Om Vyas

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Prof. Om Prakash Vyas currently works as Dean (Technology Development) and Professor (IT) at Govt. of India's IIIT Allahabad.

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Papers by Om Vyas

Providing Sensor Services by Data Correlation: The #SmartME Approach

In the current era Internet is the most used medium for sharing and retrieving the information fo... more In the current era Internet is the most used medium for sharing and retrieving the information for building applications which are commonly developed for enhancing the user experience in terms of comfort, communication. For this, the need of real-time sensor data gains importance. The data collected from the physical objects should be easily available for different applications. Semantic representation of the sensor data directly addresses the problem of storing it in logical, easily accessible and extensible manner. Our paper works towards converting the already collected sensor data of the #SmartME project into semantic format and also proposes real-time storage of semantically enriched sensor data. To build applications using these sensor data the authors consider mainly three kinds of sensors, i.e., Temperature, Humidity, Pressure. Predicting the observed value of any sensor data is the main aim of this work. The analysis leverages other sensors & environmental parameters such a...

Design of a Trustless Smart City system: The #SmartME experiment

Internet of Things, 2019

A Smart City is an example of a domain where citizens and institutions, at any level, should be e... more A Smart City is an example of a domain where citizens and institutions, at any level, should be empowered to cooperate for the greater good of the respective communities, and one of the most powerful ways to attain that is by actually decentralizing any process that can escape single-authority control and the grip of centrally-managed bureaucracies, whilst at the same time not relying on any single party trusting any other. In line with this key insight, in this paper we have designed and implemented a decentralized, trustless DLT-based system for (environmental) sensing, data acquisition, storage, and consumption, in the context of a real-world Smart City deployment, #SmartME, and with the participation of independent, institutional, stakeholders. This Open Data system has been devised to be user-friendly, with an end-user wizard for trustless (i.e., independent) data audit. Indeed, the data collection layer does not trust any IoT node by default, but requires nodes to authenticate themselves when sending readings. Last but not least, the storage layer is again trustless, as institutions can pool together their resources, without trusting one another, nor entrusting the administration of the system to any third party. In this work we extend our preliminary proof-of-concept design, and explore the expected outcomes of scaling the system to comprise an even greater number of active institutions participating in the validation process, by carrying out simulation experiments. Results from these experiments help us in validating our approach and assessing its scalability.

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Security and Authentication Issues in Emerging Network Architectures with Special Reference to SONATE

2011 International Conference on Computational Intelligence and Communication Networks, 2011

The emerging research to develop new architecture for next generation networks have made us think... more The emerging research to develop new architecture for next generation networks have made us think about the security incorporates &quot;inside&quot; the network architecture during the evolution phase. The aim is to provide better services to the user in a secured fashion. In this paper we describe three different security level approaches namely Micro level security, Medium level security and Macro

Exploration of Soft Computing Approaches in Itemset Mining

Risk Management and Decision-Making

Data Mining is largely known to extract knowledge from large databases in an attempt to discover ... more Data Mining is largely known to extract knowledge from large databases in an attempt to discover existing trends and newer patterns. While data mining refers to information extraction, soft computing is more inclined to information processing. Using Soft Computing, the tolerance for imprecision, uncertainty, approximate reasoning, and partial truth for achieving tractability, robustness, and low-cost solutions can be revealed. For effective knowledge discovery from large databases, both Soft Computing and Data Mining can be merged. Soft computing techniques are Fuzzy Logic (FL), Neural Network (NN), Genetic Algorithm (GA), Rough Set (RS), etc. For handling different types of uncertainty in huge data, FL and RS are highly suitable. NNs are a nonparametric, robust technique and provide good learning and generalization capabilities in data-rich environments. GAs provide efficient search algorithms for selecting a model, from mixed-media data, based on some priority criterion. In one of...

