Smart City Gnosys
Smart city article details
| Title | Novel Ai-Dependent Intrusion Detection System For Iot-Enabled Smart City Applications |
|---|---|
| ID_Doc | 39439 |
| Authors | Nalini M.; Priyadharshini R.S.; Keerthana C.V.; Bharathi N.P.D. |
| Year | 2024 |
| Published | Lecture Notes in Networks and Systems, 972 |
| DOI | http://dx.doi.org/10.1007/978-981-97-3466-5_25 |
| Abstract | The advancement of “SMART CITIES” is a result of the need to satisfy social and physical goals while improving the quality of life. The intention of smart cities is to effectively regulate rising urbanization, energy consumption, environmental preservation, citizens' successful standards, and increase the potential of the populace to effectively use and embrace contemporary knowledge and communication technologies (ICT). These are brought about by developments in information technology that, although they open up new economic and social possibilities, also put our security and privacy expectations in jeopardy. With the help of technology like smartphones, people are already linked. In many cities, smart appliances, security systems, and energy meters are in use. The quick development of technology not only makes life simpler but also raises several security concerns. The amount of online assaults has risen as the Internet has developed over the years. One of the supporting layers that may be used for information security is the intrusion detection system (IDS). The fast development of technology not only makes life simpler but also raises several security concerns. The amount of online assaults has risen as the Internet has developed over the years. One of the supporting layers that may be used for information security is the intrusion detection system (IDS). This system is used to protect our IoT-enabled smart city environment from suspicious activities. This work was developed using the NSL-KDD data and its competence was collected and compared using machine learning algorithms. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. |
| Author Keywords | Artificial intelligence; Classification; Intrusion detection system; Logistic regression; Machine learning algorithms; Smart cities; Suspicious activity detection |
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