Dr. irfan Uddin - Academia.edu (original) (raw)

Papers by Dr. irfan Uddin

arXiv (Cornell University), Sep 21, 2013

Due to the limited computational resources of small unmanned aerial vehicles (UAVs), the Internet... more Due to the limited computational resources of small unmanned aerial vehicles (UAVs), the Internet of flying things (IoFT) is vulnerable to cybersecurity attacks, particularly Denial of Service (DoS) and Distributed Denial of Service (DDoS) attacks. In addition, the transfer of reliable information from source UAV to destination UAV is another big challenge in IoFT networks. Therefore, this article aims to address the security deficiency by proposing an experience-based deep learning algorithm to cater to the DoS, D-DoS and a special kind of threat covering ping-of-death attacks. The proposed scheme uses the notion of the intrusion detection system (IDS). In addition, for reliable communication, a nature-based control routing algorithm AntHocNet is investigated with other contemporary protocols. The proposed approach is implemented in a smart city environment as a case study. The result authenticates the superiority of the proposed schemes in terms of security and QoS requirement fro...

ArXiv, 2021

Race classification is a long-standing challenge in the field of face image analysis. The investi... more Race classification is a long-standing challenge in the field of face image analysis. The investigation of salient facial features is an important task to avoid processing all face parts. Face segmentation strongly benefits several face analysis tasks, including ethnicity and race classification. We propose a raceclassification algorithm using a prior face segmentation framework. A deep convolutional neural network (DCNN) was used to construct a face segmentation model. For training the DCNN, we label face images according to seven different classes, that is, nose, skin, hair, eyes, brows, back, and mouth. The DCNN model developed in the first phase was used to create segmentation results. The probabilistic classification method is used, and probability maps (PMs) are created for each semantic class. We investigated five salient facial features from among seven that help in race classification. Features are extracted from the PMs of five classes, and a new model is trained based on ...

Sustainability, 2021

Globally, as the environment deteriorates, use of renewable energy is increasing. The discrepancy... more Globally, as the environment deteriorates, use of renewable energy is increasing. The discrepancy between inequalities, sustainable sources, and natural resources, on the other hand, is enormous. As a consequence, the current research simulated the link between income inequality, renewable energy, and carbon emissions from 1990 to 2018. The long run and short run interaction were estimated using an autoregressive distribution lag (ARDL) model. According to the study’s findings, improvements in sustainable power, as well as income inequality, are producing a rise in environmental quality. Natural resources seem to have a significantly positive influence on the environment’s quality. Furthermore, the study found that financial development and environmental quality have a bidirectional causal link. According to the conclusions of this study, government authorities should support the use of renewable energy, i.e., sources to optimize carbon release.

Peer-to-Peer Networking and Applications, 2021

Peer-to-peer networking is a disseminated architecture application which partition the workload a... more Peer-to-peer networking is a disseminated architecture application which partition the workload among peers. The peers are distributed with equal privileges pertaining the equipotent application. The peers are making portion of their resources including disk storage, processing power, bandwidth, which is in a straight line available to the participants of the network deprived of central management by host. The decision support system in the design of peer-to-peer computing based on lightweight blockchain plays an important role for the smooth activities of the peer-to-peer computing. Early decision making in peer-to-peer computing for the lightweight blockchain can save time, cost, bandwidth, effort, and other resources. A flawless system is the dire need for enhancing the computation efficiency of the peer-to-peer computing. The aim of the proposed research is to offer a decision support system for the uses of lightweight blockchain design for peer-to-peer computing. The SuperDecisions tool was used to plot the hierarchy of situations of the uses of blockchain for the design of peer-to-peer computing. The system enhance the early decision making for the uses of lightweight blockchiarn for effective peer-to-peer computing. The results of the proposed study elaborates the significant use of lightweight blockchain against peer-to-peer computing.

Computers, Materials & Continua, 2021

IEEE Transactions on Industrial Informatics, 2021

In this article, unmanned aerial vehicles (UAVs) are expected to play a key role in improving the... more In this article, unmanned aerial vehicles (UAVs) are expected to play a key role in improving the safety and reliability of transportation systems, particularly where data traffic is nonhomogeneous and nonstationary. However, heterogeneous data sharing raises plenty of security and privacy concerns, which may keep UAVs out of future intelligent transportation systems (ITS). Some of the well-known security and privacy issues in the UAV-enabled ITS ecosystem include tracking UAVs and vehicle locations, unauthorized access to data, and message modification. Therefore, in this article, we contribute to the sum of knowledge by combining the hyperelliptic curve cryptography (HECC) techniques, digital signature, and hash function to present a privacy-preserving authentication scheme. The security features of the proposed scheme are assessed using formal security analysis methods, i.e., real-or- random (ROR) oracle model. To examine the performance of the proposed scheme, a comparison with other existing schemes has been carried out. The results reveal that the proposed scheme outperforms its counterpart schemes in terms of computation and communication costs.

Symmetry, 2020

Deep Learning algorithms are becoming common in solving different supervised and unsupervised lea... more Deep Learning algorithms are becoming common in solving different supervised and unsupervised learning problems. Different deep learning algorithms were developed in last decade to solve different learning problems in different domains such as computer vision, speech recognition, machine translation, etc. In the research field of computer vision, it is observed that deep learning has become overwhelmingly popular. In solving computer vision related problems, we first take a CNN (Convolutional Neural Network) which is trained from scratch or some times a pre-trained model is taken and further fine-tuned based on the dataset that is available. The problem of training the model from scratch on new datasets suffers from catastrophic forgetting. Which means that when a new dataset is used to train the model, it forgets the knowledge it has obtained from an existing dataset. In other words different datasets does not help the model to increase its knowledge. The problem with the pre-train...

