Development of Continuous Authentication System on Android-Based Online Exam Application

Development of Continuous Authentication System on Android-Based Online Exam Application

The impact of technology in education can be seen from the development of learning systems. According to Alonso and Norman in particular there are four types of learning systems, namely conventional learning systems, instructional learning systems, e-learning, and mobile learning [1]. M-learning supports learning activities carried out continuously through mobile devices such as smartphones and tablets flexibly anytime and anywhere [2]. Over times, emerging innovations implemented as a feature on m-learning, such as online exam. Adapted from the conventional exam system the online exam was developed as an examination system that utilizes the internet network. Through the online exam system, examinees can access exam questions and answer without requiring a question sheet or answer sheet in physical form. However, there are still deficiencies in the implementation of online examinations. Currently the online test execution is often still held together in a room. This is less effective and makes no significant difference between conducting online examinations and conventional examinations [3]. Chula G. King's research shows that 73.6% of students think that cheating on online tests is easier than doing it on conventional examinations [4], Based on this it is necessary to improve the effectiveness of online examinations so that they can be carried out remotely and without supervision. The way to minimize cheating on online exams, especially impersonating is to develop a continuous authentication system on online exam applications that can validate the suitability of the examinees and identify participants who cheated during the exam. Hopefully, by the authentication in the online exam application makes online test activities can be done remote and unattended supervisors but can be implemented properly and without any fraud.

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C2C Ecommerce Environment: A Pattern Based Anti-Fraud Method

C2C Ecommerce Environment: A Pattern Based Anti-Fraud Method

INTRODUCTION 

With the growing popularity of online trading sites, reputation systems are increasingly becoming an integral part of C2C ecommerce systems. Reputation systems can collect, aggregate and distribute participant feedback from past actions to encourage sellers' honest behaviors, and effectively avoid cheating behaviors of those dishonest sellers. In such a situation that neither buyers nor sellers are well informed of each other, the reputation system is able to help buyers determine which sellers are more credible. Such as eBay and Taobao[1][2][3][4], they all have their own reputation systems. The world's largest C2C online auction site eBay has a reputation system dealing with feedback information. Upon the completion of each transaction, buyers and sellers have rights to give an rating points(-1, 0, 1)of the other[5]. Code Shoppy Each participant will have an identification name, and its evaluation will be given in connection with the transaction name on it. Nowadays, many trading sites are using reputation systems like eBay's, while some of them provide 1-5 rating range or use some other rating scales. 

Some of them calculate the average feedback rating points while others calculate the cumulative ones. These reputation-rating mechanisms can’t well deal with thereputation slander, the reputation speculation and other means of fraud generally. This leads to the reputation values given by reputation systems can’t effectively reflect the performance of sellers, eventually leading to the average benefit of buyers greatly reduced. In order to deal with the fraud patterns mentioned above, Based on TRUST[8] model, we proposed a new fraud pattern identification and filtering method. It is to find fraud pattern in Time Window Scope and filter out those fraud ratings, Such as plenty of newer buyers give higher ratings over threshold or lower ratings below threshold to a fixed number of sellers, higher ratings over threshold are given by a fixed number of sellers each other, etc. In this way, the reputation value that the buyer computed will show much more fully of the true reputation of the sellers. 

The experiment results in multi-agent system JADE prove that the method proposed by us can make the sellers get more profit. The organization of the paper is as follows. The second part introduces two kinds of fraud patterns that are very regular and very hard to be recognized in ecommerce system. The third part expounds the anti-fraud method we put forward based on TRUST; part four illuminates the simulation experiment which is based on multi-agent system JADE; part five is the summary of the paper and discusses the next step of our study. 

TWO COMMON PATTERNS OF FRAUD 

A.The Reputation Slander The Reputation slander is such misconduct that some sellers encourage other sellers with partnerships or they register a number of buyers to deliberately give low-ratings to their competitors to achieve the aim of suppressing their competitors. The Reputation slander undermines the harmonious order of transaction, making high-quality sellers' reputation damaged and greatly reducing the overall transaction gains. Current C2C ecommerce systems usually take such approaches that the victims provide proof to the platform for arbitration by the manual review and recognition. Manual processing always is an inefficient and time-consuming job. 

B.The Reputation Speculation The most difficult issue in reputation system is the reputation speculation which sellers and their accomplices conduct high scores for each other or sellers register a great quantity of accounts performing virtual transactions to get high ratings. Recently, Taobao has a set of programs to monitor thereputation speculationbehavior. The first is prevention mechanism. Investigations by machines are available to filter out sellers with abnormal fluctuations apparently and they are classified as "black box". Then punishment mechanism follows. Through manual analysis, communication with the reputation speculation suspected sellers to get further confirmation. And Taobao also encourages users to report reputation speculationsellers. 

 In addition, the consumer protection play on promotion has an indirect containment for reputation speculation. The scheme is proposed to allow sellers in Taobao bet a certain amount of deposit, from which Taobao can extract partial compensation if the seller cheats consumer. However, manual processing is time-consuming, laborious and inefficient after all, so researchers are on studies of some automatic filtering of false rating mechanism.

