Difference between revisions of "ISSS608 2017-18 T3 Assign Pooja Manohar Sawant"
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− | <b><font size = 5; color="#FFFFFF"> | + | <b><font size = 5; color="#FFFFFF"> Detecting Suspicious Activities at Kasios International</font></b> |
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− | [[ISSS608_2017-18_T3_Assign_Pooja_Manohar_Sawant_Methodology_Dashboard_Design| <font color="#FFFFFF">METHODOLOGY AND | + | [[ISSS608_2017-18_T3_Assign_Pooja_Manohar_Sawant_Methodology_Dashboard_Design| <font color="#FFFFFF">METHODOLOGY AND ANALYSIS </font>]] |
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− | [[ISSS608_2017-18_T3_Assign_Pooja_Manohar_Sawant_Observations & Insights| <font color="#FFFFFF"> | + | [[ISSS608_2017-18_T3_Assign_Pooja_Manohar_Sawant_Observations & Insights| <font color="#FFFFFF">INSIGHTS AND CONCLUSION</font>]] |
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== VAST Challenge 2018 == | == VAST Challenge 2018 == | ||
− | VAST | + | [[Image:MC3_2018.jpg|300px||thumb|right|float|VAST 2018 - Mini-Challenge 3]] |
− | + | The IEEE Visual Analytics Science and Technology (VAST) Challenge is an annual contest designed to help researchers to understand how their software would be used in a novel analytic task and determine if their data transformations, visualizations, and interactions would be beneficial for particular analytic tasks. | |
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− | + | == Background == | |
+ | Mistford, a mid-size city, is located to the southwest of a large nature preserve. The city has a small industrial area with four light-manufacturing endeavors. Mitch Vogel was a post-doc student studying ornithology at Mistford College and had been discovering signs that the number of nesting pairs of the Rose-Crested Blue Pipit, a popular local bird due to its attractive plumage and pleasant songs, was decreasing. The decrease was so significant that even though Mitch Vogel left his work at Mistford College, he has not forgotten the Rose-Crested Blue Pipit. | ||
− | + | == Overview of Mini Challenge-3 == | |
+ | Soon after arriving at Sulev in Northern Europe, Mitch started to see the telltale signs of Methylosmolene damage at the nearby Panteleimon Aviary Sanctuary and heard from local bird watchers that populations of the Greater Eurasian Red-Throated Pipit have been affected, something similar to the Mistford bird sanctuary. There was one more similarity between these two cities - Kasios International, Inc. – a huge multinational conglomerate that has subsidiaries in both of these cities. Mitch was immediately suspicious that EuroKasios was contaminating the aviary Sanctuary and endangering the Greater Eurasian Red-Throated Pipit. Worse yet, he wondered if Kasios International may be contaminating pipit habitats around the world. Even though, Kasios International talked about their environmentally friendly practices and recent scientific research to find a replacement for Methylosmolene, Mitch was skeptical that the company had already halted production and use of Methylosmolene. Disappointed Mitch as he could not meet Kasios representatives, received an anonymous letter from someone who’s willing to help. A fellow pipit lover who works at Kasios International had gathered up a variety of company data and identified a suspicious group within the company. The data contains communication and procurement records for Kasios International over the past 2 1/2 years. Mitch wonders if the fate of the Eurasian Pipit lies somewhere in that data. Mitch intends to put this data together to see if the problems with Kasios are much larger than he initially suspected. | ||
− | + | == Questions == | |
− | # The insider has provided a list of purchases that might indicate illicit activity elsewhere in the company. Using the structure of the first group noted by the insider as a model can you find any other instances of suspicious activities in the company? Are there other groups that have structure and activity similar to this one? Who are they? Each of the suspicious purchases could be a starting point for your search. Provide examples of up to two other groups you find that appear suspicious and compare their structure with the structure of the first group. The structures should be presented as temporal not just structural (i.e., the sequence of events—A is followed by B one or two days later—will be important). | + | #Using the four large Kasios International data sets, combine the different sources to create a single picture of the company. Characterize changes in the company over time. According to the company’s communications and purchase habits, is the company growing? |
+ | #Combine the four data sources for group that the insider has identified as being suspicious and locate the group in the larger dataset. Determine if anyone else appears to be closely associated with this group. Highlight which employees are making suspicious purchases, according to the insider’s data. | ||
+ | #Using the combined group of suspected bad actors you created in question 2, show the interactions within the group over time. | ||
