TY - GEN
T1 - A Smart Approach using Multi-agent System for Big Data Security
AU - Kassimi, Dounya
AU - Kazar, Okba
AU - Barka, Ezedin
AU - Merizig, Abdelhak
AU - Houhamdi, Zina
AU - Athamena, Belkacem
AU - Zaoui, Meftah
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - With the evaluation of technology and the appearance of new tools that help store the information we create, especially in Banking, business intelligence, and even Education as Datawarehouse, Big data, and cloud computing. Those new tools create another obstacle: how we can secure and protect the information and the data stored in them. This paper treats the problem of Big Data security and privacy using mobile and stationary agents' technologies. The main important security proprieties in big data are integrity, authentication, privacy, and access control. For integrity, the problem lies in checking the integrity of data and if this data is good and can be used since the Big Data is receiving data from different sours and different formats (structured, semi-structured, and non-structured). In access control, we need to consider the users' secrecy, monitor the authorities, and properly apply the confidentiality requirement. The problem with authentication is to authenticate each user over the network, while big data collect sensitive data from trusted or untrusted users. While the privacy policy problem revolves around data collection and the use of transparency. To answer the previous needs for security in big data, we have proposed a smart approach using multi-agent systems (MAS) as a model for our solution.
AB - With the evaluation of technology and the appearance of new tools that help store the information we create, especially in Banking, business intelligence, and even Education as Datawarehouse, Big data, and cloud computing. Those new tools create another obstacle: how we can secure and protect the information and the data stored in them. This paper treats the problem of Big Data security and privacy using mobile and stationary agents' technologies. The main important security proprieties in big data are integrity, authentication, privacy, and access control. For integrity, the problem lies in checking the integrity of data and if this data is good and can be used since the Big Data is receiving data from different sours and different formats (structured, semi-structured, and non-structured). In access control, we need to consider the users' secrecy, monitor the authorities, and properly apply the confidentiality requirement. The problem with authentication is to authenticate each user over the network, while big data collect sensitive data from trusted or untrusted users. While the privacy policy problem revolves around data collection and the use of transparency. To answer the previous needs for security in big data, we have proposed a smart approach using multi-agent systems (MAS) as a model for our solution.
KW - Hadoop
KW - Pentaho
KW - big data
KW - mobile agent
KW - multi-agent system
KW - security and privacy
UR - http://www.scopus.com/inward/record.url?scp=85150682428&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85150682428&partnerID=8YFLogxK
U2 - 10.1109/IOTSMS58070.2022.10062015
DO - 10.1109/IOTSMS58070.2022.10062015
M3 - Conference contribution
AN - SCOPUS:85150682428
T3 - 2022 9th International Conference on Internet of Things, Systems, Management and Security, IOTSMS 2022
BT - 2022 9th International Conference on Internet of Things, Systems, Management and Security, IOTSMS 2022
A2 - Lloret Mauri, Jaime
A2 - Boubchir, Larbi
A2 - Jararweh, Yaser
A2 - Benkhelifa, Elhadj
A2 - Saleh, Imad
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 9th International Conference on Internet of Things, Systems, Management and Security, IOTSMS 2022
Y2 - 28 November 2022 through 1 December 2022
ER -