Daya Gupta

Engineering Methods from Method Requirements Specifications

By analogy with a Software Requirements Specification (SRS), it is argued that a Method Requirements Specification (MRS) should be introduced in method engineering. It shares with the SRS the property of implementation-independence. This means that an MRS must be an instance of an abstract metamodel and not of a technical metamodel like GOPRR (Graph, Object, Property, Relationship, and Role). The MRS is then translated to be an instantiation of a technical metamodel. We develop a representation system for an MRS and describe an automated process for instantiating a technical metamodel with an MRS. This instantiation is used to produce the actual method which is then given to a metaCASE to produce a CASE tool. Thus, we propose a method engineering approach rooted in the MRS.

Hybrid bio-inspired techniques for land cover feature extraction: A remote sensing perspective

Recent advances in the theoretical and practical implementations of biogeography have led to the exploration of new bio-inspired techniques which can prove to be the building blocks of hybrid bio-inspired techniques. This aspect was discovered while considering the exploration of bio-inspired intelligence for developing generic optimization algorithms that can be adapted for performing the given land cover feature extraction task at hand. Certain bio-inspired techniques when integrated with the existing optimization techniques can drastically improve their optimization capability hence leading to better feature extraction. In this paper, we propose a generic architectural framework of a hybrid biologically inspired technique that is characterized by its capability to adapt according to the database of expert knowledge for a more efficient, focused and refined feature extraction. Since our hybrid feature extractor possesses intelligence for selective cluster identification for application of either of the constituent techniques which is in turn based on an inefficiency analysis, we term our classifier as the hybrid bio-inspired pattern analysis based intelligent classifier. Our hybrid classifier combines the strengths of the modified BBO Technique for land cover feature extraction with the Hybrid ACO2/PSO Technique for a more refined land cover feature extraction. The algorithm has been tested for for the remote sensing application of land cover feature extraction where we have applied it to the 7-Band carto-set satellite image of size 472x546 of the Alwar area in Rajasthan and gives far better feature extraction results than the original biogeography based land cover feature extractor [20] and the other soft computing techniques such as ACO, Hybrid PSO-ACO2, Hybrid ACO-BBO Classifier, Fuzzy sets, Rough-Fuzzy Tie up etc.. The 7-band Alwar Image is a benchmark image for testing the performance of a bio-inspired classifier on multi-spectral satellite images since this image is a complete image in the sense that it contains all the land cover features that we need to extract and hence land cover feature extraction results are demonstrated and compared using this image as the standard image.

NFC based secure mobile healthcare system

With the recent increase in usage of mobile devices especially in developing countries, they can be used for an efficient healthcare management. In this work, we have proposed a novel architecture for improving healthcare system with the help of Android based mobile devices with NFC [1] and Bluetooth interfaces, smartcard technology on tamper resistant secure element (SE) for storing credentials and secure data, and a HealthSecure service on a hybrid cloud for security and health record management. The main contribution of this paper is proposal of applications for i) Secure Medical Tags for reducing medical errors and ii) Secure Healthcard for storing Electronic Health Record (EHR) based on Secure NFC Tags, mobile device using NFC P2P Mode or Card Emulation Mode. We have also briefly mentioned a basic security framework requirement for the applications. Since NFC NDEF format is prone to security attacks [2], we have utilized low level APIs on Android based mobile devices, to securely access NFC tags such as MIFARE Classic tags with NFC-A (ISO 1443-3A) properties. Simple touch of NFC enabled mobile devices can benefit both the patient as well as the medical doctors by providing a robust and secure health flow. It can also provide portability of devices and usability for health management in emergency situation, overpopulated hospitals and remote locations.

Decisions and Decision Requirements for Data Warehouse Systems

We develop the notion of a decision requirement as the pair where ‘information’ is that required by the decision maker to assess if the ‘decision’ is to be taken or not. It is shown that there are two kinds of decisions, imperative and managerial. The former are decisions about which transactional service out of a choice of transactional services is to be provided. Managerial decisions determine what infrastructure out of a set of possibilities is to be put in place. It is shown that a decision is the reason why a functionality of an information system is invoked. The notion of decision requirement is clarified through a decisional requirement meta model. This is supported by a decision and information meta model. The example of a health scheme is taken to illustrate the different kinds of decisions and decision requirements.

An improved ID-Based key management scheme in wireless sensor network

Key management is one of the critical areas in WSN as limited resources of sensor nodes restrict the use of conventional security techniques. Most of the sensor networks use shared key among all the nodes to make communicational overhead minimal. But it is vulnerable to many attacks like stolen-verifier attack, replay attack, node-compromise attack etc. In this paper, we propose an efficient ID-based key management scheme using bilinear pairings. Our ECC based scheme requires light computational and communicational load and resist the major attacks in Wireless Sensor Network.

