Dr. Yogesh Manohar Gajmal
@famt.ac.in
Associate Professor, Information Technology Departmnet
Finolex Academy of Management and Technology
RESEARCH INTERESTS
Blockchain, Information Security, Cloud Computing
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
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>
Udayakumar Dr.R., Anuradha Dr.M., Dr. Yogesh Manohar Gajmal, and Elankavi Dr.R.
SASA Publications
The mushrooming of IoTs (Internet of Things) and decentralised paradigm in cyber security have attracted a lot of interest from the government, academic, and business sectors in recent years. The use of MLT-assisted techniques in the IoT security arena has attracted a lot of attention in recent years. Many current studies presume that massive training data is readily accessible from IoT devices and transferable to main servers. However, since data is hosted on single servers, security and privacy concerns regarding this data also increase. It is suggested to use decentralised on-device data in OFDL (Optimal Federated Deep Learning) based anomaly detections to proactively identify infiltration in networks for IoTs. The GRUs (Gated Recurrent Units) used in OFDL's training rounds share only learned weights with the main OFDL servers, protecting data integrity on local devices. The model's training costs are reduced by the use of appropriate parameters, which also secures the edge or IoT device. In order to optimise the hyper-parameter environments for the limited OFDL environment, this paper suggests an MSSO (Modified Salp Swarm Optimisation) approach. Additionally, ensembles combine updates from multiple techniques to enhance accuracies. The experimental findings show that this strategy secures user data privacy better than traditional/centralized MLTs and offers the best accuracy rate for attack detection.
Udayakumar Dr.R., Dr. Suvarna Yogesh Pansambal, Dr. Yogesh Manohar Gajmal, Vimal Dr.V.R., and Sugumar Dr.R.
SASA Publications
Mobile and wireless networking infrastructures are facing unprecedented loads due to increasing apps and services on mobiles. Hence, 5G systems have been developed to maximise mobile user experiences as they can accommodate large volumes of traffics with extractions of fine-grained data while offering flexible network resource controls. Potential solutions for managing networks and their security using network traffic are based on UAA (User Activity Analysis). DLTs (Deep Learning Techniques) have been recently used in network traffic analysis for better performances. These previously suggested techniques for network traffic analysis typically need voluminous information on network usages. Hence, this work proposes OFedeMWOUAA (optimal federated learning-based UAA technique with Meadow Wolf Optimisation) and DNN (deep Neuron Networks) for minimizing risks of data leakages in MWNs (Mobile Wireless Networks). In the proposed OFedeMWOUAA, the need to submit data to cloud servers does not arise because it trains DLTs locally and only uploads model gradients or knowledge weights. The OFedeMWOUAA approach effectively decreases dangers to data privacies with very minor performance losses in simulations.
Yogesh M Gajmal and R. Udayakumar
Informa UK Limited
ABSTRACT The outsourcing of Electronic Health Records (EHR) on cloud infrastructures has enabled medical data sharing among several healthcare applications. The blockchain offers security by authenticating users with encryption methods. The collaboration with the cloud provides better management but poses threats to the privacy of the patient. This paper devises a novel blockchain-assisted framework for effective data sharing and retrieval using cloud platforms. Here, the data protection model is devised in EHR application for secure transmission. The entities in the cloud platform include data user, data owner, smart agreement, transactional blockchain, and Inter-Planetary File System (IPFS). Here, the data owner includes a data protection model to secure EHR in which secured EHR is transferred to IPFS before sharing with the data user. The data protection is done by preserving data privacy using Tracy-Singh product and proposed Conditional Autoregressive Value at risk (CAViaR)-based Bird swarm algorithm (CAViaR-based BSA) combination of BSA and CAViaR for generating optimal privacy-preserving coefficients. The objective function is newly devised considering privacy and utility. The proposed CAViaR-based BSA outperformed other methods with minimal responsiveness of 251.339 s, maximal genuine user detection of 32.451%, maximal privacy of 96.5%, and minimal information loss of 3.5%.
Yogesh M Gajmal and R. Udayakumar
River Publishers
Access control is a major factor in enhancing data security in the cloud storage system. However, the existing data sharing and the access control method have privacy data leakage and key abuse, which is a major challenge in the research community. Therefore, an effective method named Blockchain-based access control and data sharing approach is developed in the cloud storage system to increase data security. The proposed Blockchain-based access control and data sharing approach effectively solve single-point failure in the cloud system. It provides more benefits by increasing the throughput and reducing the cost. The Data user (DU) makes the registration request using the ID and password and forwards it to the Data Owner (DO), which processes the request and authenticates the Data user. The information of the data owner is embedded in the transactional blockchain using the encrypted master key. The Data owner achieves the data encryption process, and encrypted files are uploaded to the Interplanetary File System (IPFS). Based on the encrypted file location and encrypted key, the Data owner generates the ciphertext metadata and is embedded in the transactional blockchain. The proposed Blockchain-based access control and data sharing approach achieved better performance using the metrics, like a better genuine user detection rate of 95% and lower responsiveness of 25sec with the blockchain of 100 sizes.
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.
Anagha Markandey, Prajakta Dhamdhere, and Yogesh Gajmal
IEEE
Now a days, the big data is stored on the internet called as clouds. With usage of cloud storage users can store their data on the internet. Cloud computing provides various services to the users. Data storage is one of them. But it is observed that there is very big problem of data stealing through the internet. More is the problem of data leaking & attacks on the data on clouds. The intention of this paper is to attain data security of cloud storage and to put together equivalent cloud storage security strategy. These strategies are combined with the outcomes of existing data by considering the security risks & user data on cloud storage & move towards the appropriate security technique , which is based on properties of cloud storage system. The paper will go in to subtle elements of information assurance strategies and methodologies utilized all through the world to guarantee most extreme information insurance by diminishing dangers and dangers. Accessibility of information in the cloud is helpful for some applications yet it postures hazards by presenting information to applications which may as of now have security provisos in them. Also, utilization of virtualization for distributed computing may chance information when a visitor OS is keep running over a hypervisor without knowing the unwavering quality of the visitor OS which may have a security proviso in it. The paper will likewise give a knowledge on information security perspectives for Data-in-Transit and Data-at-Rest.
Yogesh Gajmal and K. P. Thooyamani
IEEE
Cloud computing is a technique for conveying Information Technology (IT) benefits in which assets stay recouped after the Internet over connected apparatuses plus appliance. Instead of keeping documents on a restrictive hard drive or nearby storage device, cloud-based capacity makes it conceivable to spare them to a remote database. For whatever length of time that an electronic device approaches the web, it approaches the data and the software programs to run it. Cloud computing opens up another universe of chances, however blended in with these opportunities are various information get to control security challenges that should be considered and tended to preceding focusing on a Cloud computing procedure. Cloud computing security challenges fall into three general classifications are Data Protection, User Authentication and Disaster and Data Breach. In this paper we examined different existing security solution accessible for access control mechanism like Key-Policy constructed Encoding, Characteristic constructed Encoding, Multi-specialist, and Individuality constructed Encoding.