Evolving IoT honeypots
- Authors: Genov, Todor Stanislavov
- Date: 2022-10-14
- Subjects: Internet of things , Malware (Computer software) , QEMU , Honeypot , Cowrie
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/362819 , vital:65365
- Description: The Internet of Things (IoT) is the emerging world where arbitrary objects from our everyday lives gain basic computational and networking capabilities to become part of the Internet. Researchers are estimating between 25 and 35 billion devices will be part of Internet by 2022. Unlike conventional computers where one hardware platform (Intel x86) and three operating systems (Windows, Linux and OS X) dominate the market, the IoT landscape is far more heterogeneous. To meet the growth demand the number of The System-on-Chip (SoC) manufacturers has seen a corresponding exponential growth making embedded platforms based on ARM, MIPS or SH4 processors abundant. The pursuit for market share is further leading to a price war and cost-cutting ultimately resulting in cheap systems with limited hardware resources and capabilities. The frugality of IoT hardware has a domino effect. Due to resource constraints vendors are packaging devices with custom, stripped-down Linux-based firmwares optimized for performing the device’s primary function. Device management, monitoring and security features are by and far absent from IoT devices. This created an asymmetry favouring attackers and disadvantaging defenders. This research sets out to reduce the opacity and identify a viable strategy, tactics and tooling for gaining insight into the IoT threat landscape by leveraging honeypots to build and deploy an evolving world-wide Observatory, based on cloud platforms, to help with studying attacker behaviour and collecting IoT malware samples. The research produces useful tools and techniques for identifying behavioural differences between Medium-Interaction honeypots and real devices by replaying interactive attacker sessions collected from the Honeypot Network. The behavioural delta is used to evolve the Honeypot Network and improve its collection capabilities. Positive results are obtained with respect to effectiveness of the above technique. Findings by other researchers in the field are also replicated. The complete dataset and source code used for this research is made publicly available on the Open Science Framework website at https://osf.io/vkcrn/. , Thesis (MSc) -- Faculty of Science, Computer Science, 2022
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- Authors: Genov, Todor Stanislavov
- Date: 2022-10-14
- Subjects: Internet of things , Malware (Computer software) , QEMU , Honeypot , Cowrie
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/362819 , vital:65365
- Description: The Internet of Things (IoT) is the emerging world where arbitrary objects from our everyday lives gain basic computational and networking capabilities to become part of the Internet. Researchers are estimating between 25 and 35 billion devices will be part of Internet by 2022. Unlike conventional computers where one hardware platform (Intel x86) and three operating systems (Windows, Linux and OS X) dominate the market, the IoT landscape is far more heterogeneous. To meet the growth demand the number of The System-on-Chip (SoC) manufacturers has seen a corresponding exponential growth making embedded platforms based on ARM, MIPS or SH4 processors abundant. The pursuit for market share is further leading to a price war and cost-cutting ultimately resulting in cheap systems with limited hardware resources and capabilities. The frugality of IoT hardware has a domino effect. Due to resource constraints vendors are packaging devices with custom, stripped-down Linux-based firmwares optimized for performing the device’s primary function. Device management, monitoring and security features are by and far absent from IoT devices. This created an asymmetry favouring attackers and disadvantaging defenders. This research sets out to reduce the opacity and identify a viable strategy, tactics and tooling for gaining insight into the IoT threat landscape by leveraging honeypots to build and deploy an evolving world-wide Observatory, based on cloud platforms, to help with studying attacker behaviour and collecting IoT malware samples. The research produces useful tools and techniques for identifying behavioural differences between Medium-Interaction honeypots and real devices by replaying interactive attacker sessions collected from the Honeypot Network. The behavioural delta is used to evolve the Honeypot Network and improve its collection capabilities. Positive results are obtained with respect to effectiveness of the above technique. Findings by other researchers in the field are also replicated. The complete dataset and source code used for this research is made publicly available on the Open Science Framework website at https://osf.io/vkcrn/. , Thesis (MSc) -- Faculty of Science, Computer Science, 2022
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Peer-to-peer energy trading system using IoT and a low-computation blockchain network
- Authors: Ncube, Tyron
- Date: 2021-10-29
