Journal of Computer Information Systems最新文献_第6页

Social Networking Technologies in SMEs: A Bibliometric Analysis 中小企业的社会网络技术:文献计量分析

4区管理学

Journal of Computer Information Systems Pub Date : 2023-11-02 DOI: 10.1080/08874417.2023.2273811

Sandip Rakshit, Anand Jeyaraj, Tripti Paul, Sandeep Mondal

引用次数: 0

Information Security Practices and Intervention Among Teenagers 青少年资讯安全实践及干预

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Journal of Computer Information Systems Pub Date : 2023-10-26 DOI: 10.1080/08874417.2023.2270453

Satish Radhakrishnan, Lavanya Rajendran

{"title":"Information Security Practices and Intervention Among Teenagers","authors":"Satish Radhakrishnan, Lavanya Rajendran","doi":"10.1080/08874417.2023.2270453","DOIUrl":"https://doi.org/10.1080/08874417.2023.2270453","url":null,"abstract":"ABSTRACTIn the digital age, information is drastically exchanged among users. This data exchange paved the way for unsolicited access by cybercriminals, which could lead to psychological and financial loss. In this study, through a pre- and posttest experimental design, 668 Indian teenagers aged between fifteen and nineteen were evaluated last year. The preliminary study revealed low performance by teenagers in e-mail practices, password management, software practices, social media usage, and privacy settings. Through a novel intervention, 36 teenagers were observed through a curated information security module. The pretest and posttest analyses significantly supported the effects of security training, and Cohen’s d effect size reiterated the importance of progressive outcomes in their security literacy and practices. The intervention focused on the importance of threat perception and coping appraisal for inculcating security parameters and behavioral change among the teenagers.KEYWORDS: Information security awarenesssecurity practicesemail securitypassword securitysecurity training AcknowledgmentsWe would like to thank all the candidates who have participated in this research and spent time with us in spite of their busy commitments.Disclosure statementNo potential conflict of interest was reported by the author(s).","PeriodicalId":54855,"journal":{"name":"Journal of Computer Information Systems","volume":"493 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136376378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Recent Advancements in Machine Learning for Cybercrime Prediction 机器学习在网络犯罪预测中的最新进展

4区管理学

Journal of Computer Information Systems Pub Date : 2023-10-24 DOI: 10.1080/08874417.2023.2270457

Elluri, Lavanya, Mandalapu, Varun, Vyas, Piyush, Roy, Nirmalya

{"title":"Recent Advancements in Machine Learning for Cybercrime Prediction","authors":"Elluri, Lavanya, Mandalapu, Varun, Vyas, Piyush, Roy, Nirmalya","doi":"10.1080/08874417.2023.2270457","DOIUrl":"https://doi.org/10.1080/08874417.2023.2270457","url":null,"abstract":"ABSTRACTCybercrime is a growing threat to organizations and individuals worldwide, with criminals using sophisticated techniques to breach security systems and steal sensitive data. This paper aims to comprehensively survey the latest advancements in cybercrime prediction, highlighting the relevant research. For this purpose, we reviewed more than 150 research articles and discussed 50 most recent and appropriate ones. We start the review with some standard methods cybercriminals use and then focus on the latest machine and deep learning techniques, which detect anomalous behavior and identify potential threats. We also discuss transfer learning, which allows models trained on one dataset to be adapted for use on another dataset. We then focus on active and reinforcement learning as part of early-stage algorithmic research in cybercrime prediction. Finally, we discuss critical innovations, research gaps, and future research opportunities in Cybercrime prediction. This paper presents a holistic view of cutting-edge developments and publicly available datasets.KEYWORDS: Cybercrime predictionmachine learningcybersecurity AcknowledgmentsThe authors wish to acknowledge all those who contributed to the preparation and revision of the manuscript.Disclosure statementNo potential conflict of interest was reported by the author(s).","PeriodicalId":54855,"journal":{"name":"Journal of Computer Information Systems","volume":"44 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135220216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Spoofed Email Based Cyberattack Detection Using Machine Learning 基于欺骗电子邮件的机器学习网络攻击检测

4区管理学

Journal of Computer Information Systems Pub Date : 2023-10-20 DOI: 10.1080/08874417.2023.2270452