Secure Access of Smart Cards Using Elliptic Curve Cryptosystems

Public Key Cryptography (PKC) is recently playing an essential role in electronic banking and financial transactions. Elliptic Curve Cryptography (ECC) is one of the best public key techniques for its small key size and high security and is suitable for secure access of smart cards because implementation on smart cards is challenging to the platforms memory, bandwidth, and computation constraints. This paper proposes a mutual authentication protocol based on ECDSA for a secure access of smart card which allows both the server and the user to verify each others authenticity. Our scheme is efficient as it results in reducing cost and improving performance by using ECC in smart cards.

Taxonomy of nature inspired computational intelligence: A remote sensing perspective

The concepts in geospatial sciences are generally vague, ambiguous and imprecise. Also, a combination of spectral, spatial and radiometric resolution of space-borne sensors presents a selective and incomplete look of the geospatial feature/object under its view from the space. Recently, the nature inspired computational intelligence (CI) techniques have emerged as an efficient mechanism to handle diverse uncertainty characteristics. This paper proposes that the human-mind model based computational intelligence techniques, the artificial immune system based computational intelligence techniques; the swarm intelligence based computational intelligence techniques and the emerging geo-sciences based intelligent techniques can be considered as the four pillars of nature inspired CI techniques and hence redefines and extends the taxonomy of nature inspired CI. Researchers have shown keen interest on the applications of natural computing in divergent domains. Scanty references are available on the applications of nature inspired computing in the area of remote sensing. We hence also propose the taxonomy of the most recent nature inspired CI techniques that have been adapted till date for geo-spatial feature extraction and analyze their performances. We also construct a technology timeline of these recent nature inspired CI techniques.

Software Implementation of Curve based Cryptography for Constrained Devices

Curve based cryptography are preferred for embedded hardware since they require shorter operand size than RSA to attain the same security level. So ECC and HECC are more suitable in constrained environment such as smart cards if we can select suitable curves and efficient scalar multiplication technique to speed up arithmetic on the curve. With this in view, this paper explores in details the main operations like scalar multiplication, group operations on Jacobian, finite field operations etc which are the prime steps for efficient implementation of ECC / HECC. We also have compared the timings of main operations like scalar multiplication, encryption and decryption of Elliptic and Hyperelliptic curve cryptosystems to study the relative performance of these cryptosystems.

Dynamic Model of Blended Biogeography Based Optimization for Land Cover Feature Extraction

This paper presents a dynamic model of the blended biogeography based optimization (BBO) for land cover feature extraction. In the blended BBO, the habitats represent the candidate problem solutions and the species migration represents the sharing of features (SIVs) between candidate solutions according to the fitness of the habitats which is called their HSI value [9]. However, it is assumed that these SIVs i.e. the number of solution features, remain constant for every habitat [10] and the HSI for each habitat depends only on the immigration and the emigration rates of species [9]. This paper extends the blended BBO by considering the fact that the no. of SIVs or the decision variables may not remain constant for all candidate solutions (habitats) that are part of the Universal habitat. Since the characteristics of each habitat vary greatly hence, comparing all the habitats using the same set of SIVs may be misleading and also may not lead to an optimum solution. Hence, in our dynamic model, we consider the fact that HSI of a solution is affected by factors other than migration of SIVs i.e. solution features, also. These other factors can be modeled as several definitions of HSI of a habitat, each definition based on a different set of SIVs which simulates the effect of these other factors. We demonstrate the performance of the proposed model by running it on the real world problem of land cover feature extraction in a multi-spectral satellite image.

PCA based cost estimation model for agile software development projects

Agile software development has been attached much importance as a new software engineering methodology as it emphasizes on good communication between the developers, the rapid delivery of software, and change on demand. The metrics and methods from conventional lifecycle models cannot predict accurately for agile projects. We have proposed a new cost estimation model for agile software development projects. In this model we apply Principal Component Analysis to reduce the dimensions of the attributes required and identify the key attributes which have maximum correlation to the development cost; and then use constraint solving approach to satisfy the criteria imposed by agile manifesto. The proposed methodology is found to bet suitable for agile projects as it uses constraint programming to explicitly check for satisfaction of agile manifestos. On comparison with other approaches under research we find that our model provides a low MMRE value i.e.50.63. Our methodology can also be used in case of unavailability of historical data or expert opinion. Hence we can safely say that the proposed cost estimation approach increases the precision and accuracy of estimates; and hence is better suited for the Agile Software Development Projects.