*Personal data
Please read each of the paragraphs carefully and select only one of the available options, by check one box.
Age: ☐ under 30 years old ☐ 30 - less than 40 ☐ 40 - less than 50 ☐ 50 years and over Gender: ☐ Male ☐ Female Marital status: ☐ Married ☐ Unmarried ☐ Absolute ☐ Widower Educational level: ☐ High School ☐ Bachelor ☐ Master ☐ PhD
City: --------------------------------
Police Rank: ☐ Lieutenant ☐ First Lieutenant ☐ Captain ☐ Major ☐ Lieutenant-Colonel ☐ Colonel ☐ Brigadier General ☐ Other ............. Service length in years: ☐ Less than five years ☐ 5 - less than 10 ☐ 10 - less than 15 ☐ 15 - less than 20 ☐ 20 years and over Nature of the current job: ☐ Administrative ☐ Field ☐ Investigation ☐ Other ................. Investigate cyberspace issues: ☐ Did not investigate ☐ A case - less than five cases ☐ Five or more cases The period of the training course on cybercrime per week: ☐ None ☐ Less than 5 weeks ☐ 5 - Less than 10 ☐ 10 or more weeks Do you read print and electronic publications (cybercrime): ☐ Yes ☐ No English reading proficiency: ☐ Yes ☐ No Years computer use: ☐ None ☐ Less than 3 ☐ 3 - Less than 6 ☐ 6 - less than 10 ☐ 10 or more Computer hours using per week: ☐ None ☐ Less than 5 ☐ 5 - Less than 10 ☐ 10 - less than 15 ☐ 15 - less than 20 ☐ 20 or more hours Years of internet use: ☐ None ☐ Less than one year ☐ One year - less than three years ☐ Three years - less than four years ☐ years or more Average weekly internet usage hours: ☐ None ☐ Less than 5 ☐ 5 - Less than 10 ☐ 10 - less than 15 ☐ 15 - less than 20 ☐ 20 or more hours | |||||||
*Checklist axes | |||||||
s. | Cyber crime | Responses (knowledge score) | |||||
Excellent (5) | Very Good (4) | Good (3) | Poor (2) | Very Poor (1) | |||
First axis: the level of familiarity with the tools and methods used in committing cybercrime | |||||||
1 | Computer virus |
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2 | Trajan Hoarse |
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3 | Password Crackers |
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4 | Network Scanners |
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5 | Email Flooders |
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6 | Key Loggers |
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7 | Packet Sniffers |
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8 | IP Spoofing |
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9 | War dialers |
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10 | Credit Card Numbers Generators |
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11 | Anonymity |
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12 | Social Engineering |
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Second axis: level of awareness of some aspects related to cybercrime. | |||||||
1 | Some of the famous cases of these crimes. |
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2 | Current reality of these crimes. |
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3 | Categories of perpetrators of these crimes and the distinguishing characteristics of each category. |
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4 | Future trends of these crimes. |
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5 | On-line sources of information on these crimes. |
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6 | Dimensions of international prosecution and joint cooperation to combat these crimes. |
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7 | Legislation and laws relating to these crimes |
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Third axis: level of knowledge of cybercrime and the characteristics that distinguish each crime. | |||||||
s. | Cyber crime | Responses (knowledge score) | |||||
Excellent (5) | Very Good (4) | Good (3) | Poor (2) | Very Poor (1) | |||
1 | Spreading Computer Viruses and Trojans |
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2 | Denial of Service |
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3 | Distributed Denial of Service |
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4 | E-mail Hacking |
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5 | E-mail Flooding |
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6 | E-mail Forgery |
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7 | Unauthorized use of devices and networks |
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8 | Hacking devices, networks and websites |
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9 | Computer data sabotage |
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10 | Publishing information that violates laws and regulations |
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11 | Data Theft |
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12 | Software Piracy |
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13 | Intercepting and eavesdrop on computer communications |
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14 | Fraud and Embezzlement |
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15 | Manipulation of telecommunications network systems |
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16 | Online Gambling |
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17 | Cyber-Laundering |
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18 | Identity Theft |
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19 | Cyber Espionage |
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20 | Cyber Terrorism |
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Fourth axis: level of familiarity with some programs and tools used in the investigation of cybercrimes. | |||||||
1 | File compression/decoding applications include: (WinZip, WinRAR). |
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2 | Video and image processing and analysis software |
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3 | Digital forensic software such as: ProDiscover and CAINE (Computer Aided INvestigative Environment) |
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4 | Command line forensic tools |
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5 | Digital forensic hardware tools |
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6 | Tasks performed by Digital forensic tools such as: - Acquisition - Validation and verification - Extraction - Reconstruction - Reporting |
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7 | Evaluating digital forensic tool needs |
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s. | Cyber crime | Responses (knowledge score) | |||||
Excellent (5) | Very Good (4) | Good (3) | Poor (2) | Very Poor (1) | |||
8 | Digital forensic software tools |
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9 | Mobile device forensics |
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10 | Desktop forensics |
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11 | Email forensics |
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12 | Smartphone analysis |
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13 | Cloud analysis |
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14 | IoT forensics |
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15 | Triage and visualization |
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16 | File analysis tools |
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17 | Registry analysis tools |
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18 | Internet analysis tools |
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19 | Email analysis tools |
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20 | Mobile devices analysis tools |
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21 | Network forensics tools |
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22 | Database forensics tools |
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23 | Computer Forensics Methodology |
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24 | Applications of Computer Forensics |
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