Arvind Jagtap
@mituniversity.edu.in
Associate Professor
MIT Art Design and Technology University, Pune
EDUCATION
BE,ME, PHD
RESEARCH, TEACHING, or OTHER INTERESTS
Artificial Intelligence, Computer Networks and Communications, Computer Science Applications, Human-Computer Interaction
Scopus Publications
Scopus Publications
Yogesh M. Gajmal, Pranav More, Kiran Dhanaji Kale, and Arvind Jagtap
IEEE
New technologies based on cryptocurrencies and blockchain are revolutionizing how we conduct commercials online. Nowadays, a wide range of blockchain as well as cryptocurrency systems, apps, also technologies are publicly accessible in the direction of businesses, end users, as well as even malicious attackers that seek towards deploy cryptojacking malware to abuse the computational resources of common people. Without the victims' knowledge, this type of malware operates on their machines. In order to mine cryptocurrency for the cybercriminal, it frequently infects browsers and performs CPU-intensive computations. The cybercriminal then steals the revenues without compensating for the resources used. However, current detection techniques, for instance browser extensions that designed to defend users using blacklist protection or antivirus programmes by different analysis techniques, can only partially solve the problem of emerging cryptojacking because attackers can simply get around them via using obfuscation methods or else frequently altering their domains or else scripts. As a result, numerous researches in the literature suggested employing different dynamic/behavioral indicators to identify cryptojacking malware. However, a systematic study using a deep grasp of the new cryptojacking attack as well as a thorough assessment of studies into the literature is lacking in the literature. Therefore, using data from the web and journal articles, we give a systematic study of cryptojacking in this paper. Finally, we offer some prevention advice as well as warning signs that you might have been a victim of cryptojacking.
Yogesh Gajmal, Pranav More, Arvind Jagtap, and Kiran Kale
Frontier Scientific Publishing Pte Ltd
<p class="abstract">Access control is the most vital aspect of cloud data storage security. Traditional techniques for data distribution as well as access control face noteworthy challenges in the arena of research as a result of extensive abuse and privacy data breaches. The blockchain concept provides security by verifying users by multiple encryption technologies. Collaboration in the cloud improves management but compromises privacy. Consequently, we created an efficient access management and data exchange system for a blockchain-based decentralized cloud. On the basis of an ID and password, the data user (DU) submits a registering request to the data owner (DO). The DO data is incorporated into a transactional blockchain by an encoded master key. The data owner (DO) provides data encryption, and encrypted files are still published to the Interplanetary File System (IPFS). The DO generates ciphertext metadata, which is then published to the transactional blockchain utilizing a secure file location and a secure key. The projected access control and data sharing solution performed better in a decentralized blockchain based cloud, as measured by metrics such as a reduced illegitimate user rate of 5%, and a size blockchain of is 100 and 200, respectively.<strong><em></em></strong></p>
Nayar Cuitláhuac Gutiérrez Astudillo, Dinesh Bhagwan Hanchate, and Arvind M. Jagtap
Springer Nature Singapore
Parth Roy, Prateek Rao, Jay Gajre, Kanchan Katake, Arvind Jagtap, and Yogesh Gajmal
IEEE
A credit card which remains a very widespread compensation method is accepted online & offline that provides cashless transactions. It’s an easy, suitable then very common to make payments and other transactions. With the increase of developments credit card frauds are also growing. Financial deception is severely cumulative in the worldwide statement enhancement. Billion dollars are at loss due to these fraudulent acts. These actions are accomplished so gracefully that it is similar to genuine transactions. Therefore, simple design practices and other less composite methods will be non-operating. In directive to minimalize disorder and bring order in place having a well-organized method of fraud detection has become a need for all banks. In this paper we used Machine learning, to notice Master Card fake transactions. Also, IFA and OD approaches are applied towards enhance finest answer on behalf of scam finding problems. Approaches remain proved toward diminish untrue alarm proportions also upsurge scam discovery proportion. Dataset of card dealings stays obtained since European card owners having 284,807 communications. To detect and prevent the fraudulent, slightly of these approaches can be applied on bank credit card scam detection system, to detect and prevent the scam.
Arvind Madhukar Jagtap and Gomathi N.
IGI Global
In the past years, wireless sensor networks (WSNs) have increased successful real-world deployment in a wide range of civil and military applications. In order to ensure effective environmental sensing and robust communication, the two fundamental issues like TCOV and NCON are the very challenging tasks in WSN. As sensor nodes are battery-operated devices, the wide utilization of WSNs is obstructed by the severely limited energy constraints, this article tackles these kinds of issues by proposing an approach based on the energy model and aims at enhancing the network lifetime by improved balancing the movement and energy losses in the network. This article proposes a design which minimizes the power consumption and movement cost, thus enhancing the network lifetime. Finally, the authors compared the energy efficiency of the proposed approach with that of the existing approach. As such, the proposed AVABC improves the network lifetime by 14.29%, 26.09%, and 14.29% over VABC in response to the varying sensing radius of 5, 10, and 15, respectively.
Arvind Madhukar Jagtap, , N. Gomathi, and
Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP
In recent years, several applications are found to be exploiting under Wireless Sensor Networks (WSNs), and more particularly civil and military applications. However, Target Coverage (TCOV) and Network Connectivity (NCON) are found to be the most crucial issues that have to be resolved to attain effective robust data communication and environmental sensing in WSN. This paper has made an attempt to propose a new effective sensor deployment model in the application of the irrigation management system in agriculture sector. The data logger (data collector) IoT devices are typically placed over the field, which does the communication one another. The main point of this design is the IoT device TCOV and NCON, and the real-time issue related to this design is the device mobility that consumes more power thereby minimizes the lifetime of network. The proposed model intends to solve the comprised NCON and TCOV with the aid of Euclidean Spanning Tree Model (ECST). Further, this paper introduces a new Fitness Interrelated Whale Optimization Algorithm (FI-WOA) that insisted in the minimum movement of mobile sensors over the network. This novel characteristic of sensor deployment model would create the effectual impacts in the irrigation management system. Further, the adopted ECST-WOA model is compared with conventional models and the results attained from the execution demonstrate the enhanced performance of the implemented technique.
Arvind Madhukar Jagtap and N. Gomathi
Springer Science and Business Media LLC
A. M. Jagtap and N. Gomathi
Walter de Gruyter GmbH
Abstract This paper addresses the major challenges that reside on target coverage problem, which is one among the two primary sub-problems of node deployment problem. In order to accomplish a cost-efficient target coverage, a Voronoi partition-based, velocity added artificial bee colony algorithm (V-VABC) is introduced. The V-VABC is an advancement over the traditional, target-based Voronoi greedy algorithm (TVgreedy). Moreover, the VABC component of V-VABC is a hybrid, heuristic search algorithm developed from the context of ABC and particle swarm optimization (PSO). The V-VABC is an attempt to solve the network, which has an equal number of both sensors and targets, which is a special case of TCOV. Simulation results show that V-VABC performs better than TV-greedy and the classical and base algorithms of V-VABC such as ABC and PSO.