Nuno Martins, Pedro Costa, Alexandre Esteves, Tomás Martins, S. Nicola, Alberto Pereira
{"title":"New Online Reality","authors":"Nuno Martins, Pedro Costa, Alexandre Esteves, Tomás Martins, S. Nicola, Alberto Pereira","doi":"10.1109/ISDFS55398.2022.9800789","DOIUrl":"https://doi.org/10.1109/ISDFS55398.2022.9800789","url":null,"abstract":"At the beginning of 2020 we assisted to an enormous increase of remote working due to Covid-19 pandemic. Largest effects arise, the increase in flexible working has impact on how people use their home, shops, offices, enterprises. All questions about positive and negative implications cannot leave people's mind. In this ecosystem at any point employees will inevitably have to work with other people at some point, must interact with clients and customers, need to work with colleagues, managers, suppliers and build relationships with them. Changing mindset, it is not an easy task. Some companies are creating solutions with that we do not forget to maintain personal relationships between employees. This paper discuss that points and give a prototype, to try effectively tackle a problem.","PeriodicalId":114335,"journal":{"name":"2022 10th International Symposium on Digital Forensics and Security (ISDFS)","volume":"135 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":"134342014","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}
{"title":"The Relationship between Nomophobia and Perceived Socialization in the Online Learning Environment","authors":"Songül Karabatak, Sevinç Ay, M. Karabatak","doi":"10.1109/ISDFS55398.2022.9800824","DOIUrl":"https://doi.org/10.1109/ISDFS55398.2022.9800824","url":null,"abstract":"This research aimed to examine the relationship between teacher candidates' nomophobia behavior tendency and their perceptions of socialization in the online environment. For this purpose, the research was designed in the relational survey model within the scope of quantitative research. The sample of the research consists of teacher candidates at the Faculty of Education at Fırat University. To collect the data, the Nomophobia Questionnaire and the Perceived sociability in the online learning environments Scale were used. At the end of the study, it was revealed that the nomophobia behavior tendencies of the teacher candidates were at a moderate level and their perceived socialization in the online learning environment was at the level of undecided. The nomophobia levels of female teacher candidates were found to be significantly higher than males, but the perceived socialization levels of teacher candidates in the online learning environment do not differ significantly according to the gender variable. According to another finding of the study, the teacher candidates’ nomophobia levels changed according to the grade variable. The teacher candidates’ nomophobia levels differed significantly between the 1st and 2nd grades in general. It was also seen that there was a positive, significant, and low-level relationship between the nomophobia levels of teacher candidates and their perceptions of socialization in the online learning environment. Various suggestions are presented regarding the results obtained from the study.","PeriodicalId":114335,"journal":{"name":"2022 10th International Symposium on Digital Forensics and Security (ISDFS)","volume":"76 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":"123603725","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}
Innocent Paschal Mgembe, D. L. Msongaleli, Naveen Kumar Chaundhary
{"title":"Progressive Standard Operating Procedures for Darkweb Forensics Investigation","authors":"Innocent Paschal Mgembe, D. L. Msongaleli, Naveen Kumar Chaundhary","doi":"10.1109/ISDFS55398.2022.9800830","DOIUrl":"https://doi.org/10.1109/ISDFS55398.2022.9800830","url":null,"abstract":"With the advent of information and communication technology, the digital space is becoming a playing ground for criminal activities. Criminals typically prefer darkness or a hidden place to perform their illegal activities in a real-world while sometimes covering their face to avoid being exposed and getting caught. The same applies in a digital world where criminals prefer features which provide anonymity or hidden features to perform illegal activities. It is from this spirit the Darkweb is attracting all kinds of criminal activities conducted over the Internet such as selling drugs, illegal weapons, child pornography, assassination for hire, hackers for hire, and selling of malicious exploits, to mention a few. Although the anonymity offered by Darkweb can be exploited as a tool to arrest criminals involved in cybercrime, an in-depth research is needed to advance criminal investigation on Darkweb. Analysis of illegal activities conducted in Darkweb is in its infancy and faces several challenges like lack of standard operating procedures. This study proposes progressive standard operating procedures (SOPs) for Darkweb forensics investigation. We provide the four stages of SOP for Darkweb investigation. The proposed SOP consists of the following stages; identification and profiling, discovery, acquisition and preservation, and the last stage is analysis and reporting. In each stage, we consider the objectives, tools and expected results of that particular stage. Careful consideration of this SOP revealed promising results in the Darkweb investigation.","PeriodicalId":114335,"journal":{"name":"2022 10th International Symposium on Digital Forensics and Security (ISDFS)","volume":"87 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":"123950395","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}
