The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Sustainable Computing-Based Simulation of Intelligent Border Surveillance Using Mobile WSN
|
|
Author(s): Rana Muhammad Amir Latif (Center for Modern Chinese City Studies, Institute of Urban Development, East China Normal University, Shanghai, China), Muhammad Farhan (Department of Computer Science, COMSATS University Islamabad, Sahiwal, Pakistan), Navid Ali Khan (Taylor's University, Malaysia)and R. Sujatha (School of Information Technology and Engineering, Vellore Institute of Technology, India)
Copyright: 2024
Pages: 33
Source title:
Navigating Cyber Threats and Cybersecurity in the Logistics Industry
Source Author(s)/Editor(s): Noor Zaman Jhanjhi (School of Computing Science, Taylor’s University, Malaysia)and Imdad Ali Shah (School of Computing Science, Taylor’s University, Malaysia)
DOI: 10.4018/979-8-3693-3816-2.ch003
Purchase
|
Abstract
This chapter has simulated and designed the intrusion detection and border surveillance system using mobile WSN technology. Due to increased terrorism globally, border protection has become a crucial issue in every country. Conventionally in border protection, a troop cannot provide security all over time. The authors have simulated the design of border protection by using mobile WSN technology on a CupCarbon simulator tool. They have analyzed the scenario of the smart city. So, a troop can be intimated with intrusions occurring on the border. They have created the authentication protocol for the better security of the application. The security protocol is necessary because the soldier's mobile device can be stolen during the war. It can be going into the hands of the enemy in the situation when troops expire. The Android app can guide the troop in the time of emergency and what the next step should be followed. The authors can check the status of the sensors deployed on the border. They have analyzed these applications based on the application's rating with machine learning techniques.
Related Content
|
Siva Raja Sindiramutty, Noor Zaman Jhanjhi, Chong Eng Tan, Navid Ali Khan, Bhavin Shah, Amaranadha Reddy Manchuri.
© 2024.
58 pages.
|
|
Imdad Ali Shah, Raja Kumar Murugesan, Samina Rajper.
© 2024.
31 pages.
|
|
Rana Muhammad Amir Latif, Muhammad Farhan, Navid Ali Khan, R. Sujatha.
© 2024.
33 pages.
|
|
Imdad Ali Shah, Areesha Sial, Sarfraz Nawaz Brohi.
© 2024.
25 pages.
|
|
Kassim Kalinaki, Wasswa Shafik, Sarah Namuwaya, Sumaya Namuwaya.
© 2024.
24 pages.
|
|
Imdad Ali Shah, N. Z. Jhanjhi, Humaira Ashraf.
© 2024.
24 pages.
|
|
Rida Zehra.
© 2024.
18 pages.
|
|
|