工业4.0实施中数据收集和处理的安全挑战

IF 0.4 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE International Journal of Data Mining Modelling and Management Pub Date : 2023-09-19 DOI:10.46610/jodmm.2023.v08i03.001
N. Vamsi Krishna, Kowdodi Siva Prasad
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引用次数: 0

摘要

物联网对工业4.0的实施至关重要。安全性是管理数据时需要考虑的一个重要因素。与此同时,物联网(IoT)是一种快速发展的技术范式,有望彻底改变人们与周围世界的互动方式。它包括将各种设备和传感器集成到日常物品中,使它们能够收集、交换和分析数据,以提高便利性和效率。物联网的应用范围广泛而多样,包括智能手表、智能手机、工业流程,甚至教育环境。物联网功能的核心是互联设备之间的信息无缝交换。然而,这种交换通常包括个人和敏感数据,使安全成为最重要的问题。保护这些数据对于防止潜在的安全威胁和破坏至关重要。本文深入探讨了物联网的多方面世界,探索了其在各个领域的应用,同时揭示了它所带来的安全挑战。它深入研究了可能危及物联网数据完整性和机密性的不同类型的安全威胁,例如未经授权的访问、数据泄露和设备操纵。此外,本文还提供了降低这些风险的策略和技术见解。它讨论了健壮的身份验证协议、加密机制和入侵检测系统对保护物联网生态系统的重要性。随着物联网的不断发展并与我们的日常生活交织在一起,解决安全问题对于充分利用其潜力,同时确保个人和组织的安全和隐私至关重要。
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Security Challenges in Data Collection and Processing in Industry 4.0 Implementation
IoT is crucial to the implementation of Industry 4.0. Security is an important factor to consider while managing data. At the same time, the Internet of Things (IoT) is a rapidly evolving technological paradigm that promises to revolutionize the way people interact with the world around us. It involves the integration of various devices and sensors into everyday objects, enabling them to collect, exchange, and analyze data to enhance convenience and efficiency. The applications of IoT are vast and diverse, encompassing smartwatches, smartphones, industrial processes, and even educational settings. Central to the functioning of IoT is the seamless exchange of information among interconnected devices. However, this exchange often includes personal and sensitive data, making security a paramount concern. Protecting this data is essential to prevent potential security threats and breaches. This paper delves into the multifaceted world of IoT, exploring its applications across various domains while shedding light on the security challenges it presents. It delves into different types of security threats that can compromise the integrity and confidentiality of IoT data, such as unauthorized access, data breaches, and device manipulation. Moreover, the paper also provides insights into strategies and technologies to mitigate these risks. It discusses the importance of robust authentication protocols, encryption mechanisms, and intrusion detection systems to safeguard IoT ecosystems. As the IoT continues to grow and intertwine with our daily lives, addressing security concerns is crucial to fully harness its potential while ensuring the safety and privacy of individuals and organizations alike.
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来源期刊
International Journal of Data Mining Modelling and Management
International Journal of Data Mining Modelling and Management COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
1.10
自引率
0.00%
发文量
22
期刊介绍: Facilitating transformation from data to information to knowledge is paramount for organisations. Companies are flooded with data and conflicting information, but with limited real usable knowledge. However, rarely should a process be looked at from limited angles or in parts. Isolated islands of data mining, modelling and management (DMMM) should be connected. IJDMMM highlightes integration of DMMM, statistics/machine learning/databases, each element of data chain management, types of information, algorithms in software; from data pre-processing to post-processing; between theory and applications. Topics covered include: -Artificial intelligence- Biomedical science- Business analytics/intelligence, process modelling- Computer science, database management systems- Data management, mining, modelling, warehousing- Engineering- Environmental science, environment (ecoinformatics)- Information systems/technology, telecommunications/networking- Management science, operations research, mathematics/statistics- Social sciences- Business/economics, (computational) finance- Healthcare, medicine, pharmaceuticals- (Computational) chemistry, biology (bioinformatics)- Sustainable mobility systems, intelligent transportation systems- National security
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