ICFAI Tech (computer Science)

The requirement for fast and lean software delivery from the today's industry leads to adoption of agile development approaches over other conventional approaches. The Dynamic and competitive environment leads to rapid change of customer requirements which has also boosted the use of agile approach as it has merits like simplified documents and fast release which further leads to maximizing effectiveness and productivity. However, from security point of view it is very difficult to decide whether to use an agile approach for a given project or not, as there is no well defined empirical decision making process. This paper provides a roadmap for taking decision using Fuzzy Analytic Hierarchy Process and Artificial Neural Network approach by calculating Global Agility Indicator and in case it is selected, it further provides Local Agility Indicator to decide among popular Agile Development methods like Extreme Programming, Scrum, Feature-driven Development, Crystal Clear, Dynamic Software Development Method and Lean development. The fuzzy AHP deals with the inability of AHP to deal with the subjectiveness in the pair wise comparison process. In order to compensate the decision maker's uncertainty, it takes into account a range of values instead of a single crisp value. Further Artificial Neural Network with back propagation approach is used to train the network and producing correct results even for inconsistent input. By taking such a systematic approach for development, it inherently addresses the major concern of security on projects using agile approach.

Agile methods have came up as an alternative to traditional software development by providing faster and lean ways to avoid overheads which are being imposed intrinsically by traditional methods. With their widespread use many organizations are practically and technically able to adapt on agile approach effectively and rapidly. There are number of approaches to help in such a transition. However, it becomes a mammoth task for project analyst to decide upon which agile method should be used for a particular project, in the absence of any well defined guidelines or framework. As there is lack of any empirical approach for agile method selection thus this paper provides a roadmap based upon modified Fuzzy PROMETHEE with the help of Fuzzy Analytic Hierarchy Process (AHP). This paper provides a framework to choose among widely used and popular agile development methods like Extreme Programming (XP), Lean development, Scrum, Dynamic Software Development Method (DSDM), Feature-driven Development (FDD) and Crystal Clear. Because of lack of any scientific and empirical work in this field, these world widely used and tested methods would provide the authenticity and acceptability of this approach, which is sometimes questioned in agile development method selection. This work would definitely prove to be an important contribution in this field for further improvement and research

Today's software industry is striving for rapid software delivery with keeping in view the changing customer requirements. Agile development approach has evolved in order to fulfil the needs of dynamic environment in which traditional approaches were failing to cope with. It has the cutting edge like fast release and minimum documentation which results in maximizing speed and profit. However, the most difficult task is to make the decision such that the agile development method should be chosen according to the given requirements of the particular project. In the absence of any empirical work, we have proposed a multilevel hybrid approach using the world widely accepted methods as Analytic Hierarchy Process (AHP), Preference Ranking Organization Method for Enrichment Evaluation (PROME-THEE) and Fuzzy logic. We have calculated results from four different methods of multi criteria decision making and the final result is evaluated using the rank aggregation methods. This work would prove to be a pivotal point in the field of agile development as it includes these empirical methods which provide the much awaited authenticity and reliability, which sometimes is questioned in case of agile approach.

Agile software development is receiving the attention of software developers and researchers thanks to its fast software delivery and flexible development plan capabilities. The fast release and simplified documentation thus leads to the preference of the agile development model over several other traditional models. This, however, also raises critical concerns about the security issues. In this research work, we propose a framework for secure agile development. The selection of development methodology among agile versus plan driven approaches and the particular agile development method among Extreme Programming (XP), Crystal Clear, Scrum, Lean Development, Dynamic Software Development Method and Feature-Driven Development is made on the basis of the specific requirements of the project using empirical methods like AHP and PROMETHEE. Systematic Literature Review (SLR) and survey study are used to obtain the authentic industrial feedback, followed by the application of non-parametric statistical tests to identify and select the most suitable and beneficial security activities from well known security engineering processes like CLASP, Common Criteria, Cigital Touchpoints and Microsoft's SDL. A lightweight method is also introduced for integrating these security activities identified from SLR and survey study, using a dynamic integration algorithm without compromising the agility of the process. The proposed framework for integration of these security activities is implemented in java to automate the entire process and provides maximum benefit at a low integration cost.

