Narrative in picture books, or, The paper that should have had slides

In this sense picture books resemble other combinative art forms, such as opera or musical theater, films, and ballet; older examples include the courtly masque and the emblem book. This resemblance is good for me, since I thrive on analogies (I was apparently permanently warped by that section of the SATs), and I therefore often find it useful to consider picture books along with those other media, without, of course, ignoring the fact that picture books also have their own individual charms and characteristics. I'd like to examine the aspects of the picture book the text, the art and other physical factors and then discuss how these narratives work together to affect each other and the final outcome.published or submitted for publicatio

Bronze Age moss fibre garments from Scotland – the jury’s out

In the light of recent discoveries of early to middle Bronze Age burials with mats and fibrous material in Scotland, for example at Langwell farm and Forteviot, it was deemed timely to re-evaluate earlier finds of this period, several of which were discovered and initially reported on nearly a century ago. As part of this research it was noted that three Bronze Age finds from the old literature were reported as clothing or shrouds made of hair moss (Polytrichum commune). Three of these are reassessed here, with a detailed re-examination of the “hair moss apron” from North Cairn Farm. Technological analysis of this find showed no evidence for the twining previously reported and SEM fibre analysis shows that it is unlikely to be hair moss or indeed Bronze Age. However, there is other evidence for hair moss artefacts from other British Bronze Age and Roman contexts. These suggest it is possible that hair moss fibre was used in Scotland in the Bronze Age, but that the North Cairn Farm fibrous object should no longer be considered among this evidence

Machine Learning Models that Remember Too Much

Machine learning (ML) is becoming a commodity. Numerous ML frameworks and services are available to data holders who are not ML experts but want to train predictive models on their data. It is important that ML models trained on sensitive inputs (e.g., personal images or documents) not leak too much information about the training data. We consider a malicious ML provider who supplies model-training code to the data holder, does not observe the training, but then obtains white- or black-box access to the resulting model. In this setting, we design and implement practical algorithms, some of them very similar to standard ML techniques such as regularization and data augmentation, that "memorize" information about the training dataset in the model yet the model is as accurate and predictive as a conventionally trained model. We then explain how the adversary can extract memorized information from the model. We evaluate our techniques on standard ML tasks for image classification (CIFAR10), face recognition (LFW and FaceScrub), and text analysis (20 Newsgroups and IMDB). In all cases, we show how our algorithms create models that have high predictive power yet allow accurate extraction of subsets of their training data

PowerDrive: Accurate De-Obfuscation and Analysis of PowerShell Malware

PowerShell is nowadays a widely-used technology to administrate and manage Windows-based operating systems. However, it is also extensively used by malware vectors to execute payloads or drop additional malicious contents. Similarly to other scripting languages used by malware, PowerShell attacks are challenging to analyze due to the extensive use of multiple obfuscation layers, which make the real malicious code hard to be unveiled. To the best of our knowledge, a comprehensive solution for properly de-obfuscating such attacks is currently missing. In this paper, we present PowerDrive, an open-source, static and dynamic multi-stage de-obfuscator for PowerShell attacks. PowerDrive instruments the PowerShell code to progressively de-obfuscate it by showing the analyst the employed obfuscation steps. We used PowerDrive to successfully analyze thousands of PowerShell attacks extracted from various malware vectors and executables. The attained results show interesting patterns used by attackers to devise their malicious scripts. Moreover, we provide a taxonomy of behavioral models adopted by the analyzed codes and a comprehensive list of the malicious domains contacted during the analysis

A New Index for Predicting Catastrophes by Madhur Anand

A Review of Madhur Anand\u27s A New Index for Predicting Catastrophes