{"title":"Security Challenges in Data Collection and Processing in Industry 4.0 Implementation","authors":"N. Vamsi Krishna, Kowdodi Siva Prasad","doi":"10.46610/jodmm.2023.v08i03.001","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":43061,"journal":{"name":"International Journal of Data Mining Modelling and Management","volume":"42 1","pages":"0"},"PeriodicalIF":0.4000,"publicationDate":"2023-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Data Mining Modelling and Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.46610/jodmm.2023.v08i03.001","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
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.
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