2022 10th International Symposium on Digital Forensics and Security (ISDFS)最新文献_第4页

Real-time Bitcoin price tendency awareness via social media content tracking 通过社交媒体内容跟踪实时比特币价格趋势

2022 10th International Symposium on Digital Forensics and Security (ISDFS) Pub Date : 2022-06-06 DOI: 10.1109/ISDFS55398.2022.9800793

Housam Moustafa, M. Malli, Hussein Hazimeh

{"title":"Real-time Bitcoin price tendency awareness via social media content tracking","authors":"Housam Moustafa, M. Malli, Hussein Hazimeh","doi":"10.1109/ISDFS55398.2022.9800793","DOIUrl":"https://doi.org/10.1109/ISDFS55398.2022.9800793","url":null,"abstract":"Cryptocurrency has been introduced as a relatively new financial system that is widely spread among traders and investors all over the globe. This type of digital currency is hugely attracting social media attention; Social media community along with investors and traders interact to share knowledge or to predict the price tendency of the market. Bitcoin, the leading cryptocurrency nowadays, has the highest market capitalization among other currencies. Which means that any major change in its price tendency will definitely affect the whole market and therefore other coins’ prices will surely rise or fall accordingly. We can assume that the greatest concern ever of all the traders around the world is to be alerted or aware of such major price tendency shifts in real time, in which may help them gain more profit or cut losses before it is late, or in either way predict the potential market movement of other digital currencies. It is reported that emotional interactions of the social media users especially on Twitter (one of the most globally used micro-blogging social networks especially related to cryptocurrency topics) have a great influence on the trend of the Bitcoin price. The huge number of daily active Twitter users with the enormous volume of tweets related to Bitcoin price tendency makes it remarkable regarding its impact on Bitcoin market interaction. In this paper, we will implement Apache Spark logistic regression model to process the large-scale data after having a sentimental analysis of Twitter tweets regarding Bitcoin, to predict the upcoming price tendency and classify an awareness level to alert potential traders and investors in real time about such potential market changes.","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":"131081016","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

Serverless Service Architectures and Security Minimals 无服务器服务架构和最低安全要求

2022 10th International Symposium on Digital Forensics and Security (ISDFS) Pub Date : 2022-06-06 DOI: 10.1109/ISDFS55398.2022.9800779

N. Coelho, Manuela Cruz-Cunha

{"title":"Serverless Service Architectures and Security Minimals","authors":"N. Coelho, Manuela Cruz-Cunha","doi":"10.1109/ISDFS55398.2022.9800779","DOIUrl":"https://doi.org/10.1109/ISDFS55398.2022.9800779","url":null,"abstract":"The Serverless subject is an emerging new world within technology scope. Although it seems to be by name a specific and a circumscriptive topic, it is a vast and complex subject that has an ongoing study and not a standardized use to be promoted as a technology standard. There are a variety of complex offers, platforms, products, applications, and ways to use, but, like other emerging and essential technologies, it has not yet been broadly accepted as architecture, and for cybersecurity, it’s complex to configure. This doesn't mean it is not usable or defective; it is only an anticipated conclusion and analysis of the factual and present panorama. This research has the objective of demonstrating the pontification of the use of Serverless architectures and the base security measures and risks to consider. This research reviewed prominent research articles from IEEE Journals and interviews with developers that are in contact with this technology, clarifying the central aspect of Serverless, its overall architecture as secure technology-usable-results cross platforms. This research aimed at the principal types of usage, security aspects within the mobile, its applications and networks parts and within the Cloud, the applications, filesystems, and possible other main uses. The study scope of these systems is circumscribed to the technology, tendencies, best and worst of its model, and lastly, its usage.","PeriodicalId":114335,"journal":{"name":"2022 10th International Symposium on Digital Forensics and Security (ISDFS)","volume":"17 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":"133591906","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: 5

Digital Forensics Analysis of Windows 11 Shellbag with Comparative Tools 使用比较工具对Windows 11 Shellbag进行数字取证分析

2022 10th International Symposium on Digital Forensics and Security (ISDFS) Pub Date : 2022-06-06 DOI: 10.1109/ISDFS55398.2022.9800788

Ashar Neyaz, N. Shashidhar, C. Varol, A. Rasheed

{"title":"Digital Forensics Analysis of Windows 11 Shellbag with Comparative Tools","authors":"Ashar Neyaz, N. Shashidhar, C. Varol, A. Rasheed","doi":"10.1109/ISDFS55398.2022.9800788","DOIUrl":"https://doi.org/10.1109/ISDFS55398.2022.9800788","url":null,"abstract":"Operating systems have various components that produce artifacts. These artifacts are the outcome of a user’s interaction with an application or program and the operating system’s logging capabilities. Thus, these artifacts have great importance in digital forensics investigations. For example, these artifacts can be utilized in a court of law to prove the existence of compromising computer system behaviors. One such component of the Microsoft Windows operating system is Shellbag, which is an enticing source of digital evidence of high forensics interest. The presence of a Shellbag entry means a specific user has visited a particular folder and done some customizations such as accessing, sorting, resizing the window, etc. In this work, we forensically analyze Shellbag as we talk about its purpose, types, and specificity with the latest version of the Windows 11 operating system and uncover the registry hives that contain Shellbag customization information. We also conduct in-depth forensics examinations on Shellbag entries using three tools of three different types, i.e., open-source, freeware, and proprietary tools. Lastly, we compared the capabilities of tools utilized in Shellbag forensics investigations.","PeriodicalId":114335,"journal":{"name":"2022 10th International Symposium on Digital Forensics and Security (ISDFS)","volume":"107 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":"132480340","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

Machine Learning-Based Security Solutions for Critical Cyber-Physical Systems 关键网络物理系统基于机器学习的安全解决方案

