De-identification of personal information for use in software testing to ensure compliance with the Protection of Personal Information Act
- Authors: Mark, Stephen John
- Date: 2018
- Subjects: Data processing , Information technology -- Security measures , Computer security -- South Africa , Data protection -- Law and legislation -- South Africa , Data encryption (Computer science) , Python (Computer program language) , SQL (Computer program language) , Protection of Personal Information Act (POPI)
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/63888 , vital:28503
- Description: Encryption of Personally Identifiable Information stored in a Structured Query Language Database has been difficult for a long time. This is owing to block-cipher encryption algorithms changing the length and type of the input data when encrypted, which cannot subsequently be stored in the database without altering its structure. As the enactment of the South African Protection of Personal Information Act, No 4 of 2013 (POPI), was set in motion with the appointment of the Information Regulators Office in December 2016, South African companies are intensely focused on implementing compliance strategies and processes. The legislation, promulgated in 2013, encompasses the processing and storage of personally identifiable information (PII), ensuring that corporations act responsibly when collecting, storing and using individuals’ personal data. The Act comprises eight broad conditions that will become legislation once the new Information Regulator’s office is fully equipped to carry out their duties. POPI requires that individuals’ data should be kept confidential from all but those who specifically have permission to access the data. This means that not all members of IT teams should have access to the data unless it has been de-identified. This study tests an implementation of the Fixed Feistel 1 algorithm from the National Institute of Standards and Technology (NIST) “Special Publication 800-38G: Recommendation for Block Cipher Modes of Operation : Methods for Format-Preserving Encryption” using the LibFFX Python library. The Python scripting language was used for the experiments. The research shows that it is indeed possible to encrypt data in a Structured Query Language Database without changing the database schema using the new Format-Preserving encryption technique from NIST800-38G. Quality Assurance software testers can then run their full set of tests on the encrypted database. There is no reduction of encryption strength when using the FF1 encryption technique, compared to the underlying AES-128 encryption algorithm. It further shows that the utility of the data is not lost once it is encrypted.
- Full Text:
- Date Issued: 2018
- Authors: Mark, Stephen John
- Date: 2018
- Subjects: Data processing , Information technology -- Security measures , Computer security -- South Africa , Data protection -- Law and legislation -- South Africa , Data encryption (Computer science) , Python (Computer program language) , SQL (Computer program language) , Protection of Personal Information Act (POPI)
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/63888 , vital:28503
- Description: Encryption of Personally Identifiable Information stored in a Structured Query Language Database has been difficult for a long time. This is owing to block-cipher encryption algorithms changing the length and type of the input data when encrypted, which cannot subsequently be stored in the database without altering its structure. As the enactment of the South African Protection of Personal Information Act, No 4 of 2013 (POPI), was set in motion with the appointment of the Information Regulators Office in December 2016, South African companies are intensely focused on implementing compliance strategies and processes. The legislation, promulgated in 2013, encompasses the processing and storage of personally identifiable information (PII), ensuring that corporations act responsibly when collecting, storing and using individuals’ personal data. The Act comprises eight broad conditions that will become legislation once the new Information Regulator’s office is fully equipped to carry out their duties. POPI requires that individuals’ data should be kept confidential from all but those who specifically have permission to access the data. This means that not all members of IT teams should have access to the data unless it has been de-identified. This study tests an implementation of the Fixed Feistel 1 algorithm from the National Institute of Standards and Technology (NIST) “Special Publication 800-38G: Recommendation for Block Cipher Modes of Operation : Methods for Format-Preserving Encryption” using the LibFFX Python library. The Python scripting language was used for the experiments. The research shows that it is indeed possible to encrypt data in a Structured Query Language Database without changing the database schema using the new Format-Preserving encryption technique from NIST800-38G. Quality Assurance software testers can then run their full set of tests on the encrypted database. There is no reduction of encryption strength when using the FF1 encryption technique, compared to the underlying AES-128 encryption algorithm. It further shows that the utility of the data is not lost once it is encrypted.
- Full Text:
- Date Issued: 2018
NetwIOC: a framework for the automated generation of network-based IOCS for malware information sharing and defence
- Authors: Rudman, Lauren Lynne
- Date: 2018
- Subjects: Malware (Computer software) , Computer networks Security measures , Computer security , Python (Computer program language)
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/60639 , vital:27809
- Description: With the substantial number of new malware variants found each day, it is useful to have an efficient way to retrieve Indicators of Compromise (IOCs) from the malware in a format suitable for sharing and detection. In the past, these indicators were manually created after inspection of binary samples and network traffic. The Cuckoo Sandbox, is an existing dynamic malware analysis system which meets the requirements for the proposed framework and was extended by adding a few custom modules. This research explored a way to automate the generation of detailed network-based IOCs in a popular format which can be used for sharing. This was done through careful filtering and analysis of the PCAP hie generated by the sandbox, and placing these values into the correct type of STIX objects using Python, Through several evaluations, analysis of what type of network traffic can be expected for the creation of IOCs was conducted, including a brief ease study that examined the effect of analysis time on the number of IOCs created. Using the automatically generated IOCs to create defence and detection mechanisms for the network was evaluated and proved successful, A proof of concept sharing platform developed for the STIX IOCs is showcased at the end of the research.
- Full Text:
- Date Issued: 2018
- Authors: Rudman, Lauren Lynne
- Date: 2018
- Subjects: Malware (Computer software) , Computer networks Security measures , Computer security , Python (Computer program language)
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/60639 , vital:27809
- Description: With the substantial number of new malware variants found each day, it is useful to have an efficient way to retrieve Indicators of Compromise (IOCs) from the malware in a format suitable for sharing and detection. In the past, these indicators were manually created after inspection of binary samples and network traffic. The Cuckoo Sandbox, is an existing dynamic malware analysis system which meets the requirements for the proposed framework and was extended by adding a few custom modules. This research explored a way to automate the generation of detailed network-based IOCs in a popular format which can be used for sharing. This was done through careful filtering and analysis of the PCAP hie generated by the sandbox, and placing these values into the correct type of STIX objects using Python, Through several evaluations, analysis of what type of network traffic can be expected for the creation of IOCs was conducted, including a brief ease study that examined the effect of analysis time on the number of IOCs created. Using the automatically generated IOCs to create defence and detection mechanisms for the network was evaluated and proved successful, A proof of concept sharing platform developed for the STIX IOCs is showcased at the end of the research.
- Full Text:
- Date Issued: 2018
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