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Towards a Scalable Approach for Mining Frequent Patterns from the Linked Open Data Cloud

Smart Innovation, Systems and Technologies, 2014

In recent years, the linked data principles have become one of the prominent ways to interlink an... more In recent years, the linked data principles have become one of the prominent ways to interlink and publish datasets on the web creating the web space a big data store. With the data published in RDF form and available as open data on the web opens up a new dimension to discover knowledge from the heterogeneous sources. The major problem with the linked open data is the heterogeneity and the massive volume along with the preprocessing requirements for its consumption. The massive volume also constraint the high memory dependencies of the data structures required for methods in the mining process in addition to the mining process overheads. This paper proposes to extract and store the RDF dumps available for the source data from the linked open data cloud which can be further retrieved and put in a format for mining and then suggests the applicability of an efficient method to generate frequent patterns from these huge volumes of data without any constraint of the memory requirement.

Path Stability Based Adaptation of MANET Routing Protocols

Lecture Notes in Computer Science, 2004

This paper proposes adaptation of Mobile Ad-hoc Network (MANET) [13] routing protocols taking sta... more This paper proposes adaptation of Mobile Ad-hoc Network (MANET) [13] routing protocols taking stability of links as primary consideration. The presented scheme can be associated with a resource reservation strategy to ensure Quality Of Service (QoS). Packets routed through stable routes have very low waiting time in queue which reduces end to end delay. The overall performance shows that the

Design and Implementation Issues of Flexible Network Architecture

2011 International Conference on Computational Intelligence and Communication Networks, 2011

ABSTRACT Present Internet protocol was developed long way back with the intention to provide simp... more ABSTRACT Present Internet protocol was developed long way back with the intention to provide simple end-to-end network functionalities for network applications of 1980&#39;s. Since then many times network and its related applications were reformed over technological advancement. To support new applications more and more protocols were created as patches which resulted in IP bloat. As a result of this Internet community researcher worries about upcoming days of failure of current Internet. This paper emphasis on design and implementation issues of flexible network using with Service Oriented Architecture methodology. And also highlights a framework for Flexible Network Architecture which is one of the way to address current as well as future network application problem.

Mining Retail E-Commerce: Lessons from Path Breaking Case Studies

adit.ac.in, 2005

Abstract-The e-commerce domain can provide all the right ingredients for successful data mining a... more

Broker's Communication for Service Oriented Network Architecture

The diversity, heterogeneity and innovation in network application domain prompted a new era of I... more The diversity, heterogeneity and innovation in network application domain prompted a new era of Internet. Many technologies such as ATM, Frame Relay, X.25, etc., were developed to provide alternative for communication in networked systems, but could not succeed to get evolved as one of the alternate / replacement technology for the Internet. The Internet adopted a method of patchwork approach to cope with the needs of evolution and revolution of technology growth with acceptable cost and speed. The Internet is not designed for any specific application purposes; rather it is for generic and evolves purposes. The Future Network is expected to hosts much more than today's applications in an efficient manner, but researcher predicted rigidity as one of the failure factors for Current Internet (CI). In this paper the authors’ emphasis on the development of the improved Future Network using with broker's communication which works based on SOA while accounting and addressing the issues of CI failure factors.

Simulation Study of QoS Mechanism in ATM Networks

A Stance on Challenges with Current Internet and Approaches for Future Internet

The expansion of the Internet, worldwide network of interconnected computer networks based on the... more The expansion of the Internet, worldwide network of interconnected computer networks based on the TCP/IP standard communication protocol, was driven over last 30 years by the exchange of data between hosts such as server platforms and Personal Computers (PCs). Today, the Internet has become essential for enabling data information flow exchanges all over the world enabling in turn a wide range of applications and services. The aim of this contribution to explore the challenges currently faced by Internet community, trying to identify the root of problem and finally presents the directions where Internet can move.

An ontology-based adaptive personalized e-learning system, assisted by software agents on cloud storage

Knowledge-Based Systems, 2015

E-Learning and online education have made great strides in the recent past. It has moved from a k... more E-Learning and online education have made great strides in the recent past. It has moved from a knowledge transfer model to a highly intellect, swift and interactive proposition capable of advanced decision-making abilities. Two challenges have been observed during the exploration of recent developments in e-learning. Firstly, to incorporate e-learning systems effectively in the evolving semantic web environment and secondly, to realize adaptive personalization according to the learner's changing behaviour. An ontology-driven system has proposed to implement the Felder-Silverman learning style model in addition to the learning contents, to validate its integration with the semantic web environment. Software agents are employed to monitor the learner's actual learning style and modify them accordingly. The learner's learning style and their modifications are made within the proposed e-learning system. Cloud storage is used as the primary back-end in order to maintain the ontology, databases and other required server resources. To verify the system, comparisons are made between the information presented and adaptive learning styles of the learner along with actions of agents according to learners' behaviour. Finally, various conclusions are drawn by exploring the learner's behavior in an adaptive environment for the proposed e-learning system.