{"title":"‘Unified Side-Channel Attack - Model’ (USCA-M): An Extension with Biometrics Side-Channel Type","authors":"Andrew Johnson, Richard O. Ward","doi":"10.1109/ISDFS55398.2022.9800753","DOIUrl":"https://doi.org/10.1109/ISDFS55398.2022.9800753","url":null,"abstract":"This paper presents the ‘Unified Side-Channel Attack Model’ (USCA-M) with an additional side-channel type of ‘Biometrics.’ The original published paper ‘Introducing the Unified Side-Channel Attack–Model (USCA-M)’ [1] was presented and published through the International Symposium on Digital Forensics and Security (ISDFS) conference in 2020 [1]. The USCA-M model was initially compiled by research on side-channel attacks (SCAs) from published journal articles and conference papers between 2015 and 2020. The study found that SCAs can be categorized into three main areas: SCA types, SCA methods, and SCA techniques. The USCA-M provides a unified model to categorize present and future SCA vulnerabilities and exploit techniques found. Its future use would provide a reference point for organizations to identify and place a found SCA within a standard or unified categorization. It can also be used to granulate SCA techniques into identifiable components to assist in defending SCAs, such as code pattern recognition and intrusion detection systems (IDS).","PeriodicalId":114335,"journal":{"name":"2022 10th International Symposium on Digital Forensics and Security (ISDFS)","volume":"28 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":"114261011","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}
{"title":"Classification of Tissue Types in Histology Images Using Graph Convolutional Networks","authors":"Esra Tepe, G. Bilgin","doi":"10.1109/ISDFS55398.2022.9800776","DOIUrl":"https://doi.org/10.1109/ISDFS55398.2022.9800776","url":null,"abstract":"This article uses Graphic Neural Network (GNN) models on histology images to classify tissue to find phenotypes. The majority of tissue phenotyping approaches are confined to tumor and stroma classification and necessitate a significant number of histology images. In this study, Graphics Convolutional Network (GCN) is used on the CRC Tissue Phenotyping dataset, which consists of seven tissue phenotypes, namely Benign, Complex Stroma, Debris, Inflammatory, Muscle, Stroma, and Tumor. First, the input images are converted into superpixels using the SLIC algorithm and the region neighborhood graphs (RAGs), where each superpixel is a node, and the edges connect neighboring superpixels to each other are converted. Finally, graphic classification is performed on the graphic data set using GCN.","PeriodicalId":114335,"journal":{"name":"2022 10th International Symposium on Digital Forensics and Security (ISDFS)","volume":"37 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":"134349314","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}
{"title":"Technical and Legal Strategic Approaches Protecting the Privacy of Personal Data in Cloud-Based Big Data Applications","authors":"Süleyman Muhammed Arikan","doi":"10.1109/ISDFS55398.2022.9800794","DOIUrl":"https://doi.org/10.1109/ISDFS55398.2022.9800794","url":null,"abstract":"As a result of the importance given to the privacy over the years, various legal arrangements and technical solutions have been provided. Thanks to studies from both perspectives, despite the development of technology, the importance given to the concept of personal data has increased day by day and has reached a level that cannot be ignored. By the way, the characteristics of data have also changed with the digital revolution, and today, big data differs from traditional data in many ways. Thus traditional methods can no longer be effective in protecting the privacy. Also, cloud computing, which provides practical solutions for problems encountered in many subjects, is frequently preferred by solution architects in big data applications, and due to the data it contains, it exposes its users to various risks within the scope of being subject to diversified violations. This situation imposes different roles and responsibilities on various stakeholders for the protection of personal data. To fulfill all these roles and responsibilities, complementary and adequate strategic approaches should be used. The aim of this study is to analyze, discuss, and provide privacy protection approaches for cloud-based big data applications. First of all, from technical and legal perspectives, examinations in cloud computing and big data have been performed separately. Then existing methods, possible technical solutions, legal requirements, and obligations are shown and discussed. Lastly, within the scope of cloud-based big data applications, additional inferences have been made and shared.","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":"128169799","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}