2022 10th International Symposium on Digital Forensics and Security (ISDFS) Pub Date : 2022-06-06 DOI: 10.1109/ISDFS55398.2022.9800811

Asad Raza, S. Memon, M. A. Nizamani, M. Shah

{"title":"Machine Learning-Based Security Solutions for Critical Cyber-Physical Systems","authors":"Asad Raza, S. Memon, M. A. Nizamani, M. Shah","doi":"10.1109/ISDFS55398.2022.9800811","DOIUrl":"https://doi.org/10.1109/ISDFS55398.2022.9800811","url":null,"abstract":"Cyber-Physical Systems(CPS) are complex critical infrastructure that assists society and provides efficient services to the people and governments. CPS uses many technologies including industrial control systems, smart grid, smart metering systems and the Industrial Internet of Things(IIoT). Extensive usage of ICT, giant physical components, and interconnected nature makes them extremely vulnerable to physical and cyber threats. A cyber-attack on a smart manufacturing system may halt the overall manufacturing process of the industry and reason to stop/reduce the production extensive time. Traditional security systems such as signature-based intrusion detection systems, firewalls and blacklisting are not effective due to high false alarm rates. Cyber-attacks such as DoS, DDoS, zero-day attacks and advanced persistent threats are advanced threats to CPS complex infrastructures. This paper discusses the current and future security challenges associated with CPS, datasets, and the impact of Machine Learning (ML) techniques proposed/used to detect and protect CPS from cyber-attacks. Numerous ML techniques such as unsupervised anomaly detection, Support Vector Machines (SVM), deep belief networks, recurrent neural networks and convolutional neural networks (CNN) have been proposed in the literature to mitigate risks for the critical CPS.","PeriodicalId":114335,"journal":{"name":"2022 10th International Symposium on Digital Forensics and Security (ISDFS)","volume":"67 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":"125108021","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

Unsupervised Machine Learning for Drone Forensics through Flight Path Analysis 无监督机器学习无人机取证通过飞行路径分析

2022 10th International Symposium on Digital Forensics and Security (ISDFS) Pub Date : 2022-06-06 DOI: 10.1109/ISDFS55398.2022.9800808

N. Syed, M. Khan, Nazeeruddin Mohammad, G. B. Brahim, Zubair A. Baig

引用次数: 0

Threat Modeling and Threat Intelligence System for Cloud using Splunk 基于Splunk的云威胁建模和威胁情报系统

2022 10th International Symposium on Digital Forensics and Security (ISDFS) Pub Date : 2022-06-06 DOI: 10.1109/ISDFS55398.2022.9800787

Ananthapadmanabhan A, K. Achuthan

引用次数: 2

Detection of Network Anomalies with Machine Learning Methods 用机器学习方法检测网络异常

2022 10th International Symposium on Digital Forensics and Security (ISDFS) Pub Date : 2022-06-06 DOI: 10.1109/ISDFS55398.2022.9800814

İhsan Rıza Kara, A. Varol

引用次数: 0

On the Digital Forensics of Social Networking Web-based Applications 基于web的社交网络应用的数字取证研究

2022 10th International Symposium on Digital Forensics and Security (ISDFS) Pub Date : 2022-06-06 DOI: 10.1109/ISDFS55398.2022.9800839

Basheer Al-Duwairi, Ahmed S. Shatnawi, Hala Jaradat, Afnan Al-Musa, Hamzah Al-Awadat

引用次数: 1

Swarm Intelligence Approach for Feature Selection Problem 特征选择问题的群体智能方法

2022 10th International Symposium on Digital Forensics and Security (ISDFS) Pub Date : 2022-06-06 DOI: 10.1109/ISDFS55398.2022.9800815

Eva Tuba, Adis Alihodžić, Una Tuba, Romana Capor-Hrosik, M. Tuba

{"title":"Swarm Intelligence Approach for Feature Selection Problem","authors":"Eva Tuba, Adis Alihodžić, Una Tuba, Romana Capor-Hrosik, M. Tuba","doi":"10.1109/ISDFS55398.2022.9800815","DOIUrl":"https://doi.org/10.1109/ISDFS55398.2022.9800815","url":null,"abstract":"Classification problems have been part of numerous real-life applications in fields of security, medicine, agriculture, and more. Due to the wide range of applications, there is a constant need for more accurate and efficient methods. Besides more efficient and better classification algorithms, the optimal feature set is a significant factor for better classification accuracy. In general, more features can better describe instances, but besides showing differences between instances of different classes, it can also capture many similarities that lead to wrong classification. Determining the optimal feature set can be considered a hard optimization problem for which different metaheuristics, like swarm intelligence algorithms can be used. In this paper, we propose an adaptation of hybridized swarm intelligence (SI) algorithm for feature selection problem. To test the quality of the proposed method, classification was done by k-means algorithm and it was tested on 17 benchmark datasets from the UCI repository. The results are compared to similar approaches from the literature where SI algorithms were used for feature selection, which proves the quality of the proposed hybridized SI method. The proposed method achieved better classification accuracy for 16 datasets. Higher classification accuracy was achieved while simultaneously reducing the number of used features.","PeriodicalId":114335,"journal":{"name":"2022 10th International Symposium on Digital Forensics and Security (ISDFS)","volume":"85 3 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":"130242963","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

The Digital Forensics of Cyber-Attacks at Electrical Power Grid Substation 电网变电站网络攻击的数字取证

2022 10th International Symposium on Digital Forensics and Security (ISDFS) Pub Date : 2022-06-06 DOI: 10.1109/ISDFS55398.2022.9800831

J. Pärssinen, P. Raussi, S. Noponen, Mikael Opas, J. Salonen

引用次数: 1