : 2022-06-06 DOI: 10.1109/ISDFS55398.2022.9800833

Rami Alnafrani, D. Wijesekera

引用次数: 0

Phishing Detection and Prevention using Chrome Extension 网络钓鱼检测和预防使用Chrome扩展

2022 10th International Symposium on Digital Forensics and Security (ISDFS) Pub Date : 2022-06-06 DOI: 10.1109/ISDFS55398.2022.9800826

M. Rose, N. Basir, Nur Fatin Nabila Binti Mohd Rafei Heng, N. J. Zaizi, M. Saudi

{"title":"Phishing Detection and Prevention using Chrome Extension","authors":"M. Rose, N. Basir, Nur Fatin Nabila Binti Mohd Rafei Heng, N. J. Zaizi, M. Saudi","doi":"10.1109/ISDFS55398.2022.9800826","DOIUrl":"https://doi.org/10.1109/ISDFS55398.2022.9800826","url":null,"abstract":"During pandemic COVID-19 outbreaks, number of cyber-attacks including phishing activities have increased tremendously. Nowadays many technical solutions on phishing detection were developed, however these approaches were either unsuccessful or unable to identify phishing pages and detect malicious codes efficiently. One of the downside is due to poor detection accuracy and low adaptability to new phishing connections. Another reason behind the unsuccessful anti-phishing solutions is an arbitrary selected URL-based classification features which may produce false results to the detection. Therefore, in this work, an intelligent phishing detection and prevention model is designed. The proposed model employs a self-destruct detection algorithm in which, machine learning, especially supervised learning algorithm was used. All employed rules in algorithm will focus on URL-based web characteristic, which attackers rely upon to redirect the victims to the simulated sites. A dataset from various sources such as Phish Tank and UCI Machine Learning repository were used and the testing was conducted in a controlled lab environment. As a result, a chrome extension phishing detection were developed based on the proposed model to help in preventing phishing attacks with an appropriate countermeasure and keep users aware of phishing while visiting illegitimate websites. It is believed that this smart phishing detection and prevention model able to prevent fraud and spam websites and lessen the cyber-crime and cyber-crisis that arise from year to year.","PeriodicalId":114335,"journal":{"name":"2022 10th International Symposium on Digital Forensics and Security (ISDFS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128485427","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: 3

Countering Steganographic Security with CNN 与CNN对抗隐写安全

2022 10th International Symposium on Digital Forensics and Security (ISDFS) Pub Date : 2022-06-06 DOI: 10.1109/ISDFS55398.2022.9800800

Narendrapurapu Surya Chandu, N. Subramanian

引用次数: 1

A Deep Learning Based Fast Face Detection and Recognition Algorithm for Forensic Analysis 基于深度学习的法医分析快速人脸检测与识别算法

2022 10th International Symposium on Digital Forensics and Security (ISDFS) Pub Date : 2022-06-06 DOI: 10.1109/ISDFS55398.2022.9800785

S. Karakus, M. Kaya, S. Tuncer, M. Bahsi, Merve Açikoğlu

{"title":"A Deep Learning Based Fast Face Detection and Recognition Algorithm for Forensic Analysis","authors":"S. Karakus, M. Kaya, S. Tuncer, M. Bahsi, Merve Açikoğlu","doi":"10.1109/ISDFS55398.2022.9800785","DOIUrl":"https://doi.org/10.1109/ISDFS55398.2022.9800785","url":null,"abstract":"Face detection and recognition applications have become an important research issue with the advent of artificial intelligence and deep learning studies, which have drawn much attention to researchers in recent years. The knowledge of retrieving contents from image, video, and audio files is seen as one of the vital influences in the field of digital forensics. In this study, we proposed a software that is supported with deep learning model which can analyze video and image files extracted from forensic evidence for either face detection or object recognition in a folder given as input and file a report of the images and videos that have been realized via this proposed application. The proposed deep learning model trained with YOLOv5 object detection algorithms can easily detect faces that are completely or partially visible under different light levels or in the image. This study shows that deep learning supported solutions can be easily preferred for real-time applications and time-consuming implementations to reduce fatigue and error-prone incurred during forensic investigations.","PeriodicalId":114335,"journal":{"name":"2022 10th International Symposium on Digital Forensics and Security (ISDFS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131338950","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

A New Chaos-Based Lightweight Encryption Mechanism for Microcomputers 一种新的基于混沌的微型计算机轻量级加密机制

2022 10th International Symposium on Digital Forensics and Security (ISDFS) Pub Date : 2022-06-06 DOI: 10.1109/ISDFS55398.2022.9800803

Harun Emre Kiran, A. Akgul, O. Yildiz

{"title":"A New Chaos-Based Lightweight Encryption Mechanism for Microcomputers","authors":"Harun Emre Kiran, A. Akgul, O. Yildiz","doi":"10.1109/ISDFS55398.2022.9800803","DOIUrl":"https://doi.org/10.1109/ISDFS55398.2022.9800803","url":null,"abstract":"Many casual objects are now connected to the internet. The objects are managed with micro-computers for cost-effectiveness. Because this computer has limited processing and storage, they usually act as a collection of data. The data are processed by powerful computers. Therefore, data needs to be transferred to the computers. However, since most of the objects are connected to the internet in a wireless environment, they cause significant security weakness. In this study, a new chaos-based lightweight encryption mechanism is proposed to provide a solution to the problem. The aim of the study is to reduce the overhead of microcomputers and to have strong encryption of data. The 3-dimensional Lorenz chaotic system is used to test the performance of the study. According to the experimental results obtained, it has been observed that the proposed working image data is strongly encrypted and with less processing and storage than traditional encryption algorithms. This study will be used for the security of microcomputers to be used in future studies and more detailed performance tests of this method will be carried out.","PeriodicalId":114335,"journal":{"name":"2022 10th International Symposium on Digital Forensics and Security (ISDFS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125576440","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

A New Method of Automatic Content Analysis in Disaster Management 灾害管理中自动内容分析的新方法

2022 10th International Symposium on Digital Forensics and Security (ISDFS) Pub Date : 2022-06-06 DOI: 10.1109/ISDFS55398.2022.9800778

Ali Burak Can, I. B. Parlak, T. Acarman

引用次数: 0

A deep learning-enhanced botnet detection system based on Android manifest text mining 基于Android清单文本挖掘的深度学习增强僵尸网络检测系统

2022 10th International Symposium on Digital Forensics and Security (ISDFS) Pub Date : 2022-06-06 DOI: 10.1109/ISDFS55398.2022.9800817

S. Yerima, Yi Min To

引用次数: 1

Network Intrusion Detection Packet Classification with the HIKARI-2021 Dataset: a study on ML Algorithms 基于HIKARI-2021数据集的网络入侵检测数据包分类:ML算法研究

2022 10th International Symposium on Digital Forensics and Security (ISDFS) Pub Date : 2022-06-06 DOI: 10.1109/ISDFS55398.2022.9800807

Rui Fernandes, Nuno Lopes

引用次数: 3

AIFIS: Artificial Intelligence (AI)-Based Forensic Investigative System AIFIS:基于人工智能(AI)的法医调查系统

2022 10th International Symposium on Digital Forensics and Security (ISDFS) Pub Date : 2022-06-06 DOI: 10.1109/ISDFS55398.2022.9800801

Rami Alnafrani, D. Wijesekera

引用次数: 1