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Proceedings ArticleDOI

Desktop phishing attack detection and elimination using TSO program

M. K. Priyan1, C. Gokul Nath1, E. Vishnu Balan1, K.P. Rama Prabha1, R. Jeyanthi1 
06 May 2015-pp 198-201
TL;DR: A TSO programmatically solution to Desktop phishing attack, which has a capability to detection and prevention of the attack.
Abstract: In today's computer world security is the major issue. For every project most of the money spent on the security and testing than developing. Because security issue is one of the major issue for everyone to protect data. According to the security analysts more than seven billion hackers are existing over one hundred and five billion computers. Almost all of them trying to collapse the security system. There are so many security attacks are rotating throughout the network. Phishing is one of the popular security attack on the websites due to fall in this attack we lose our valuable information. Today most of us are using e-commerce websites for online shopping. Most of them are paying money through online. By taking this as an advantage so many hackers are host phishing website for stealing our bank and credit card detail. No only this so many social accounts are hacking daily. Other than this there is a new model of attack that is Desktop phishing. It is one of the advance attack which is applied on victim computer it can prevent the victim user actions in websites. By that we don't allow to the real page even to modify of change our password. By that the attacker success his goal. For phishing detection there are so many solutions are available. But Till now so many antiviruses can't find this attack. So we prose a TSO programmatically solution to Desktop phishing attack. It has a capability to detection and prevention of the attack.
Citations
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Journal ArticleDOI
01 Oct 2018
TL;DR: The proposed speech recognition method offers 98.2% accuracy and consists of a linear dual classifier that finds the same class attributes and different class attributes simultaneously and a cross fitness validation method to prevent over fitting problem.
Abstract: In this research, a new speech recognition method based on improved feature extraction and improved support vector machine (ISVM) is developed. A Gaussian filter is used to denoise the input speech signal. The feature extraction method extracts five features such as peak values, Mel frequency cepstral coefficient (MFCC), tri-spectral features, discrete wavelet transform (DWT), and the difference values between the input and the standard signal. Next, these features are scaled using linear identical scaling (LIS) method with the same scaling method and the same scaling factors for each set of features in both training and testing phases. Following this, to accomplish the training process, an ISVM is developed with best fitness validation. The ISVM consists of two stages: (i) linear dual classifier that finds the same class attributes and different class attributes simultaneously and (ii) cross fitness validation (CFV) method to prevent over fitting problem. The proposed speech recognition method offers 98.2% accuracy.

59 citations


Cites methods from "Desktop phishing attack detection a..."

  • ...The performance of ISVM is tested with 160 speech signals spoken by 17 speakers, out of which 6 are native speakers and 11 are non-native speakers [20, 21]....

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Journal ArticleDOI
TL;DR: A fall detection algorithm that uses accelerometer and gyroscope sensor to predict the fall correctly and reduce the false positives and false negatives and increase the accuracy and can be used in real-time.
Abstract: Falls are considered as risky for the elderly people because it may affect the health of the people. So, in the recent years many elderly fall detection methods has been developed. In the present years many fall detection method had been developed but it uses only accelerometer sensor to detect the fall. It may fail in finding in the difference between actual fall and fall like activities such as sitting fast and jumping. In the proposed approach I have suggested a fall detection algorithm to detect the fall of elderly people. Daily human activities are divided into two parts such as static position and dynamic position. With the help of tri-axis accelerometer proposed fall detection can detect four kinds of positions such as falling front, front backward, jumping and sitting fastly. Acceleration and velocity is used to determine kind of fall. Our algorithm uses accelerometer and gyroscope sensor to predict the fall correctly and reduce the false positives and false negatives and increase the accuracy. In addition to that our method is made out of low cost and it can be used in real-time.

40 citations


Cites methods from "Desktop phishing attack detection a..."

  • ...Our solution divides the daily human activities into two broad categories such as static position and dynamic position, with the help of tri-axis accelerometer combined with the gyroscope the accuracy can be achieved where accelerometer is using acceleration and gyroscope uses velocity angle to detect the fall [6]....

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Journal ArticleDOI
TL;DR: Experimental results show that the proposed algorithm can preserve the edges and textures very well while weakening the noise can obtain better suppressed noise and enhances the objective of evaluations than other noise removal methods.
Abstract: Breast cancer is the second highest death causing disease in female. From the data it’s clear that one of the eight women is affected by breast cancer. The most effective way to detect the cancer is by using mammography technique and also it detects masses and abnormal conditions. The cluster shaped white spots on mammograms are used the cancer in the early stages. The importance of breast cancer detection to reduce different noises which are commonly found in mammogram images and provides better image quality. Here the multi-scale and the multi-directional analysis would produce optimal approximation and detail coefficients of Non-subsampled shearlet transform (NSST). Hence in this paper, the noisy image is amended into piecewise smooth function in different subbands of frequency. NSST coefficients are amended into information and noise related coefficients are noise is removed by using the adaptive threshold. To evaluate the performance of this proposed algorithm, Mean Square Error (MSE) and Peak Signal-to-Noise Ratio (PSNR) are used. Testing these experimental results show that the proposed algorithm can preserve the edges and textures very well while weakening the noise can obtain better suppressed noise and enhances the objective of evaluations than other noise removal methods.