- Subjects: Blockchains (Databases) , Internet of things , Renewable energy sources , Smart power grids , Peer-to-peer architecture (Computer networks) , Energy trading system
- Language: English
- Type: Master's theses , text
- Identifier: http://hdl.handle.net/10962/192119 , vital:45197
- Description: The use of renewable energy is increasing every year as it is seen as a viable and sustain- able long-term alternative to fossil-based sources of power. Emerging technologies are being merged with existing renewable energy systems to address some of the challenges associated with renewable energy, such as reliability and limited storage facilities for the generated energy. The Internet of Things (IoT) has made it possible for consumers to make money by selling off excess energy back to the utility company through smart grids that allow bi-directional communication between the consumer and the utility company. The major drawback of this is that the utility company still plays a central role in this setup as they are the only buyer of this excess energy generated from renewable energy sources. This research intends to use blockchain technology by leveraging its decentralized architecture to enable other individuals to be able to purchase this excess energy. Blockchain technology is first explained in detail, and its main features, such as consensus mechanisms, are examined. This evaluation of blockchain technology gives rise to some design questions that are taken into consideration to create a low-energy, low-computation Ethereum-based blockchain network that is the foundation for a peer-to-peer energy trading system. The peer-to-peer energy trading system makes use of smart meters to collect data about energy usage and gives users a web-based interface where they can transact with each other. A smart contract is also designed to facilitate payments for transactions. Lastly, the system is tested by carrying out transactions and transferring energy from one node in the system to another. , Thesis (MSc) -- Faculty of Science, Computer Science, 2021
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- Authors: Ncube, Tyron
- Date: 2021-10-29
- Subjects: Blockchains (Databases) , Internet of things , Renewable energy sources , Smart power grids , Peer-to-peer architecture (Computer networks) , Energy trading system
- Language: English
- Type: Master's theses , text
- Identifier: http://hdl.handle.net/10962/192119 , vital:45197
- Description: The use of renewable energy is increasing every year as it is seen as a viable and sustain- able long-term alternative to fossil-based sources of power. Emerging technologies are being merged with existing renewable energy systems to address some of the challenges associated with renewable energy, such as reliability and limited storage facilities for the generated energy. The Internet of Things (IoT) has made it possible for consumers to make money by selling off excess energy back to the utility company through smart grids that allow bi-directional communication between the consumer and the utility company. The major drawback of this is that the utility company still plays a central role in this setup as they are the only buyer of this excess energy generated from renewable energy sources. This research intends to use blockchain technology by leveraging its decentralized architecture to enable other individuals to be able to purchase this excess energy. Blockchain technology is first explained in detail, and its main features, such as consensus mechanisms, are examined. This evaluation of blockchain technology gives rise to some design questions that are taken into consideration to create a low-energy, low-computation Ethereum-based blockchain network that is the foundation for a peer-to-peer energy trading system. The peer-to-peer energy trading system makes use of smart meters to collect data about energy usage and gives users a web-based interface where they can transact with each other. A smart contract is also designed to facilitate payments for transactions. Lastly, the system is tested by carrying out transactions and transferring energy from one node in the system to another. , Thesis (MSc) -- Faculty of Science, Computer Science, 2021
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Building the field component of a smart irrigation system: A detailed experience of a computer science graduate
- Authors: Pipile, Yamnkelani Yonela
- Date: 2021-10
- Subjects: Irrigation efficiency Computer-aided design South Africa , Irrigation projects Computer-aided design South Africa , Internet of things , Machine-to-machine communications , Smart water grids South Africa , Raspberry Pi (Computer) , Arduino (Programmable controller) , ZigBee , MQTT (MQ Telemetry Transport) , MQTT-SN , XBee
- Language: English
- Type: Master's theses , text
- Identifier: http://hdl.handle.net/10962/191814 , vital:45167
