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Sprint Review / Retrospective Week 4

Senior Innovation Project III: Analysis and Patent

Professor: Todd Spencer
By James Raygor

 My Senior Innovation Project

 Status Report

 Inquiry

 The Curve

 Deals with free Facebook user data

 Can lead to compromises in security

 What is PassFinder and how does it work

 Started as a Web Scraper concept

 The journey at becoming Facebook App

 Learning to work with Graph API

 Generic program operational

 Scraping data is nothing new

 Data on Facebook is free

 The Innovation is the process

 Teach people about personal information
security

 Teach companies that security doesn't stop at
the doorstep

 How human nature can be used against the
human

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Data is more defenseless than any time in recent memory and each mechanical development raises new security danger that requires new security arrangements. web kill tool is directed to assess the security of an IT framework by securely uncovering its weaknesses. The performance of an application is measured based on the number of false negatives and false positives. Testing technique that is highly automated, which covers several boundary cases by means of invalid data as the application input to make sure that exploitable vulnerabilities are absent. Deepesh Seth | Ms. N. Priya "Vulnerability Assessment and Penetration Testing using Webkill" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-1 , December 2020, URL: https://www.ijtsrd.com/papers/ijtsrd37919.pdf Paper URL : https://www.ijtsrd.com/computer-science/computer-security/37919/vulnerability-assessment-and-penetration-testing-using-webkill/deepesh-seth

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We describe our experience gained while exploring practical security and privacy problems in a real-world, large- scale social network (i.e., Facebook), and summarize our conclu- sions in a series of “lessons learned”. We first conclude that it is better to adequately describe the potential ethical concerns from the very beginning and plan ahead the institutional review board (IRB) request. Even though sometimes optional, the IRB approval is a valuable point from the reviewer’s perspective. Another aspect that needs planning is getting in touch with the online social network security team, which takes a substantial amount of time. With their support, “bending the rules” (e.g., using scrapers) when the experimental goals require so, is easier. Clearly, in cases where critical technical vulnerabilities are found during the research, the general recommendations for responsible disclosure should be followed. Gaining the audience’s engagement and trust was essential to the success of our user study. Participants felt more comfortable when subscribing to our experiments, and also responsibly reported bugs and glitches. We did not observe the same behavior in crowd-sourcing workers, who were instead more interested in obtaining their rewards. On a related point, our experience suggests that crowd sourcing should not be used alone: Setting up tasks is more time consuming than it seems, and researchers must insert some sentinel checks to ensure that workers are not submitting random answers. From a logistics point of view, we learned that having at least a high-level plan of the experiments pays back, especially when the IRB requires a detailed description of the work and the data to be collected. However, over planning can be dangerous because the measurement goals can change dynamically. From a technical point of view, partially connected to the logistics remarks, having a complex and large data-gathering and analysis framework may be counterproductive in terms of set-up and management overhead. From our experience we suggest to choose simple technologies that scale up if needed but, more importantly, can scale down. For example, launching a quick query should be straightforward, and the frameworks should not impose too much overhead for formulating it. We conclude with a series of practical recommendations on how to successfully collect data from online social networks (e.g., using techniques for network multi presence, mimicking user behavior, and other crawling “tricks”’) and avoid abusing the online service, while gathering the data required by the experiments.

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Academic dishonesty has been a growing concern in e-learning environment due to the fact that eexamination takes place under supervised and unsupervised learning environment despite its huge advantages. The e-examination environment has faced various security breaches such as academic dishonesty (impersonation), identity theft, unauthorised access and illegal assistance as a result of inefficient measures employed. Hence, an efficient framework which will aid the monitoring of the eexamination is needed. This paper reviews the process of mining multimedia data and propose a framework for monitoring the e-examination environment in order to extract images and audio features. The framework has four major phases: data pre-processing, mining, association and post processing. The pre-processing phases carries out the extraction and transformation of multimedia data features, the mining phase does the classification and clustering of these features, the association does pattern matching while the post processing carries out the knowledge interpretation and reporting. The approach presented in this study will allow for efficient and accurate monitoring of e-examination environment which will help provide adequate security and reduce unethical behaviour in e-examination environment.

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Rough draftfinal

1. Sprint Review / Retrospective Week 4 Senior Innovation Project III: Analysis and Patent Professor: Todd Spencer By James Raygor

2.  My Senior Innovation Project  Status Report  Inquiry  The Curve

3.  Deals with free Facebook user data  Can lead to compromises in security  What is PassFinder and how does it work

4.  Started as a Web Scraper concept  The journey at becoming Facebook App  Learning to work with Graph API  Generic program operational

5.  Scraping data is nothing new  Data on Facebook is free  The Innovation is the process

6.  Teach people about personal information security  Teach companies that security doesn't stop at the doorstep  How human nature can be used against the human

Rough draftfinal

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Rough draftfinal