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Augmented intuitive dissimilarity metric for clustering of Web user sessions

Journal of Information Science, 2016

Clustering is a very useful technique to categorise Web users with common browsing activities, ac... more Clustering is a very useful technique to categorise Web users with common browsing activities, access patterns and navigational behaviour. Web user clustering is used to build Web visitor profiles that make the core of a personalised information recommender system. These systems are used to comprehend Web users surfing activities by offering tailored content to Web users with similar interests. The principle objective of Web user sessions clustering is to maximise the intra-group while minimising the inter-group similarity. Efficient clustering of Web users’ sessions not only depend on the clustering algorithm’s nature but also depend on how well user concerns are captured and accommodated by the dissimilarity measure that are used. Determining the right dissimilarity measure to capture the access behaviour of the Web user is very significant for substantial clustering. In this paper, an intuitive dissimilarity measure is presented to estimate a Web user’s concern from augmented Web...

A Discounted Fuzzy Relational Clustering of Web Users’ Using Intuitive Augmented Sessions Dissimilarity Metric

IEEE Access, 2016

Relational fuzzy clustering (RFC) algorithms prove very useful in Web user session clustering bec... more Relational fuzzy clustering (RFC) algorithms prove very useful in Web user session clustering because Web user sessions may contain fuzzy, conflicting and imprecise information. Though RFC algorithms are very sensitive to cluster initialization and works only if the numbers of clusters are specified in advance. However, at all times, the prior initialization of a number of clusters is not feasible due to the dynamically evolving nature of user sessions. Therefore, estimating the number of clusters and initializing suitable cluster prototype are a significant performance bottleneck in this method. In this paper, the discounted fuzzy relational clustering (DFRC) algorithm is proposed to address the major constraint of RFC. The DFRC algorithm identifies Web user session clusters from Web server access logs, without initializing the number of clusters and prototypes of initial clusters. The DFRC algorithm works in two stages. In the first stage, DFRC automatically identifies the number of potential clusters based on the successively discounted potential density function value of each relational data and their respective centres. In the second stage, DFRC assigns fuzzy membership values to each data point and forms fuzzy clusters from the relational matrix. The DFRC algorithm is applied on an augmented session dissimilarity matrix obtained from a publicly accessed NASA Web server log data. The experimental results are evaluated using different fuzzy validity measures. The extensive experiments are performed to test the effect of various parameters, including accept/reject ratio and neighbourhood radius on the performance of DFRC algorithm. The results were also compared with fuzzy relational clustering algorithm using cluster quality measures. It is observed that the quality of generated clusters using DFRC is superior as compared with that of RFC.

Quantitative Evaluation of Web user Session Dissimilarity measures using Medoids based Relational Fuzzy clustering

Indian Journal of Science and Technology, 2016

Background/Objectives: Proficient relational clustering of web users’ sessions not only depends o... more Background/Objectives: Proficient relational clustering of web users’ sessions not only depends on clustering algorithm’s character but also profoundly influenced by the used dissimilarity measures. Therefore, determining the right dissimilarity measure to capture the actual access behaviour of the web user is imperative for the significant clustering.Methods: In this paper, the concept of an augmented session is used to derive different augmented session dissimilarity measures. The quantitative performance evaluation of different session dissimilarity measures are performed using a relational fuzzy c-medoid clustering approach. The intra-cluster and inter-cluster distance based cluster quality ratio is used for performance evaluation. Findings: The experimental results demonstrated that augmented web user session dissimilarity in general, and intuitive augmented session dissimilarity, in particular, performed better than the other dissimilarity measures. Improvements: It is argued that augmented session similarity measures are more realistic and represent session similarities based on the web user’s habits, interest, and expectations as compared to simple binary session similarity measures.