- Description: South Africa is a semi-arid area with an average annual rainfall of approximately 450mm, 60 per cent of which goes towards irrigation. Current irrigation systems generally apply water in a uniform manner across a field, which is both inefficient and can kill the plants. The Internet of Things (IoT), an emerging technology involving the utilization of sensors and actuators to build complex feedback systems, present an opportunity to build a smart irrigation solution. This research project illustrates the development of the field components of a water monitoring system using off the shelf and inexpensive components, exploring at the same time how easy or difficult it would be for a general Computer Science graduate to use hardware components and associated tools within the IoT area. The problem was initially broken down through a classical top-down process, in order to identify the components such as micro-computers, micro- controllers, sensors and network connections, that would be needed to build the solution. I then selected the Raspberry Pi 3, the Arduino Arduino Uno, the MH-Sensor-Series hygrometer, the MQTT messaging protocol, and the ZigBee communication protocol as implemented in the XBee S2C. Once the components were identified, the work followed a bottom-up approach: I studied the components in isolation and relative to each other, through a structured series of experiments, with each experiment addressing a specific component and examining how easy was to use the component. While each experiment allowed the author to acquire and deepen her understanding of each component, and progressively built a more sophisticated prototype, towards the complete solution. I found the vast majority of the identified components and tools to be easy to use, well documented, and most importantly, mature for consumption by our target user, until I encountered the MQTT-SN (MQTT-Sensor Network) implementation, not as mature as the rest. This resulted in us designing and implementing a light-weight, general ZigBee/MQTT gateway, named “yoGa” (Yonella's Gateway) from the author. At the end of the research, I was able to build the field components of a smart irrigation system using the selected tools, including the yoGa gateway, proving practically that a Computer Science graduate from a South African University can become productive in the emerging IoT area. , Thesis (MSc) -- Faculty of Science, Computer Science, 2021
- Full Text:
- Authors: Pipile, Yamnkelani Yonela
- Date: 2021-10
- Subjects: Irrigation efficiency Computer-aided design South Africa , Irrigation projects Computer-aided design South Africa , Internet of things , Machine-to-machine communications , Smart water grids South Africa , Raspberry Pi (Computer) , Arduino (Programmable controller) , ZigBee , MQTT (MQ Telemetry Transport) , MQTT-SN , XBee
- Language: English
- Type: Master's theses , text
- Identifier: http://hdl.handle.net/10962/191814 , vital:45167
- Description: South Africa is a semi-arid area with an average annual rainfall of approximately 450mm, 60 per cent of which goes towards irrigation. Current irrigation systems generally apply water in a uniform manner across a field, which is both inefficient and can kill the plants. The Internet of Things (IoT), an emerging technology involving the utilization of sensors and actuators to build complex feedback systems, present an opportunity to build a smart irrigation solution. This research project illustrates the development of the field components of a water monitoring system using off the shelf and inexpensive components, exploring at the same time how easy or difficult it would be for a general Computer Science graduate to use hardware components and associated tools within the IoT area. The problem was initially broken down through a classical top-down process, in order to identify the components such as micro-computers, micro- controllers, sensors and network connections, that would be needed to build the solution. I then selected the Raspberry Pi 3, the Arduino Arduino Uno, the MH-Sensor-Series hygrometer, the MQTT messaging protocol, and the ZigBee communication protocol as implemented in the XBee S2C. Once the components were identified, the work followed a bottom-up approach: I studied the components in isolation and relative to each other, through a structured series of experiments, with each experiment addressing a specific component and examining how easy was to use the component. While each experiment allowed the author to acquire and deepen her understanding of each component, and progressively built a more sophisticated prototype, towards the complete solution. I found the vast majority of the identified components and tools to be easy to use, well documented, and most importantly, mature for consumption by our target user, until I encountered the MQTT-SN (MQTT-Sensor Network) implementation, not as mature as the rest. This resulted in us designing and implementing a light-weight, general ZigBee/MQTT gateway, named “yoGa” (Yonella's Gateway) from the author. At the end of the research, I was able to build the field components of a smart irrigation system using the selected tools, including the yoGa gateway, proving practically that a Computer Science graduate from a South African University can become productive in the emerging IoT area. , Thesis (MSc) -- Faculty of Science, Computer Science, 2021
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