+ | ##Characterize the group’s organizational structure and show a full picture of communications within the group. | ||
+ | ##Does the group composition change during the course of their activities? | ||
+ | ##How do the group’s interactions change over time? | ||
+ | #The insider has provided a list of purchases that might indicate illicit activity elsewhere in the company. Using the structure of the first group noted by the insider as a model can you find any other instances of suspicious activities in the company? Are there other groups that have structure and activity similar to this one? Who are they? Each of the suspicious purchases could be a starting point for your search. Provide examples of up to two other groups you find that appear suspicious and compare their structure with the structure of the first group. The structures should be presented as temporal not just structural (i.e., the sequence of events—A is followed by B one or two days later—will be important). |
Latest revision as of 12:01, 12 July 2018
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VAST Challenge 2018
The IEEE Visual Analytics Science and Technology (VAST) Challenge is an annual contest designed to help researchers to understand how their software would be used in a novel analytic task and determine if their data transformations, visualizations, and interactions would be beneficial for particular analytic tasks.
Background
Mistford, a mid-size city, is located to the southwest of a large nature preserve. The city has a small industrial area with four light-manufacturing endeavors. Mitch Vogel was a post-doc student studying ornithology at Mistford College and had been discovering signs that the number of nesting pairs of the Rose-Crested Blue Pipit, a popular local bird due to its attractive plumage and pleasant songs, was decreasing. The decrease was so significant that even though Mitch Vogel left his work at Mistford College, he has not forgotten the Rose-Crested Blue Pipit.
Overview of Mini Challenge-3
Soon after arriving at Sulev in Northern Europe, Mitch started to see the telltale signs of Methylosmolene damage at the nearby Panteleimon Aviary Sanctuary and heard from local bird watchers that populations of the Greater Eurasian Red-Throated Pipit have been affected, something similar to the Mistford bird sanctuary. There was one more similarity between these two cities - Kasios International, Inc. – a huge multinational conglomerate that has subsidiaries in both of these cities. Mitch was immediately suspicious that EuroKasios was contaminating the aviary Sanctuary and endangering the Greater Eurasian Red-Throated Pipit. Worse yet, he wondered if Kasios International may be contaminating pipit habitats around the world. Even though, Kasios International talked about their environmentally friendly practices and recent scientific research to find a replacement for Methylosmolene, Mitch was skeptical that the company had already halted production and use of Methylosmolene. Disappointed Mitch as he could not meet Kasios representatives, received an anonymous letter from someone who’s willing to help. A fellow pipit lover who works at Kasios International had gathered up a variety of company data and identified a suspicious group within the company. The data contains communication and procurement records for Kasios International over the past 2 1/2 years. Mitch wonders if the fate of the Eurasian Pipit lies somewhere in that data. Mitch intends to put this data together to see if the problems with Kasios are much larger than he initially suspected.
Questions
- Using the four large Kasios International data sets, combine the different sources to create a single picture of the company. Characterize changes in the company over time. According to the company’s communications and purchase habits, is the company growing?
- Combine the four data sources for group that the insider has identified as being suspicious and locate the group in the larger dataset. Determine if anyone else appears to be closely associated with this group. Highlight which employees are making suspicious purchases, according to the insider’s data.
- Using the combined group of suspected bad actors you created in question 2, show the interactions within the group over time.
- Characterize the group’s organizational structure and show a full picture of communications within the group.
- Does the group composition change during the course of their activities?
- How do the group’s interactions change over time?
- The insider has provided a list of purchases that might indicate illicit activity elsewhere in the company. Using the structure of the first group noted by the insider as a model can you find any other instances of suspicious activities in the company? Are there other groups that have structure and activity similar to this one? Who are they? Each of the suspicious purchases could be a starting point for your search. Provide examples of up to two other groups you find that appear suspicious and compare their structure with the structure of the first group. The structures should be presented as temporal not just structural (i.e., the sequence of events—A is followed by B one or two days later—will be important).