Numerical encoding to tame SQL injection attacks.

Recent years have seen an astronomical rise in SQL Injection Attacks (SQLIAs) used to compromise the confidentiality, authentication and integrity of organisations’ databases. Intruders becoming smarter in obfuscating web requests to evade detection combined with increasing volumes of web traffic from the Internet of Things (IoT), cloud-hosted and on-premise business applications have made it evident that the existing approaches of mostly static signature lack the ability to cope with novel signatures. A SQLIA detection and prevention solution can be achieved through exploring an alternative bio-inspired supervised learning approach that uses input of labelled dataset of numerical attributes in classifying true positives and negatives. We present in this paper a Numerical Encoding to Tame SQLIA (NETSQLIA) that implements a proof of concept for scalable numerical encoding of features to a dataset attributes with labelled class obtained from deep web traffic analysis. In the numerical attributes encoding: the model leverages proxy in the interception and decryption of web traffic. The intercepted web requests are then assembled for front-end SQL parsing and pattern matching by applying traditional Non-Deterministic Finite Automaton (NFA). This paper is intended for a technique of numerical attributes extraction of any size primed as an input dataset to an Artificial Neural Network (ANN) and statistical Machine Learning (ML) algorithms implemented using Two-Class Averaged Perceptron (TCAP) and Two-Class Logistic Regression (TCLR) respectively. This methodology then forms the subject of the empirical evaluation of the suitability of this model in the accurate classification of both legitimate web requests and SQLIA payloads.

Hierarchical clustering with multiple-height branch-cut applied to short time-series gene expression data.

Rigid adherence to pre-specified thresholds and static graphical representations can lead to incorrect decisions on merging of clusters. As an alternative to existing automated or semi-automated methods, we developed a visual analytics approach for performing hierarchical clustering analysis of short time-series gene expression data. Dynamic sliders control parameters such as the similarity threshold at which clusters are merged and the level of relative intra-cluster distinctiveness, which can be used to identify "weak-edges" within clusters. An expert user can drill down to further explore the dendrogram and detect nested clusters and outliers. This is done by using the sliders and by pointing and clicking on the representation to cut the branches of the tree in multiple-heights. A prototype of this tool has been developed in collaboration with a small group of biologists for analysing their own datasets. Initial feedback on the tool has been positive.

Can Regional Cooperation Promote Sustainable Development?

This chapter argues that regional cooperation may be a promising framework to work towards sustainable development. There are two broad pathways linking regional cooperation and sustainable development. On the one hand, shared or transboundary socio-environmental concerns may spark regional cooperation and on the other, pre-existing regional organisations created for other purposes become frameworks to address sustainability concerns. Yet, neither of these processes is automatic and whether they take place depends on the existence of particular drivers pursuing a sustainability agenda at the regional level. Ultimately, whether regional cooperation fosters sustainable development and how this takes place thus depends to a large extent on the specific people or organisations driving a sustainability agenda at the regional level and their relationship to national governments.

Technology enhancement - A full role for the elderly.

An invited address to the University of Melbourne's Graduate House Seminar program, covering the interactions between technology and the elderly from the point of view of the regulatory and governance failures that are leading to inappropriate results. Issues of codesign, IT access, mobility, falls prevention are specifically addressed. Draws somewhat from Wigan, M.R. (2013) Constructing Age and Technology as Augmentation, not Degradation. IEEE ISTAS Conference, Toronto June 25-27, pp 136-143