17 citations


Additional excerpts

  • ...to wavelet shrinkage de-noising method [14]....

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Journal ArticleDOI
TL;DR: The bound unified power quality conditioner has been proposed to upgrade the power quality in wind energy frameworks and a nine-level inverter is planned using a capacitor decision design with a full-interface control converter, related to course.
Abstract: Internet of things (IoT) wind farm foundation is constructed using small wind turbines with cordless communication. In this work, the bound unified power quality conditioner has been proposed to upgrade the power quality in wind energy frameworks. The cluster computing is built a various downwind distances (between the turbines) can be examined with small reorganizing effort. Far away gathered information for an offline assessment of wind turbine power design, each turbine within the farm is furnished with an IoT foundation. This venture proposes another sun-based power era framework, which is made out of a dc/dc control converter in addition to another multilevel inverter with reduced number of switches. The dc to dc control converter incorporates are dc to dc SEPIC step-up(boost) converters are to change over the yield voltage of the sun controlled cell display into three self-ruling voltage sources with various associations. This proposed nine-level inverter is planned using a capacitor decision design with a full-interface control converter, related to course. The capacitor assurance design changes over the three yield wellsprings of dc–dc voltage control converters are using four-level dc voltage, and the full-associate control converter also changes over the four-level unidirectional dc into a nine-level bidirectional ac voltage. The new daylight based power period method creates a sine wave yield current to arrange with the used power and is energized into the system. The striking components of the new nine-level inverter are using nine semiconductor switches be used, and simply a solitary semiconductor switches are traded the high repeat at whatever point. A module is made and attempted to affirm the execution the proposed sun arranged power time system.

16 citations

Journal ArticleDOI
TL;DR: The proposed work is concerned in predicting the probability of CVD and high blood pressure in India, and the disease has been predicted with body mass index value; from the health reports of India, the pervasiveness ofCVD and HBP is identified and Bayesian model is used to find the pervasive based on the gender and the place of living.
Abstract: Increase in body mass index value is a serious health problem across the world. Humans with high body mass index value have the higher probability of getting the cardiovascular disease and high blood pressure. The proposed work is concerned in predicting the probability of CVD and high blood pressure in India. The disease has been predicted with body mass index value; from the health reports of India, the pervasiveness of CVD and HBP is identified. The demographic health survey 2016 of India is used in this work. Bayesian model is used to find the pervasiveness of CVD and HBP based on the gender and the place of living. Out of 432 articles studied, 34 articles suggested the pervasiveness of CVD and HBP. Pervasiveness of CVD increased (95% of interval) rapidly between 1992 and 2016 from 3.0% (0.3–5.7) to 16.4% (9.4–16.2) for men, and from 5.2% (2.3–8.6) to 15.4% (3.3–18.6) for women. Pervasiveness of high blood pressure increased rapidly between 1992 and 2016 from 11.0% (8.6–17.4) to 21.4% (19.4–23.6) for men and from 14.0% (4.3–16.7) to 20.4% (5.6–25.6) for women. The pervasiveness of CVD in 2030 is predicted as 24.6% (13.6–37.8), and pervasiveness of high blood pressure is predicted to be 21.7% (19.6–27.8). The annual average of pervasiveness of CVD is high for women in village areas, and pervasiveness of high blood pressure is found high for men in city regions. The cutoff point for pervasiveness of CVD for overall population is 23.02 kg/m2.

16 citations


Cites background or methods from "Desktop phishing attack detection a..."

  • ...The current method for predicting the disease is based on the international cut-point value considering Asian and European population, and it may fail in case of African population because their fat percentage is more compared to the Asian and European [20, 21]....

    [...]

  • ...The current method for predicting disease is based on the international cut-point value considering Asian and European populations, and it may fail in case of African population because their fat percentage is more compared to the Asian and European [42, 43]....

    [...]

  • ...25%; for additional information, refer to the DHL website [21]....