Scientific Reports, 2020

Link prediction in a complex network is a problem of fundamental interest in network science and ... more Link prediction in a complex network is a problem of fundamental interest in network science and has attracted increasing attention in recent years. It aims to predict missing (or future) links between two entities in a complex system that are not already connected. Among existing methods, local similarity indices are most popular that take into account the information of common neighbours to estimate the likelihood of existence of a connection between two nodes. In this paper, we propose global and quasi-local extensions of some commonly used local similarity indices. We have performed extensive numerical simulations on publicly available datasets from diverse domains demonstrating that the proposed extensions not only give superior performance, when compared to their respective local indices, but also outperform some of the current, state-of-the-art, local and global link-prediction methods.

Physica A: Statistical Mechanics and its Applications, 2020

Research Journal of Pharmacy and Technology, 2019

Poloxamer-188 (P-188) is a polymer well renowned for possessing medical properties. Present study... more Poloxamer-188 (P-188) is a polymer well renowned for possessing medical properties. Present study was conducted with an aim to evaluate Hepato-protective potential of P-188 against paracetamol induced liver damage in wistar albino rats. Group-I served as Normal control which received normal saline 5ml/kg of Body weight (BW) for 7 days. Group-II served as Negative control in which animals received same dose as mentioned in Group-I. Group-III, IV and V animals received P-188(50mg/kg), P-188(100mg/kg) and silymarin (25mg/kg) respectively for 7 days. Except Group-I all other groups challenged with a very high dose of paracetamol (750 mg/kg) to induce hepatotoxicity. Biochemical estimation results showed that SGOT, SGPT and ALP levels were increased in negative control group animals which were decreased to normal levels when treated with P-188. There was highly significant (p<0.0001) decrease of these values in all three treatment groups. Moreover decrease in P-188 treated groups is dose dependent. Histopathological study supports the results of biochemical estimation. Negative control animal showed inflammation with mild cholestasis. P-188 (50mg/kg) showed mild inflammation, more number of normal hepatocytes, whereas P-188 (100 mg/kg) showed scattered lymphocytes among normal hepatocytes and kupffer cell hyperplasia, no incidence of inflammation and necrosis. Based on these results we can conclude that P-188 is a hepatoprotective polymer.

protocols.io, 2020

This algorithm implements Reversible Data Hiding (RDH) technique by rearranging the columns (or r... more This algorithm implements Reversible Data Hiding (RDH) technique by rearranging the columns (or rows) of the image in a way that enhances the smooth regions of an image. Any difference based technique to embed data can then be used in the transformed image.

International Journal of Engineering & Technology, 2018

Background and objective: A novel face parsing method is proposed in this paper which partition f... more Background and objective: A novel face parsing method is proposed in this paper which partition facial image into six semantic classes. Unlike previous approaches which segmented a facial image into three or four classes, we extended the class labels to six. Materials and Methods: A data-set of 464 images taken from FEI, MIT-CBCL, Pointing’04 and SiblingsDB databases was annotated. A discriminative model was trained by extracting features from squared patches. The built model was tested on two different semantic segmentation approaches – pixel-based and super-pixel-based semantic segmentation (PB_SS and SPB_SS).Results: A pixel labeling accuracy (PLA) of 94.68% and 90.35% was obtained with PB_SS and SPB_SS methods respectively on frontal images. Conclusions: A new method for face parts parsing was proposed which efficiently segmented a facial image into its constitute parts.

Human Systems Management, 2019

GSTF Journal on Computing (JoC), 2015

Computer architects are always interested in analyzing the complex interactions amongst the dynam... more Computer architects are always interested in analyzing the complex interactions amongst the dynamically allocated resources. Generally a detailed simulator with a cycle-accurate simulation of the execution time is used. However, the cycleaccurate simulator can execute at the rate of 100K instructions per second, divided over the number of simulated cores. This means that the evaluation of a complex application with complex concurrency interactions on contemporary multi-core machine can be very slow. To perform efficient design space exploration we present a co-simulation environment, where the detailed execution of concurrency instructions in the pipeline of microthreaded cores and the interactions amongst the hardware components are abstracted. We present the evaluation of the high-level simulation framework against the cycle-accurate simulation framework. The results show that high-level simulator is faster and less complicated than cycle-accurate simulator and has reasonable accu...

Open Journal of Modelling and Simulation, 2015

International Journal of High Performance Computing Applications, 2016

The microthreaded many-core architecture is comprised of multiple clusters of fine-grained multi-... more The microthreaded many-core architecture is comprised of multiple clusters of fine-grained multi-threaded cores. The management of concurrency is supported in the instruction set architecture of the cores and the computational work in application is asynchronously delegated to different clusters of cores, where the cluster is allocated dynamically. Computer architects are always interested in analyzing the complex interaction amongst the dynamically allocated resources. Generally a detailed simulation with a cycle-accurate simulation of the execution time is used. However, the cycle-accurate simulator for the microthreaded architecture executes at the rate of 100,000 instructions per second, divided over the number of simulated cores. This means that the evaluation of a complex application executing on a contemporary multi-core machine can be very slow. To perform efficient design space exploration we present a co-simulation environment, where the detailed execution of instructions ...

Proceedings of the 4th International Conference on Simulation and Modeling Methodologies, Technologies and Applications, 2014