A Real Time Solution to Flood Monitoring System using IoT and Wireless Sensor Networks

A Real Time Solution to Flood Monitoring System using IoT and Wireless Sensor Networks
Abstract – There are some places that are more prone to flooding than other placess, the implementation of flood alert systems near any major water area or body of water provides critical information that can protect property and save lives. Of course, the most effective flood warning methods are very costly and requires high maintenance and also requires highly qualified employee to operate it.
Nowadays, there is no idea about when flood will occur so there is need to prewar people who are near the flooded area. Hence we are design this system to inform the people about the upcoming flood through notification and alert messages. For that purpose we are going to use some sensors which will helpful to give information about the flood. As well as we are going to give all safe places near the user location where user can migrate. Always we are using map for trace safe location. This system provides actual implementation to organizations, communities and individuals interested in establishing and operating flood monitoring and warning systems.
Key Words: Flood Monitoring, Node MCU ESP8266, Sensors, Android Application, Web Application
1. INTRODUCTION
To develop A Real Time Solution to Flood Monitoring Using IoT and Wireless Sensor Network, weproposed a flood warning system which requires attention to three basic factors: Data collection via gaging, data processing, and the hardware and software required, and the dissemination of flood warning information. While automated flood warning systems are often surprisingly inexpensive to implement, the primary factor determining cost for any such system is the number of gage site locations.[9]
Severe flooding affected Indian state of Kerala due to unusual high rain during monsoon season. It was the worst flooding in Kerala in nearly a century. In which over 373 people died within fortnight. Thirty-five out of 42 dams within the state open for the first time in history. Kerala received heavy monsoon rainfall on the midevening of August and resulting in dams filling to capacity in thefirst 24 hours of rainfall the state received 310 mm of rain.
2. LITERATURE REVIEW
Existing system refers to the system is to develop a local real-time river flood monitoring and warning system for the selected communities near river. This study focuses only on the detection and early warning alert system (via website and/or cell phone text messages) that alerts local subscribers of potential flood events.
For this project, we have referred some IEEE papers and what we have studied in these papers is shortly described as follows:
In this paper [10],[11],[12] proposed an IoT based water monitoring system that measure water level in real time. The prototype is based on idea that the level of water can be very important parameterwhen it comes to the flood occurrencesespecially in disaster prone area. A water level sensor is used to detect the desired parameter and if the water level reaches the parameter the signal will be freed in real time to social network like Twitter. A cloud server was configured as data repository. The measurement of water level are displayed in remote dashboard. The proposed solution with integrated sensory system that allows inner monitoring of water quality. Alerts and relevant data are transmitted over the internet to a cloud server and can be received by user terminal owned by consumer. The outcome of water measurement is displayed in web based remote dashboard.
In this paper [11], presents a neuro-fuzzy controller based on flood monitoring system using wireless sensor network. The distributed sensor nodes used IEEE 802.15.4 protocol, to collect sensor information such as water level data from the river. The Sensor information is send to distributed alerts center via Arduino microcontroller and Xbee Transceiver. At the distributed alert center, XBee transceiver and Raspberry pi microcomputer are used to generate flood alert based on sensor information and to detect flood data and this data are stored in database. This is not cost effective system. And performance also weak as compared to our system.
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 06 Issue: 02 | Feb 2019 www.irjet.net p-ISSN: 2395-0072
© 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 1808
3. BASIC CONCEPTS/TECHNOLOGIES USED
3.1Hardware module
In this project, some hardware is used that are Microcontroller, sensors, components required for power supply. The Hardware collects the water level, Pressure of water, Rainfall measure to detect the levels of the flood. The hardware consists of Wi-Fi enabled controller which connects to the server and allows to share the data to through internet.
1. Microcontroller- This does the controlling with processing .Microcontroller will take the information from the sensor .This information will sent to the admin through the database
2. Sensors-This will collect the information from the particular nodes which are located at certain site. There are four sensors we are going to use in this project. They are as follows:
Water level measurement: This sensor is used to measure the water level height. For that we are going to use Ultrasonic sensorwhich emits short, high frequency sound pulses at regular intervals. If they strike an object, then they are reflected back as echo signals to the sensors.
Rainfall measurement: This sensor is used to measure the average rainfall. For that we are going to use same ultrasonic sensor.Ultrasonic sensor is 4 pin sensor. Those are ground connection (GND), Trigger, echo and last current (VCC).
TemperatureandHumidity: This sensor is used to measure change in atmospheric temperature and humidity. For this we are using DHT11 sensor which works on one wire protocol and gives digital output.
Pressure measurement: This sensor is used to determine the atmospheric pressure. For this we are going to useBMP 180Barometric sensor.
3. Power Supply- In real time we get 230v AC, in actual project we do not need this amount of power supply so we convert this AC power supply to DC power supply.
3.2 Software Module
In this module, we have done an android application as well as the Website application for this project. Admin web page will contain and display the information like Login, Registration, Number of users registered to the app, status of the sensor, safe places near flood affected area where people can migrate and that places are shown on the Map.
The Android application will be used by the users who are register. After registration the user can login with aunique username and password. And then user can access all facilities provided by application. Application is provided the information like current status of water level and temperature etc. This app contain map which are show the safe places near the user and also the current place where the user is.
3.3 Database Module
Microcontroller will send the values measured by the sensors to the server. This will contain the number of users registered to App; this will also show the safe places through the Map. The data uploaded on server is stored on the database. The stored data is then routed to the front end web applications and mobile application
4. PROPOSED SYSTEM
1. There will be a node as shown in above diagram.
2. This node is the independent flood monitoring node equipped with necessary sensors and connectivity modules.
3. It has three major stages, Including Sensors, Controller, Wi-Fi interface to upload the information on server.
4. Data from various sensors are collected by the ESP and is then computed and uploaded on the server.
5. The data uploaded on server is stored on the database.
6. The stored data is then routed to the front end web applications and mobile applications.
Module Description
The overall system consists of 3 main stages –
1] Hardware nodes
2] Cloud Architecture
3] Front end clients (mobile app)
Chart -1:Proposed System Architecture
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 06 Issue: 02 | Feb 2019 www.irjet.net p-ISSN: 2395-0072
© 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 1809
The Hardware collects the water level, Pressure of water, Rainfall measure to detect the levels of the flood. The hardware consists of Wi-Fi enabled controller which connects to the server and allows to share the data to through internet .The architecture contains Server and database which handles the data coming from the devices and saves it in the database. The Front end apps will have http client to establish connection to device and backend. The app will collect the data from backend and represent it on the map. All these communication will be done over the internet though http protocol.
5. IMPLEMENTATION AND RESULTS
Fig: Hardware Implementation
Snapshot of website:
Website: Login page
Above snapshot is of the website login page (the first page of website) through which the admin can enter his username and password and have access to the facilities provided by the website.
Website: Users
Above page shows the list of registered users to admin on website who have registered using the android application.
Website: River Status
Above page shows the current values detected by the sensors from river side, recent top 10 status updates are shown.
Website: Dam Status
Above page shows the current values at admin site detected by the sensors from dam side, recent top 10 status updates are shown.
Website: Safe place List
Above page shows the safe places list where the people can migrate after the alert is received for migrating to a safe place. (Alert will be given after a threshold value is reached).