{"title":"Procedural Information Security Countermeasure Awareness and Cybersecurity Protection Motivation in Enhancing Employee’s Cybersecurity Protective Behaviour","authors":"N. Humaidi, Saif Hussein Abdallah Alghazo","doi":"10.1109/ISDFS55398.2022.9800834","DOIUrl":"https://doi.org/10.1109/ISDFS55398.2022.9800834","url":null,"abstract":"Radical changes in the Industrial Revolution 4.0 (IR4.0) have provoked several organizations in developed and emerging economies to constantly re-evaluate cybersecurity protective behaviour among their employees. Evidence from an emerging economy like Malaysia suggests that security awareness influences employees’ psychological factors and leads to enhancing employees’ cybersecurity protective behaviour to become actively engaged in effective cybersecurity practices. By overlooking these factors, employees are consequently exposed to various cybersecurity threats which could have adverse impacts on their organisations. Therefore, this study was conducted to explore the direct effect of procedural information security countermeasure (PCM) awareness on protection motivation components in enhancing employees’ cybersecurity protective behaviour. This study extended the Protection Motivation Theory (PMT) and the online survey was conducted to get feedback from the employees in various sectors within Klang Valley, Malaysia. A total of 245 responses were received. The results show that procedural security countermeasure awareness does positively influence protection motivation components, except for self-efficacy. Meanwhile, threat appraisal and coping appraisal positively influence some of the dimensions of cybersecurity protective behaviour. The research findings would serve as evidence that is fundamental to enhancing cybersecurity practices of urban community employees in Malaysia. Congruent with the diverse recent impacts of the IR4.0, the research would help to bolster cybersecurity-related policy implications that resonate with the Malaysian government agenda.","PeriodicalId":114335,"journal":{"name":"2022 10th International Symposium on Digital Forensics and Security (ISDFS)","volume":"11 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":"126664396","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}
{"title":"Verifying Integrity of Deep Ensemble Models by Lossless Black-box Watermarking with Sensitive Samples","authors":"Li-Chiun Lin, Hanzhou Wu","doi":"10.1109/ISDFS55398.2022.9800818","DOIUrl":"https://doi.org/10.1109/ISDFS55398.2022.9800818","url":null,"abstract":"With the widespread use of deep neural networks (DNNs) in many areas, more and more studies focus on protecting DNN models from intellectual property (IP) infringement. Many existing methods apply digital watermarking to protect the DNN models. The majority of them either embed a watermark directly into the internal network structure/parameters or insert a zero-bit watermark by fine-tuning a model to be protected with a set of so-called trigger samples. Though these methods work very well, they were designed for individual DNN models, which cannot be directly applied to deep ensemble models (DEMs) that combine multiple DNN models to make the final decision. It motivates us to propose a novel black-box watermarking method in this paper for DEMs, which can be used for verifying the integrity of DEMs. In the proposed method, a certain number of sensitive samples are carefully selected through mimicking real-world DEM attacks and analyzing the prediction results of the sub-models of the non-attacked DEM and the attacked DEM on the carefully crafted dataset. By analyzing the prediction results of the target DEM on these carefully crafted sensitive samples, we are able to verify the integrity of the target DEM. Different from many previous methods, the proposed method does not modify the original DEM to be protected, which indicates that the proposed method is lossless. Experimental results have shown that the DEM integrity can be reliably verified even if only one sub-model was attacked, which has good potential in practice.","PeriodicalId":114335,"journal":{"name":"2022 10th International Symposium on Digital Forensics and Security (ISDFS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130976696","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}