scholarly journals Oil Well Detection System for Seismic Surveying Based on Internet of Things (IOT)

Author(s):  
Norsyazwani Mohd Puad ◽  
Maheyzah Md. Siraj ◽  
Nur Rafeeqkha Sulaiman
Author(s):  
NAGENDRA V. ◽  
RAKSHITHA G. ◽  
NAMBIAR K. T. SIDDHARTH ◽  
BURLE VYSHNAVI LAKSHMI ◽  
MANU D. K. ◽  
...  

2021 ◽  
Vol 21 (3) ◽  
pp. 1-22
Author(s):  
Celestine Iwendi ◽  
Saif Ur Rehman ◽  
Abdul Rehman Javed ◽  
Suleman Khan ◽  
Gautam Srivastava

In this digital age, human dependency on technology in various fields has been increasing tremendously. Torrential amounts of different electronic products are being manufactured daily for everyday use. With this advancement in the world of Internet technology, cybersecurity of software and hardware systems are now prerequisites for major business’ operations. Every technology on the market has multiple vulnerabilities that are exploited by hackers and cyber-criminals daily to manipulate data sometimes for malicious purposes. In any system, the Intrusion Detection System (IDS) is a fundamental component for ensuring the security of devices from digital attacks. Recognition of new developing digital threats is getting harder for existing IDS. Furthermore, advanced frameworks are required for IDS to function both efficiently and effectively. The commonly observed cyber-attacks in the business domain include minor attacks used for stealing private data. This article presents a deep learning methodology for detecting cyber-attacks on the Internet of Things using a Long Short Term Networks classifier. Our extensive experimental testing show an Accuracy of 99.09%, F1-score of 99.46%, and Recall of 99.51%, respectively. A detailed metric representing our results in tabular form was used to compare how our model was better than other state-of-the-art models in detecting cyber-attacks with proficiency.


2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Yulong Fu ◽  
Zheng Yan ◽  
Jin Cao ◽  
Ousmane Koné ◽  
Xuefei Cao

Internet of Things (IoT) transforms network communication to Machine-to-Machine (M2M) basis and provides open access and new services to citizens and companies. It extends the border of Internet and will be developed as one part of the future 5G networks. However, as the resources of IoT’s front devices are constrained, many security mechanisms are hard to be implemented to protect the IoT networks. Intrusion detection system (IDS) is an efficient technique that can be used to detect the attackers when cryptography is broken, and it can be used to enforce the security of IoT networks. In this article, we analyzed the intrusion detection requirements of IoT networks and then proposed a uniform intrusion detection method for the vast heterogeneous IoT networks based on an automata model. The proposed method can detect and report the possible IoT attacks with three types: jam-attack, false-attack, and reply-attack automatically. We also design an experiment to verify the proposed IDS method and examine the attack of RADIUS application.


2020 ◽  
pp. 35-44
Author(s):  
Satyam Tayal ◽  
Harsh Pallav Govind Rao ◽  
Suryansh Bhardwaj ◽  
Samyak Jain

Author(s):  
Meteb Altaf ◽  
Alaa Menshawi ◽  
Ruba Al-Skate ◽  
Taghreed Al-Musharraf ◽  
Wejdan Al-Sakaker

Author(s):  
Muhammad Ramdhan MS ◽  
Muhammad Ali ◽  
Paulson Eberechukwu N ◽  
Nurzal Effiyana G ◽  
Samura Ali ◽  
...  

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