Sanjeev Shukla, Manoj Misra, Gaurav Varshney

{"title":"Spoofed Email Based Cyberattack Detection Using Machine Learning","authors":"Sanjeev Shukla, Manoj Misra, Gaurav Varshney","doi":"10.1080/08874417.2023.2270452","DOIUrl":"https://doi.org/10.1080/08874417.2023.2270452","url":null,"abstract":"ABSTRACTCyberattacks on e-mails are of different types, but the most pervasive and ubiquitous are spoofing attacks. Our approach uses memory forensics to extract e-mail headers from live memory to perform an e-mail header investigation to identify spoofing attacks. We have identified the research gaps and advanced our work to achieve better results. In this paper, we have made two significant improvements. First is URL validation module that uses a novel technique of checking each captured URL with an MX record and e-mail URL features. This scheme is fast, and reduces the total time from 35 sec to 27 sec. Second, spoofed e-mail detection is ameliorated by applying an ML model built using two novel e-mail header fields (BIMI and X-FraudScore) and four authentication header fields (SPF, DKIM, DMARC, and ARC). This enhances the spoofed e-mail detection accuracy from 96.15% to 97.57% with low false positives.KEYWORDS: Email spoofingemail attacksmemory forensicsemail forensicscyber-security Disclosure statementNo potential conflict of interest was reported by the author(s).Data availability statementThe datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request through email.","PeriodicalId":54855,"journal":{"name":"Journal of Computer Information Systems","volume":"6 12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135567535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Deep Temporal Graph Infomax for Imbalanced Insider Threat Detection 用于不平衡内部威胁检测的深度时间图信息集

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Journal of Computer Information Systems Pub Date : 2023-10-18 DOI: 10.1080/08874417.2023.2267510

Peng Gao, Haotian Zhang, Ming Wang, Weiyong Yang, Xinshen Wei, Zhuo Lv, Zengzhou Ma

{"title":"Deep Temporal Graph Infomax for Imbalanced Insider Threat Detection","authors":"Peng Gao, Haotian Zhang, Ming Wang, Weiyong Yang, Xinshen Wei, Zhuo Lv, Zengzhou Ma","doi":"10.1080/08874417.2023.2267510","DOIUrl":"https://doi.org/10.1080/08874417.2023.2267510","url":null,"abstract":"ABSTRACTInsider threats pose a significant concern for critical information infrastructures. Graph neural networks are widely used for detection due to their ability to model complex relationships among network entities. However, deep learning algorithms struggle with learning from business system data as anomalies are extremely rare. To tackle this challenge, we propose deep temporal graph infomax (DTGI), a new method for detecting insider threats in real-world scenarios with highly imbalanced data. DTGI utilizes an extended continuous-time dynamic heterogeneous graph network and a behavior context constraint anomaly sample generator. This generator incorporates attack behavior context constraints to augment attack samples and enhance the performance of the supervised model. Extensive experiments conducted on the CERT dataset, consisting of over one million records, demonstrate that DTGI surpasses state-of-the-art methods in terms of detection performance.KEYWORDS: Insider threatanomaly detectiondynamic graphgraph neural networkgraph contrastive learning Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work is supported by the State Grid Science and Technology Project [Project No.5108-202224046A-1-1-ZN].","PeriodicalId":54855,"journal":{"name":"Journal of Computer Information Systems","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135825277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Potential of Generative Artificial Intelligence Across Disciplines: Perspectives and Future Directions 跨学科生成人工智能的潜力:观点和未来方向

4区管理学

Journal of Computer Information Systems Pub Date : 2023-10-05 DOI: 10.1080/08874417.2023.2261010

Keng-Boon Ooi, Garry Wei-Han Tan, Mostafa Al-Emran, Mohammed A. Al-Sharafi, Alexandru Capatina, Amrita Chakraborty, Yogesh K. Dwivedi, Tzu-Ling Huang, Arpan Kumar Kar, Voon-Hsien Lee, Xiu-Ming Loh, Adrian Micu, Patrick Mikalef, Emmanuel Mogaji, Neeraj Pandey, Ramakrishnan Raman, Nripendra P. Rana, Prianka Sarker, Anshuman Sharma, Ching-I Teng, Samuel Fosso Wamba, Lai-Wan Wong

{"title":"The Potential of Generative Artificial Intelligence Across Disciplines: Perspectives and Future Directions","authors":"Keng-Boon Ooi, Garry Wei-Han Tan, Mostafa Al-Emran, Mohammed A. Al-Sharafi, Alexandru Capatina, Amrita Chakraborty, Yogesh K. Dwivedi, Tzu-Ling Huang, Arpan Kumar Kar, Voon-Hsien Lee, Xiu-Ming Loh, Adrian Micu, Patrick Mikalef, Emmanuel Mogaji, Neeraj Pandey, Ramakrishnan Raman, Nripendra P. Rana, Prianka Sarker, Anshuman Sharma, Ching-I Teng, Samuel Fosso Wamba, Lai-Wan Wong","doi":"10.1080/08874417.2023.2261010","DOIUrl":"https://doi.org/10.1080/08874417.2023.2261010","url":null,"abstract":"ABSTRACTIn a short span of time since its introduction, generative artificial intelligence (AI) has garnered much interest at both personal and organizational levels. This is because of its potential to cause drastic and widespread shifts in many aspects of life that are comparable to those of the Internet and smartphones. More specifically, generative AI utilizes machine learning, neural networks, and other techniques to generate new content (e.g. text, images, music) by analyzing patterns and information from the training data. This has enabled generative AI to have a wide range of applications, from creating personalized content to improving business operations. Despite its many benefits, there are also significant concerns about the negative implications of generative AI. In view of this, the current article brings together experts in a variety of fields to expound and provide multi-disciplinary insights on the opportunities, challenges, and research agendas of generative AI in specific industries (i.e. marketing, healthcare, human resource, education, banking, retailing, the workplace, manufacturing, and sustainable IT management).KEYWORDS: Generative artificial intelligencemachine learninglarge language modelChatGPTBard Disclosure statementNo potential conflict of interest was reported by the author(s).","PeriodicalId":54855,"journal":{"name":"Journal of Computer Information Systems","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134947432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Legal and Privacy Concerns of BYOD Adoption BYOD采用的法律和隐私问题