Individual users are able to buy and sell a broad variety of goods and services worldwide on online auction and shopping websites, e.g. eBay.com and Taobao.com. However, attackers have also attempted to conduct fraudulent activities against honest parties for the purpose of illegitimate profit. On Internet auction sites, auction fraud mainly involves fraud attributable to the non-delivery of products purchased through an Internet auction site or the misrepresentation of a product advertised for sale. Malicious sellers may post a non existing item for bidding with false description to deceive the buyer concerning its true value, and request payments to be wired directly to them. Similarly, malicious buyers may make a purchase through a fraudulent credit card where the address of the card holder does not match the shipping address. Both consumers as well as merchants can be victims of online auction fraud, as well as the commercial auction websites. In this paper we study the problem ...

Shortest job first task scheduling algorithm allocates task based on the length of the task, i.e the task that will have small execution time will be scheduled first and the longer tasks will be executed later based on system availability. Min- Min algorithm will schedule short tasks parallel and long tasks will follow them. Short tasks will be executed until the system is free to schedule and execute longer tasks. Task Particle optimization model can be used for allocating the tasks in the network of cloud computing network by applying Quality of Service (QoS) to satisfy user’s needs. The tasks are categorized into different groups. Every one group contains the tasks with attributes (types of users and tasks, size and latency of the task). Once the task is allocated to a particular group, scheduler starts assigning these tasks to accessible services. The proposed optimization model includes Resource and load balancing Optimization, Non-linear objective function, Resource allocation...

In the past few years, remote monitoring technologies have grown increasingly important in the delivery of healthcare. According to healthcare professionals, a variety of factors in uence the public perception of connected healthcare systems in a variety of ways. First and foremost, wearable technology in healthcare must establish better bonds with the individuals who will be using them. e emotional reactions of patients to obtaining remote healthcare services may be of interest to healthcare practitioners if they are given the opportunity to investigate them. In this study, we develop an arti cial intelligence-based classi cation system that aims to detect the emotions from the input data using metaheuristic feature selection and machine learning classi cation. e proposed model is made to undergo series of steps involving preprocessing, feature selection, and classi cation. e simulation is conducted to test the e cacy of the model on various features present in a dataset. e results of simulation show that the proposed model is e ective enough to classify the emotions from the input dataset than other existing methods.

In cloud computing resources are considered as services hence utilization of the resources in an efficient way is done by using task scheduling and load balancing. Quality of service is an important factor to measure the trustiness of the cloud. Using quality of service in task scheduling will address the problems of security in cloud computing. This paper studied quality of service based task scheduling algorithms and the parameters used for scheduling. By comparing the results the efficiency of the algorithm is measured and limitations are given. We can improve the efficiency of the quality of service based task scheduling algorithms by considering these factors arriving time of the task, time taken by the task to execute on the resource and the cost in use for the communication.

One of the ongoing technologies which are used by large number of companies and users is cloud computing environment. This computing technology has proved that it provides certainly a different level of efficiency, security, privacy, flexibility and availability to its users. Cloud computing delivers on demand services to the users by using various service-based models. All these models work on utility-based computing such that users pay for their used services. Along with the various advantages of the cloud computing environment, it has its own limitations and problems such as efficient resource identification or discovery, security, task scheduling, compliance and sustainability. Among these resource identification and scheduling plays an important role because users always submits their jobs and expects responses in least possible time. Research is happening all around the world to optimize the response time, make span so as to reduce the burden on the cloud resources. In this paper, QoS based service ranking model is proposed for cloud computing environment to find the essential top ranked services. Proposed model is implemented in two phases. In the first phase, similarity computation between the users and their services is considered. In the second phase, computing the missing values based on the computed similarity measures is calculated. The efficiency of the proposed ranking is measured and the average precision correlation of the proposed ranking measure is showing better results than the existing measures.

In this work poly(3,4-ethylenedioxythiophene) (PEDOT) coated SnO 2-Fe 2 O 3 continuous nanotubes with a uniform core-shell structure have been demonstrated for rapid sensitive detection of iodide ions. The SnO 2-Fe 2 O 3 nanotubes were firstly fabricated via an electrospinning technique and following calcination process. An in situ polymerization approach was then performed to coat a uniform PEDOT shell on the surface of as-prepared SnO 2-Fe 2 O 3 nanotubes by vapor phase polymerization, using Fe 2 O 3 on the surface of nanotubes as an oxidant in an acidic condition. The resultant PEDOT@SnO 2-Fe 2 O 3 core-shell nanotubes exhibit a fast response time (~4 s) toward iodide ion detection and a linear current response ranging from 10 to 100 µM, with a detection limit of 1.5 µM and sensitivity of 70 µA/mM/cm 2. The facile fabrication process and high sensing performance of this study can promote a wide range of potential applications in human health monitoring and biosensing systems.