Papers by Vijaypal Rathor
Color Crop Image Compression Technique using Singular Vector Sparse Reconstruction
GateLock: Input-Dependent Key-Based Locked Gates for SAT Resistant Logic Locking
Performance of Interpolation Techniques for Compression of Crop Image: A Comparative Study
2023 International Conference on Computer, Electronics & Electrical Engineering & their Applications (IC2E3)
Hyperspectral image classification using multiobjective optimization
Multimedia Tools and Applications, Mar 23, 2022
Hybrid technique for crop image compression using discrete wavelet transform and sparse singular vector reconstruction
Computers and Electronics in Agriculture
A New ATPG and Online Monitoring based Technique for Hardware Trojan Detection
Microprocessors and Microsystems
Multi-Objective Optimization Based Test Pattern Generation for Hardware Trojan Detection
Journal of Electronic Testing
Intelligent Analytics for Industry 4.0 Applications
Intelligent Analytics for Industry 4.0 Applications
Cooperative Geometric Scheme for Passive Localization of Target in an Indoor Environment
2022 IEEE Symposium Series on Computational Intelligence (SSCI)
Survey on Load Balancing through Virtual Machine Scheduling in cloud computing Environment
In the cloud environment number of user can request for the services simultaneously. So there sho... more In the cloud environment number of user can request for the services simultaneously. So there should be a mechanism that efficiently allocates the resources to the user, but resources in the cloud environment are highly dynamic and heterogeneous in nature. Because of this nature it is very difficult to fully utilize the resources with the proper resource balancing. In order to improving the system performance, resources must be properly assigned with minimum overhead time and load must be equally distributed on the physical machines. Proper VM scheduling can also reduce the number of migration that will increase the overall performance of the system. Numbers of VM scheduling methods have been proposed. This paper includes some exiting VM scheduling methodologies with their anomalies.
Hyperspectral Image Classification Using Multiple Kernel Learning SVM with FA-KLD-LFDA for Multi Feature Selection
International Review on Computers and Software (IRECOS), 2014
ABSTRACT
International Journal of Machine Learning and Cybernetics
Completely Automated Public Turing Test To Tell Computer and Humans Apart (CAPTCHA) is a computer... more Completely Automated Public Turing Test To Tell Computer and Humans Apart (CAPTCHA) is a computer program that prevents malicious computer users. Text-CAPTCHA schemes utilize less-computational costs. Hence, they are the most popularly used. This paper investigates the effectiveness of state-of-the-art (SOTA) text-CAPTCHA schemes, proposes a Multiview deep learning system to break them, and highlights their weaknesses. Rather than the usual single-view feature extraction, the proposed model explores correlational features from multiple views to increase the model's generalization and classification accuracy. The model combines convolutional neural networks and recurrent networks to preserve the input text-CAPTCHA's spatial and sequential order. The proposed system has successfully achieved average accuracies ranging from 93.6% to 100%, and the average time to break a text-CAPTCHA scheme ranges from 0.0032 to 0.21 seconds on eight different datasets. Furthermore, an ablation study on 71 human users was conducted to evaluate the effectiveness of the schemes. The results demonstrated that the proposed system effectively outperforms the human users whom the schemes were designed to serve. Lastly, when compared with existing systems, the proposed system outperforms existing SOTA systems with an accuracy gap of almost 40% higher.
Tolerance Satisfiability Sequences for Image Similarity
2020 2nd International Conference on Advances in Computing, Communication Control and Networking (ICACCCN)
We propose a solution to a fundamental problem of content based image retrieval (CBIR), "How... more We propose a solution to a fundamental problem of content based image retrieval (CBIR), "How to calculate the degree of similarity among a pair of images". This article introduces a novel technique called Tolerance Satisfiablity Sequence (TSS) which is based on the concept of tolerance space and near set theory. In this work, images are divided into different visual element (objects) and affinity is calculated between the corresponding object of the two images. Each object is further divided into sub-objects that are mapped to each other under the constraints of tolerance satisfiability. The maximal satisfying set of sub objects (between the two parent objects) is found. This maximal set of sub-object is (termed as TSS) compared with the parent object i.e. the ratio of the cardinality of maximum satisfying set to the cardinality of the parent object is calculated and this gives the quantified similarity index termed as Tolerant Satisfiable Similarity Metric (TSSM). Initially, we verified that proposed approach is metric as well as pseudo-metric and later it is compared with popular image nearness metrics, viz., Hausdorff and Structural Similarity Index (SSIM). It is experimentally proved that the TSSM outperformed them in visual acuity.
Security analysis of image CAPTCHA using a mask R-CNN-based attack model
International Journal of Ad Hoc and Ubiquitous Computing
A new hardware Trojan detection technique using deep convolutional neural network
The involvement of external vendors in semiconductor industries increases the chance of hardware ... more The involvement of external vendors in semiconductor industries increases the chance of hardware Trojan (HT) insertion in different phases of the integrated circuit (IC) design. Recently, several partial reverse engineering (RE) based HT detection techniques are reported, which attempt to reduce the time and complexity involved in the full RE process by applying machine learning or image processing techniques in IC images. However, these techniques fail to extract the relevant image features, not robust to image variations, complicated, less generalizable, and possess a low detection rate. Therefore, to overcome the above limitations, this paper proposes a new partial RE based HT detection technique that detects Trojans from IC layout images using Deep Convolutional Neural Network (DCNN). The proposed DCNN model consists of stacking several convolutional and pooling layers. It layer-wise extracts and selects the most relevant and robust features automatically from the IC images and ...
Journal of Ambient Intelligence and Humanized Computing, 2021
This paper presents a novel significance driven inverse distance weighted (SDIDW) filter for the ... more This paper presents a novel significance driven inverse distance weighted (SDIDW) filter for the impulsive noise removal in the X-ray images. The proposed SDIDW filter restores the noisy pixel using minimum number of nearest noise-free pixels to achieve good estimation while exhibiting low computational complexity. In the proposed filter, higher priority (weight) is given to nearest pixels compared to distant pixels and only sufficient nearest noise free pixels are determined to estimate the value of noisy pixel. A high level analysis of the computation complexity at varying noise density is done which shows that proposed SDIDW filter provides significant reduction in computation complexity over the adaptive median filters. Finally, the performance of the proposed filter is evaluated and compared over the state-of-the-art impulse noise removal techniques for varying noise density (wide range 10–90% and very high noise density range 91–99%). The experimental results on medical images...
New lightweight Anti-SAT block design and obfuscation technique to thwart removal attack
Integration
A Lightweight Robust Logic Locking Technique to Thwart Sensitization and Cone Based Attacks
IEEE Transactions on Emerging Topics in Computing
New Lightweight Architectures for Secure FSM Design to Thwart Fault Injection and Trojan Attacks
Journal of Electronic Testing
A Novel Low Complexity Logic Encryption Technique for Design-for-Trust
IEEE Transactions on Emerging Topics in Computing
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Papers by Vijaypal Rathor