Cloud based intruder detection system

Author(s):  
Chandan N Bhagwat ◽  
Y. Navaneeth Krishnan ◽  
K Badrinath
2018 ◽  
Vol 7 (2.4) ◽  
pp. 10
Author(s):  
V Mala ◽  
K Meena

Traditional signature based approach fails in detecting advanced malwares like stuxnet, flame, duqu etc. Signature based comparison and correlation are not up to the mark in detecting such attacks. Hence, there is crucial to detect these kinds of attacks as early as possible. In this research, a novel data mining based approach were applied to detect such attacks. The main innovation lies on Misuse signature detection systems based on supervised learning algorithm. In learning phase, labeled examples of network packets systems calls are (gave) provided, on or after which algorithm can learn about the attack which is fast and reliable to known. In order to detect advanced attacks, unsupervised learning methodologies were employed to detect the presence of zero day/ new attacks. The main objective is to review, different intruder detection methods. To study the role of Data Mining techniques used in intruder detection system. Hybrid –classification model is utilized to detect advanced attacks.


Author(s):  
K. Vijayaprabakaran ◽  
Priyanka Kodidela ◽  
Parinitha Gurram

The intruder detection system is targeted for the private areas, restricted areas and for the domestic home applications to notify the entrance of the intruder or any person to the specified areas. The intruder detection system eliminates the theft and entrance of the persons to the restricted areas by notifying the owner or the gardener through the registered application when the system detects an intruder in the locality. In this work an IoT based intruder detection system named Smart-IDS is proposed to avoid the entrance of the person without any special workforce for the target location. The proposed Smart-IDS detects the intruder using the Node MCU and Ultrasonic sensor and the cloud based Blynk application is employed to send the alert notification to the user. The experiments with the proposed Smart-IDS has performed more efficiently.


2021 ◽  
Author(s):  
Aniket Yadav ◽  
Nehal Thaker ◽  
Disha Makwana ◽  
Ninad Waingankar ◽  
Prashant Upadhyay

2018 ◽  
Vol 15 (11) ◽  
pp. 3565-3570 ◽  
Author(s):  
S Vimal ◽  
M Kaliappan ◽  
A Suresh ◽  
P Subbulakshmi ◽  
Sanjeev Kumar ◽  
...  

Author(s):  
Corneliu Rusu ◽  
Marius Vasile Ghiureau ◽  
Marius Sirbu ◽  
Radu Ciprian Bilcu ◽  
Jaakko Astola

2005 ◽  
Vol 51 (1) ◽  
pp. 130-138 ◽  
Author(s):  
Young-Keun Choi ◽  
Ki-Man Kim ◽  
Ji-Won Jung ◽  
Seung-Yong Chun ◽  
Kyu-Sik Park

Recent times there is an increase in thefts in the recent past. This creates a very bad environment for people to live in fear. The problem with home security in the modern world is a cause for concern. The conventional intruder detection system now we are using are highly expensive and there can be a possibility of false alarms. This problem is fixed by building a home intruder detection system that can accurately detect a human intruder, while filtering out movements that are caused due to any other moving objects using LabVIEW and Python. The images that were acquired and analyzed through frame comparisons are converted to gray scale images and then processed to detect an intruder. Here LabVIEW works as server and Python works as a client. At client video is acquired continuously, video is converted into images. Images are processed and information is send to the server. Server displays the status of the intruder with date and time. If the intruder is present then the system compares the intruder’s data with the data in the system. The images that were acquired and analyzed through frame comparisons converted to gray scale images that represent change, and then filtered through a series of image refining VI’s, helping to enhance our change detection results. If the data matches then the processing stops, if not then the system alerts the user through SMS or email if any intruder has been detected and sends the image to the user app. Through app we can make an alarm.


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