Power Electronics Loads Considering Response Cost

Power Electronics Loads Considering Response Cost

Nowadays, microgrid has received worldwide attention, where a few DG units and loads are clustered together [1]. It is a good choice for power system to improve the reliability and power quality. Microgrid operation is highly flexible, it therefore can operate freely between the grid-connected mode and islanded mode [2], [3]. It is well known that operation stability and reliability of power system is highly depended on balance between the supply and demand in real time. This is a big challenge for microgrid since both power generators and loads could change rapidly and unexpectedly due to many reasons, such as DGs capacity limitation, output power fluctuation, line fault and sudden load change [4], [5]. 

Keeping large power reserve can solve this problem. In [6], ESS are considered in the microgrid construction and applied to help maintain the supply and demand balance. Although, it can maintain the microgrid stable, it is not ideal mothed due to the high price of the ESS. On the other hand, the demand side (load) response is one of the available and cheaper method to solve the supply and demand imbalance problem in microgrid [7]. Demand Response can be defined as the end users change their consumption models to response the power grid operation. 

There are many researches on the demand response program used in the utility grid, which can generally be classified as the price-based programs and incentive-based programs [7]-[9], as shown in Fig. 1. The demand response programs are usually integrated to the power network management system. Although the centralized demand response programs are generally more accurate, they usually need expensive and fast communication links which may not be economical for islanded microgrid. While, the response program reliability is highly dependent on the communication. The communication or the central controller fault may introduce the response method failure. Thus, there is a great interest in decentralized response scheme. 

In [10], a decentralized load control of was proposed to introduce the  loads to participate in supply and demand balance of the islanded microgrid. It makes the FPELs regulate their power consumption in proportion to their power capacities only using local measurement. However, this scheme does not consider the response cost of the loads involved. It will lead to higher response cost which will introduce additional operation cost for islanded microgrid.

https://codeshoppy.com/android-app-ideas-for-students-college-project.html

 

To address the concern illustrated above, an autonomous control of flexible loads considering response cost scheme has been proposed in this paper. The proposed schemes use the response cost of the FPELs to achieve different dispatch for various FPELs to participate in the supply and demand balance. It forces the lower response cost FEPL to automatically reduce more power consumption in order to satisfy the supply and demand balance. The overall response cost and the communication links, therefore, will be saved when compared with the traditional load response schemes. Simulation results have verified the effectiveness of the proposed control scheme.

 An autonomous control of FPELs considering response cost scheme has been proposed in this paper. Unlike the traditional scheme which consider the response capacities, the proposed control scheme arrived at a better balance between load response capacities and response costs. It makes the lower costed FPEL to reduce more power consumption to participate in the supply and demand balance. Thus, it can reduce the total response cost for the microgrid and save the investments of the ESS and communication system. The finding has been verified via simulation results. View more