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Institution

Thapar University

EducationPatiāla, Punjab, India
About: Thapar University is a education organization based out in Patiāla, Punjab, India. It is known for research contribution in the topics: Cloud computing & Fuzzy logic. The organization has 2944 authors who have published 8558 publications receiving 130392 citations.


Papers
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Journal ArticleDOI
TL;DR: Investigation of the potential of using DWTS as sand replacement in Concrete Paving Blocks found the addition of DWTS could result in ettringite formation and the interfacial transition zone between the cement matrix and DWTS was more porous than that of sand.

52 citations

Book ChapterDOI
01 Jan 2019
TL;DR: Applications of IoT on agriculture and forestry has been studied and analyzed, and the technology IoT, agriculture IoT, list of some potential applications domains where IoT is applicable in the agriculture sector, benefits of IoT in agriculture, and a review of some literature are introduced.
Abstract: The Internet of Things is the hot point in the Internet field. The concepts help to interconnect physical objects equipped with sensing, actuating, computing power and thus lends them the capability to collaborate on a task in unison remaining connected to the Internet termed as the “Internet of things” IoT. With the help of sensor, actuators and embedded microcontrollers the notion of smart object is realized. Wherein these smart objects collect data from the environment of development, process them, and initiate suitable actions. Thus, the Internet of things will bring hitherto unimaginable benefits and helps humans in leading a smart and luxurious life. Because of the potential applications of IoT (Internet of Things), it has turned out to be a prominent subject of scientific research. The importance and the application of these technologies are in sizzling discussion and research, but on the field of agriculture and forestry, it is quite less. Thus, in this paper, applications of IoT on agriculture and forestry has been studied and analyzed, also this paper concisely introduced the technology IoT, agriculture IoT, list of some potential applications domains where IoT is applicable in the agriculture sector, benefits of IoT in agriculture, and presents a review of some literature.

52 citations

Book ChapterDOI
20 Apr 2018
TL;DR: Average class error and overall error have been calculated for the multi-classification problem and, on the basis of performance parameters, XGBoost performs efficiently and in robust manner to find an intrusion.
Abstract: In a fast-growing digital era, the increase in devices connected to internet have raised many security issues. For providing security, varieties of the system are available in the IT sector, Intrusion Detection system is one of such system. The design of an efficient intrusion detection system is an open problem to the research community. In this paper, various machine learning algorithms have been used for detecting different types of Denial-of-Service attack. The performance of the models have been measured on the basis of binary and multi-classification. Furthermore, parameter tuning algorithm has been discussed. On the basis of performance parameters, XGBoost performs efficiently and in robust manner to find an intrusion. The proposed method i.e. XGBoost has been compared with other classifiers like AdaBoost, Naive Bayes, Multi-layer perceptron (MLP) and K-Nearest Neighbour (KNN) on recently captured network traffic by Canadian Institute of Cybersecurity (CIC). In this research, average class error and overall error have been calculated for the multi-classification problem.

52 citations

Journal ArticleDOI
TL;DR: The product of unrestricted L - R flat fuzzy numbers is proposed and then with the help of proposed product, a new method (named as Mehar’s method) is proposed for solving fully FLP problems.

52 citations

Journal ArticleDOI
TL;DR: The experimental results demonstrated that the proposed system identifies the attacks proactively than other state-of-the-art approaches and generates signatures effectively thereby causing minimum damage due to network attacks.
Abstract: Automated signature generation for Intrusion Detection Systems (IDSs) for proactive security of networks is a promising area of research. An IDS monitors a system or activities of a network for detecting any policy violations or malicious actions and produces reports to the management system. Numerous solutions have been proposed by various researchers so far for intrusion detection in networks. However, the need to efficiently identifying any intrusion in the network is on the rise as the network attacks are increasing exponentially. This research work proposes a deep learning-based system for hybrid intrusion detection and signature generation of unknown web attacks referred as D-Sign. D-Sign is capable of successfully detecting and generating attack signatures with high accuracy, sensitivity and specificity. It has been for attack detection and signature generation of web-based attacks. D-Sign has reported significantly low False Positives and False Negatives. The experimental results demonstrated that the proposed system identifies the attacks proactively than other state-of-the-art approaches and generates signatures effectively thereby causing minimum damage due to network attacks.

52 citations


Authors

Showing all 3035 results

NameH-indexPapersCitations
Gaurav Sharma82124431482
Vinod Kumar7781526882
Neeraj Kumar7658718575
Ashish Sharma7590920460
Dinesh Kumar69133324342
Pawan Kumar6454715708
Harish Garg6131111491
Rafat Siddique5818311133
Surya Prakash Singh5573612989
Abhijit Mukherjee5537810196
Ajay Kumar5380912181
Soumen Basu452477888
Sudeep Tanwar432635402
Yosi Shacham-Diamand422876463
Rupinder Singh424587452
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202347
2022149
20211,237
20201,083
2019962
2018933