Fuzzy Rule-Based Approach for Software Fault Prediction

IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2017

Knowing faulty modules prior to testing makes testing more effective and helps to obtain reliable... more Knowing faulty modules prior to testing makes testing more effective and helps to obtain reliable software. Here, we develop a framework for automatic extraction of human understandable fuzzy rules for software fault detection/classification. This is an integrated framework to simultaneously identify useful determinants (attributes) of faults and fuzzy rules using those attributes. At the beginning of the training, the system assumes every attribute (feature) as a useless feature and then uses a concept of feature attenuating gate to select useful features. The learning process opens the gates or closes them more tightly based on utility of the features. Our system can discard derogatory and indifferent attributes and select the useful ones. It can also exploit subtle nonlinear interaction between attributes. In order to demonstrate the effectiveness of the framework, we have used several publicly available software fault data sets and compared the performance of our method with that of some existing methods. The results using tenfold cross-validation setup show that our system can find useful fuzzy rules for fault prediction.

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CSHURI - Modified HURI Algorithm for Customer Segmentation and Transaction Profitability

International Journal of Computer Science, Engineering and Information Technology, 2012

Association rule mining (ARM) is the process of generating rules based on the correlation between... more Association rule mining (ARM) is the process of generating rules based on the correlation between the set of items that the customers purchase.Of late, data mining researchers have improved upon the quality of association rule mining for business development by incorporating factors like value (utility), quantity of items sold (weight) and profit. The rules mined without considering utility values (profit margin) will lead to a probable loss of profitable rules. The advantage of wealth of the customers' needs information and rules aids the retailer in designing his store layout[9]. An algorithm CSHURI, Customer Segmentation using HURI, is proposed, a modified version of HURI [6], finds customers who purchase high profitable rare items and accordingly classify the customers based on some criteria; for example, a retail business may need to identify valuable customers who are major contributors to a company's overall profit. For a potential customer arriving in the store, which customer group one should belong to according to customer needs, what are the preferred functional features or products that the customer focuses on and what kind of offers will satisfy the customer, etc., finds the key in targeting customers to improve sales [9], which forms the base for customer utility mining.

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Exploiting Vulnerabilities in the SCADA Modbus Protocol: An ICT-Reliant Perspective

Communications in Computer and Information Science, 2022

Distributed Grid restoration based on graph theory

2020 IEEE International Symposium on Sustainable Energy, Signal Processing and Cyber Security (iSSSC), 2020

With the emergence of smart grids as the primary means of distribution across wide areas, the imp... more With the emergence of smart grids as the primary means of distribution across wide areas, the importance of improving its resilience to faults and mishaps is increasing. The reliability of a distribution system depends upon its tolerance to attacks and the efficiency of restoration after an attack occurs. This paper proposes a unique approach to the restoration of smart grids under attack by impostors or due to natural calamities via optimal islanding of the grid with primary generators and distributed generators(DGs) into sub-grids minimizing the amount of load shed which needs to be incurred and at the same time minimizing the number of switching operations via graph theory. The minimum load which needs to be shed is computed in the first stage followed by selecting the nodes whose load needs to be shed to achieve such a configuration and then finally deriving the sequence of switching operations required to achieve the configuration. The proposed method is tested against standard...

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Cyber Physical Defense Framework for Distributed Smart Grid Applications

Cyber-Physical Systems (CPS) is the amalgamation of highly sophisticated sensors with physical sp... more Cyber-Physical Systems (CPS) is the amalgamation of highly sophisticated sensors with physical spaces. These close conjunctions of sensors with communication infrastructure intrinsically linking to society’s Critical Infrastructures (C.I.) are being witnessed more often in the context of Smart Grid (SG). As a backbone of C.I., Smart Grid demonstrates ability to precisely monitor large scale energy systems and designed in order to achieve complex local and global objectives. Being capable of performing such sophisticated operation it also bears the vulnerability of being exposed for cyber-physical co-ordinated attack that may lead to catastrophic effect. Many researchers have analyze the different stages of cyber-physical co-ordinated attacks like attack detection, prevention, impact analysis and recovery plans but there exist a research gap to address all the issues under single framework. Through this paper, we propose a novel Cyber Physical Defense Framework (CPDF) based on Nation...

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