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Journal of Computer Information Systems Pub Date : 2023-10-02 DOI: 10.1080/08874417.2023.2259346

Kenan Degirmenci, Michael H. Breitner, Ferry Nolte, Jens Passlick

引用次数: 0

Post-Quantum Cryptography Research Landscape: A Scientometric Perspective 后量子密码学研究前景:科学计量学视角

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Journal of Computer Information Systems Pub Date : 2023-09-29 DOI: 10.1080/08874417.2023.2260333

Priya Sharma, Vrinda Gupta, Sandeep Kumar Sood

{"title":"Post-Quantum Cryptography Research Landscape: A Scientometric Perspective","authors":"Priya Sharma, Vrinda Gupta, Sandeep Kumar Sood","doi":"10.1080/08874417.2023.2260333","DOIUrl":"https://doi.org/10.1080/08874417.2023.2260333","url":null,"abstract":"ABSTRACTPost-quantum cryptography (PQC) is under development to guard against the threats of quantum computers by implementing a new class of cryptosystems. In this direction, much work has been done since 2006, which has led to many publications. Hence, this study presents an overview of PQC research through scientometric analysis of the data containing 1611 publications published from 2006 to 2023, retrieved from the Scopus database. The analysis identifies growth, trends, leading countries, and significant publications, providing insights into impactful PQC research. It also demonstrates a significant rise in publications after 2015, and the United States is a highly productive country. Furthermore, this study also discusses the managerial view, which can assist technology managers in understanding its impact on global and local markets. The findings of this analysis can be a valuable resource for researchers, policymakers, and stakeholders interested in the future of cryptography and other potential impacts of quantum computing.KEYWORDS: Post-quantum cryptography (PQC)scientometricVOSviewerpublication trendsmanagerial perspective Disclosure statementNo potential conflict of interest was reported by the author(s).Data availability statementThe data supporting the findings presented in this article is downloadable from Scopus database or can be made available by the corresponding author upon reasonable request.Notesa These classifications of economic status are done according to statistics prepared by the Economy Analysis and Policy Division (EAPD) of the Department of Economy and Social Affairs of the United Nations Secretariat. For more, readers are requested to refer toCitation50","PeriodicalId":54855,"journal":{"name":"Journal of Computer Information Systems","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135193537","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

IoT and Blockchain: A Review and a Technical-Legal-Social Acceptance Model 物联网和区块链:回顾和技术-法律-社会接受模型

4区管理学

Journal of Computer Information Systems Pub Date : 2023-09-29 DOI: 10.1080/08874417.2023.2259334

Katia Guerra, Chang Koh, Victor Prybutok, Vess Johnson

{"title":"IoT and Blockchain: A Review and a Technical-Legal-Social Acceptance Model","authors":"Katia Guerra, Chang Koh, Victor Prybutok, Vess Johnson","doi":"10.1080/08874417.2023.2259334","DOIUrl":"https://doi.org/10.1080/08874417.2023.2259334","url":null,"abstract":"ABSTRACTInternet of Things (IoT) and blockchain are complex digital technologies characterized by a strong connection and dependency between individuals, data, and information technology (IT). A socio-technical perspective that captures the dynamic interaction of social, legal, and technical artifacts is essential to understanding the IoT and blockchain phenomena. This review provides direction for employing a social-technical perspective across IoT and blockchain studies. The findings lead to new insights for developing a theoretical framework, research model, and research agenda to investigate IoT and blockchain technology. Practitioners and institutions can use these findings to develop strategies to promote the adoption of IoT and blockchain technologies through specific technical, legal, and social strategies. Overall, this research is unique in its attempt to trace new trajectories for future IS scholars and practitioners facing the complexity of IoT and blockchain.KEYWORDS: Internet of thingsblockchainsocio-technical paradigmsocial, legal, and technical factors Disclosure statementNo potential conflict of interest was reported by the author(s).","PeriodicalId":54855,"journal":{"name":"Journal of Computer Information Systems","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135193680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Job Performance in Digital Work: Do Personality Traits Matter? 数字化工作中的工作表现:人格特质重要吗?

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Journal of Computer Information Systems Pub Date : 2023-09-27 DOI: 10.1080/08874417.2023.2255551

Sophia Xiaoxia Duan, Hepu Deng

引用次数: 0