Cybersecurity Strategies for Safeguarding Customer’s Data and Preventing Financial Fraud in the United States Financial Sectors

Q3 Computer Science
Efijemue Oghenekome Paul, Obunadike Callistus, Olisah Somtobe, Taiwo Esther, Kizor-Akaraiwe Somto, Odooh Clement, Ifunanya Ejimofor
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引用次数: 2

Abstract

As the financial sectors in the United States deal with expanding cyberthreats and a rising danger of financial crime, cybersecurity has become a top priority. This paper examines the crucial cybersecurity techniques used by financial institutions to protect client information and counter the growing risk of financial fraud. It proves that understanding common fraud tactics used to defraud financial institutions and customers, putting fraud detection and prevention techniques like anomaly detection and machine learning into practice, and using transaction monitoring and anti-money laundering tactics to spot and stop fraudulent activity are all necessary for preventing financial fraud. The paper begins by reviewing the common cyber dangers affecting the financial industry and the strategies used by cybercriminals to circumvent security precautions and take advantage of weaknesses. After looking at potential risks, the paper highlights the importance of proactive cybersecurity measures and risk mitigation techniques. It highlights crucial components of cybersecurity frameworks, including strong data encryption, multifactor authentication, intrusion detection systems, and ongoing security monitoring. This paper also emphasizes the value of educating and training financial institution staff members to increase cybersecurity resilience. It underlines the significance of building a strong security culture, educating personnel about potential dangers, and encouraging responsible management of client data. The study also explores the advantages of financial organizations working together and exchanging threat knowledge. It examines industry alliances, information-sharing platforms, and public-private partnerships as crucial methods for group protection against cyber threats. This paper highlighted the significance of artificial intelligence and machine learning in cybersecurity domain. It demonstrates how these technologies improve cybersecurity systems' capabilities by spotting irregularities and potential attacks. It emphasizes the significance of taking a proactive and dynamic strategy to securing client information and maintaining faith in the United States’ financial sectors. Overall, this paper provides a thorough overview of cybersecurity tactics crucial for protecting consumer data and avoiding financial fraud in the financial sectors across the United States. By taking a vigilant, team-based, and technology-driven strategy, financial institutions may strengthen their cyber defenses, protect the data of their clients, and defend the integrity of the financial system.
美国金融部门保护客户数据和防止金融欺诈的网络安全策略
随着美国金融部门应对不断扩大的网络威胁和不断上升的金融犯罪危险,网络安全已成为重中之重。本文探讨了金融机构用于保护客户信息和应对日益增长的金融欺诈风险的关键网络安全技术。这证明,了解用于欺骗金融机构和客户的常见欺诈策略,将异常检测和机器学习等欺诈检测和预防技术应用于实践,以及使用交易监控和反洗钱策略来发现和阻止欺诈活动都是防止金融欺诈的必要条件。本文首先回顾了影响金融行业的常见网络危险,以及网络罪犯用来规避安全预防措施和利用弱点的策略。在研究了潜在风险之后,本文强调了主动网络安全措施和风险缓解技术的重要性。它强调了网络安全框架的关键组成部分,包括强大的数据加密、多因素认证、入侵检测系统和持续的安全监控。本文还强调了教育和培训金融机构工作人员以提高网络安全弹性的价值。它强调了建立强大的安全文化、教育人员了解潜在危险以及鼓励对客户数据进行负责任管理的重要性。该研究还探讨了金融机构合作和交换威胁知识的优势。它考察了行业联盟、信息共享平台和公私合作伙伴关系作为群体防御网络威胁的关键方法。本文强调了人工智能和机器学习在网络安全领域的重要意义。它展示了这些技术如何通过发现违规行为和潜在攻击来提高网络安全系统的能力。它强调了采取积极主动和动态的策略来保护客户信息和维护对美国金融部门的信心的重要性。总体而言,本文提供了对保护消费者数据和避免美国金融部门金融欺诈至关重要的网络安全策略的全面概述。通过采取警惕、以团队为基础和技术驱动的战略,金融机构可以加强其网络防御,保护客户数据,并捍卫金融系统的完整性。
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来源期刊
International Journal of Advances in Soft Computing and its Applications
International Journal of Advances in Soft Computing and its Applications Computer Science-Computer Science Applications
CiteScore
3.30
自引率
0.00%
发文量
31
期刊介绍: The aim of this journal is to provide a lively forum for the communication of original research papers and timely review articles on Advances in Soft Computing and Its Applications. IJASCA will publish only articles of the highest quality. Submissions will be evaluated on their originality and significance. IJASCA invites submissions in all areas of Soft Computing and Its Applications. The scope of the journal includes, but is not limited to: √ Soft Computing Fundamental and Optimization √ Soft Computing for Big Data Era √ GPU Computing for Machine Learning √ Soft Computing Modeling for Perception and Spiritual Intelligence √ Soft Computing and Agents Technology √ Soft Computing in Computer Graphics √ Soft Computing and Pattern Recognition √ Soft Computing in Biomimetic Pattern Recognition √ Data mining for Social Network Data √ Spatial Data Mining & Information Retrieval √ Intelligent Software Agent Systems and Architectures √ Advanced Soft Computing and Multi-Objective Evolutionary Computation √ Perception-Based Intelligent Decision Systems √ Spiritual-Based Intelligent Systems √ Soft Computing in Industry ApplicationsOther issues related to the Advances of Soft Computing in various applications.
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