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References
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Proceedings ArticleDOI
06 Jul 2005
TL;DR: A new scheme is proposed, Dynamic Security Skins, that allows a remote web server to prove its identity in a way that is easy for a human user to verify and hard for an attacker to spoof.
Abstract: Phishing is a model problem for illustrating usability concerns of privacy and security because both system designers and attackers battle using user interfaces to guide (or misguide) users.We propose a new scheme, Dynamic Security Skins, that allows a remote web server to prove its identity in a way that is easy for a human user to verify and hard for an attacker to spoof. We describe the design of an extension to the Mozilla Firefox browser that implements this scheme.We present two novel interaction techniques to prevent spoofing. First, our browser extension provides a trusted window in the browser dedicated to username and password entry. We use a photographic image to create a trusted path between the user and this window to prevent spoofing of the window and of the text entry fields.Second, our scheme allows the remote server to generate a unique abstract image for each user and each transaction. This image creates a "skin" that automatically customizes the browser window or the user interface elements in the content of a remote web page. Our extension allows the user's browser to independently compute the image that it expects to receive from the server. To authenticate content from the server, the user can visually verify that the images match.We contrast our work with existing anti-phishing proposals. In contrast to other proposals, our scheme places a very low burden on the user in terms of effort, memory and time. To authenticate himself, the user has to recognize only one image and remember one low entropy password, no matter how many servers he wishes to interact with. To authenticate content from an authenticated server, the user only needs to perform one visual matching operation to compare two images. Furthermore, it places a high burden of effort on an attacker to spoof customized security indicators.

578 citations

Journal ArticleDOI
TL;DR: An effective approach to phishing Web page detection is proposed, which uses Earth mover's distance (EMD) to measure Web page visual similarity and train an EMD threshold vector for classifying a Web page as a phishing or a normal one.
Abstract: An effective approach to phishing Web page detection is proposed, which uses Earth mover's distance (EMD) to measure Web page visual similarity. We first convert the involved Web pages into low resolution images and then use color and coordinate features to represent the image signatures. We use EMD to calculate the signature distances of the images of the Web pages. We train an EMD threshold vector for classifying a Web page as a phishing or a normal one. Large-scale experiments with 10,281 suspected Web pages are carried out to show high classification precision, phishing recall, and applicable time performance for online enterprise solution. We also compare our method with two others to manifest its advantage. We also built up a real system which is already used online and it has caught many real phishing cases

302 citations

01 Jan 2002
TL;DR: A prototype intelligent intrusion detection system that combines both anomaly based intrusion detection using fuzzy data mining techniques and misuse detection using traditional rule-based expert system techniques is developed.
Abstract: We are developing a prototype intelligent intrusion detection system (IIDS) to demonstrate the effectiveness of data mining techniques that utilize fuzzy logic and genetic algorithms. This system combines both anomaly based intrusion detection using fuzzy data mining techniques and misuse detection using traditional rule-based expert system techniques. The anomaly-based components are developed using fuzzy data mining techniques. They look for deviations from stored patterns of normal behavior. Genetic algorithms are used to tune the fuzzy membership functions and to select an appropriate set of features. The misuse detection components look for previously described patterns of behavior that are likely to indicate an intrusion. Both network traffic and system audit data are used as inputs for both components.

265 citations

Proceedings ArticleDOI
11 Dec 2006
TL;DR: The idea is to examine the anomalies in Web pages, in particular, the discrepancy between a Web site's identity and its structural features and HTTP transactions, which demands neither user expertise nor prior knowledge of the Web site.
Abstract: Many anti-phishing schemes have recently been proposed in literature. Despite all those efforts, the threat of phishing attacks is not mitigated. One of the main reasons is that phishing attackers have the adaptability to change their tactics with little cost. In this paper, we propose a novel approach, which is independent of any specific phishing implementation. Our idea is to examine the anomalies in web pages, in particular, the discrepancy between a web site?s identity and its structural features and HTTP transactions. It demands neither user expertise nor prior knowledge of the website. The evasion of our phishing detection entails high cost to the adversary. As shown by the experiments, our phishing detector functions with low miss rate and low false-positive rate.

217 citations

Journal ArticleDOI
TL;DR: The authors' proposed antiphishing strategy uses visual characteristics to identify potential phishing sites and measure suspicious pages similarity to actual sites registered with the SiteWatcher system.
Abstract: The authors' proposed antiphishing strategy uses visual characteristics to identify potential phishing sites and measure suspicious pages similarity to actual sites registered with the system. The first of two sequential processes in the SiteWatcher system runs on local email servers and monitors emails for keywords and suspicious URLs. The second process then compares the potential phishing pages against actual pages and assesses visual similarities between them in terms of key regions, page layouts, and overall styles. The approach is designed to be part of an enterprise antiphishing solution.

201 citations