title: Workshop on Smart Sensors - Instrumentation and Measurement: Program

authors: Künnemeyer, Rainer

abstract: On 18-19 February, the School of Engineering successfully ran a two-day workshop on Smart Sensors - Instrumentation and Measurement.  Associate Professor Rainer Künnemeyer organised the event on behalf of the IEEE Instrumentation and Measurement Society, New Zealand Chapter.  Over 60 delegates attended and appreciated the 34 presentations which covered a wide range of topics related to sensors, sensor networks and instrumentation.  There was substantial interest and support from local industry and crown research institutes.

text: Workshop on Smart Sensors - Instrumentation and Measurement: Program On 18-19 February, the School of Engineering successfully ran a two-day workshop on Smart Sensors - Instrumentation and Measurement.  Associate Professor Rainer Künnemeyer organised the event on behalf of the IEEE Instrumentation and Measurement Society, New Zealand Chapter.  Over 60 delegates attended and appreciated the 34 presentations which covered a wide range of topics related to sensors, sensor networks and instrumentation.  There was substantial interest and support from local industry and crown research institutes.

year: 2013

title: Effectiveness of entropy-based features in high-and low-intensity DDoS attacks detection

authors: Koay, Abigail

subjects: computer science

abstract: DDoS attack detection using entropy-based features in network traffic has become a popular approach among researchers in the last five years. The use of traffic distribution features constructed using entropy measures has been proposed as a better approach to detect Distributed Denial of Service (DDoS) attacks compared to conventional volumetric methods, but it still lacks in the generality of detecting various intensity DDoS attacks accurately. In this paper, we focus on identifying effective entropy-based features to detect both high- and low-intensity DDoS attacks by exploring the effectiveness of entropy-based features in distinguishing the attack from normal traffic patterns. We hypothesise that using different entropy measures, window sizes, and entropy-based features may affect the accuracy of detecting DDoS attacks. This means that certain entropy measures, window sizes, and entropy-based features may reveal attack traffic amongst normal traffic better than the others. Our experimental results show that using Shannon, Tsallis and Zhou entropy measures can achieve a clearer distinction between DDoS attack traffic and normal traffic than Rényi entropy. In addition, the window size setting used in entropy construction has minimal influence in differentiating between DDoS attack traffic and normal traffic. The result of the effectiveness ranking shows that the commonly used features are less effective than other features extracted from traffic headers.

text: Effectiveness of entropy-based features in high-and low-intensity DDoS attacks detection DDoS attack detection using entropy-based features in network traffic has become a popular approach among researchers in the last five years. The use of traffic distribution features constructed using entropy measures has been proposed as a better approach to detect Distributed Denial of Service (DDoS) attacks compared to conventional volumetric methods, but it still lacks in the generality of detecting various intensity DDoS attacks accurately. In this paper, we focus on identifying effective entropy-based features to detect both high- and low-intensity DDoS attacks by exploring the effectiveness of entropy-based features in distinguishing the attack from normal traffic patterns. We hypothesise that using different entropy measures, window sizes, and entropy-based features may affect the accuracy of detecting DDoS attacks. This means that certain entropy measures, window sizes, and entropy-based features may reveal attack traffic amongst normal traffic better than the others. Our experimental results show that using Shannon, Tsallis and Zhou entropy measures can achieve a clearer distinction between DDoS attack traffic and normal traffic than Rényi entropy. In addition, the window size setting used in entropy construction has minimal influence in differentiating between DDoS attack traffic and normal traffic. The result of the effectiveness ranking shows that the commonly used features are less effective than other features extracted from traffic headers.

year: 2019

title: Everyday experiences of racism: Suppressing Māori cultural expressions in mental health

authors: Southey, Kim Marie

abstract: Tēnā kautau i runga i ngā tini āhuatanga o te wā.

This publication has been produced as part of the He Kokonga Ngākau Fellowships, an initiative of Te Atawhai o Te Ao that seeks to support and contribute to our research projects, and grow Māori research capability that promotes Kaupapa Māori research. These fellowships have been established to support Māori postgraduate students, practitioners, community researchers, and writers in their writing on kaupapa that have relevance to our organisation and wider community.

Dr Kim Southey (Ngāti Porou, Ngāti Kuia) draws on her doctoral research on re-presenting Māori and Indigenous understandings of being, and deconstructing the notion of mental illness. This
publication focuses on how Māori and Indigenous expressions within the mental (and wider) health system are suppressed and restricted by a dominant (western) worldview. Dr Southey posits that the western insistence on representing things in the world through rational, logical explanations impacts on Māori cultural understandings, limiting how we can express ourselves. This is viewed by Dr Southey as a form of institutional racism.

text: Everyday experiences of racism: Suppressing Māori cultural expressions in mental health Tēnā kautau i runga i ngā tini āhuatanga o te wā.

This publication has been produced as part of the He Kokonga Ngākau Fellowships, an initiative of Te Atawhai o Te Ao that seeks to support and contribute to our research projects, and grow Māori research capability that promotes Kaupapa Māori research. These fellowships have been established to support Māori postgraduate students, practitioners, community researchers, and writers in their writing on kaupapa that have relevance to our organisation and wider community.

Dr Kim Southey (Ngāti Porou, Ngāti Kuia) draws on her doctoral research on re-presenting Māori and Indigenous understandings of being, and deconstructing the notion of mental illness. This
publication focuses on how Māori and Indigenous expressions within the mental (and wider) health system are suppressed and restricted by a dominant (western) worldview. Dr Southey posits that the western insistence on representing things in the world through rational, logical explanations impacts on Māori cultural understandings, limiting how we can express ourselves. This is viewed by Dr Southey as a form of institutional racism.

year: 2022