The Challenges in SDN/ML Based Network Security : A Survey

Machine Learning is gaining popularity in the network security domain as many more network-enabled devices get connected, as malicious activities become stealthier, and as new technologies like Software Defined Networking (SDN) emerge. Sitting at the application layer and communicating with the control layer, machine learning based SDN security models exercise a huge influence on the routing/switching of the entire SDN. Compromising the models is consequently a very desirable goal. Previous surveys have been done on either adversarial machine learning or the general vulnerabilities of SDNs but not both. Through examination of the latest ML-based SDN security applications and a good look at ML/SDN specific vulnerabilities accompanied by common attack methods on ML, this paper serves as a unique survey, making a case for more secure development processes of ML-based SDN security applications.Comment: 8 pages. arXiv admin note: substantial text overlap with arXiv:1705.0056

One Financial Education Intervention, Two Performances, What Happened?

It is often expected that one financial education intervention should offer similar performance in changing financial behaviour to determine its role in social marketing. Behaviour change takes time and it needs different approaches to different segmentations. It involves multifaceted aspects and cannot always be controlled by the organisers. If the performances of an intervention are not consistent, should we reject or endorse it? This paper takes a critical view of the application of social marketing mix concepts from 4Ps and segmentation in designing and assessing the impact of a financial education intervention. The short course “Managing My Money” (the MMM) was designed and delivered through direct and online channels. Using the dataset from a large research project of the True Potential Centre for the Public Understanding of Finance (PUFin) at the Open University in co-operation with the Coventry University, funded by the Money Advice Service’s What Works Fund. There were diversified experiments to explore the impact of one financial education intervention which distributed to specific target audiences in different places. This seeks to explore what works and does not work for different populations in improving their personal financial behaviours including saving and borrowing. This paper selected the datasets of 438 members of New Central Credit Union (NCCU) from 1953 NCCU members and 1257 members of Coventry District Credit Union (CDCU) from 1322 CDCU members who lived in Coventry and categorised into neighbourhood segmentation by wards. The purpose is to explore how a specific neighbourhood environment might influence individual saving and borrowing behaviour. Randomised Controlled Trials (RCTs) was used to design the experiment and to assess the impact of the intervention toward saving and borrowing behaviours among the control and experimental group. The experimental group received either face-to-face intervention at a workshop or printed materials and an online course, while the control group did not receive any of these treatments. This paper offers a case study to explain why one financial education intervention does not always offer the repeated performance through the lens of social marketing. Some findings are useful to social marketers and educators, in the use and evaluation of a financial education intervention, to promote desirable saving and borrowing behaviours. Changing borrowing behaviour is more multifaceted than changing saving behaviour. It requires a sensitive approach in dealing with simultaneous savers and debtors. Individual financial capacity constrains their saving and borrowing behaviour change. Neighbourhood segmentation is useful in explaining the limitations when intervening in a financial behaviour change

Smooth (non)rigidity of piecewise rank one locally symmetric manifolds

We define \emph{piecewise rank 1} manifolds, which are aspherical manifolds that generally do not admit a nonpositively curved metric but can be decomposed into pieces that are diffeomorphic to finite volume, irreducible, locally symmetric, nonpositively curved manifolds with $\pi_1$-injective cusps. We prove smooth (self) rigidity for this class of manifolds in the case where the gluing preserves the cusps' homogeneous structure. We compute the group of self homotopy equivalences of such a manifold and show that it can contain a normal free abelian subgroup and thus, can be infinite. Elements of this abelian subgroup are twists along elements in the center of the fundamental group of a cusp.Comment: 20 pages, 1 figur