Responsive glyco-poly(2-oxazoline)s: synthesis, cloud point tuning, and lectin binding

A new sugar-substituted 2-oxazoline monomer was prepared using the copper-catalyzed alkyne-azide cycloaddition (CuAAC) reaction. Its copolymerization with 2-ethyl-2-oxazoline as well as 2-(dec-9-enyl)-2-oxazoline, yielding well-defined copolymers with the possibility to tune the properties by thiol-ene "click" reactions, is described. Extensive solubility studies on the corresponding glycocopolymers demonstrated that the lower critical solution temperature behavior and pH-responsiveness of these copolymers can be adjusted in water and phosphate-buffered saline (PBS) depending on the choice of the thiol. By conjugation of 2,3,4,6-tetra-O-acetyl-1-thio-beta-D-glucopyranose and subsequent deprotection of the sugar moieties, the hydrophilicity of the copolymer could be increased significantly, allowing a cloud-point tuning in the physiological range. Furthermore, the binding capability of the glycosylated copoly(2-oxazoline) to concanavalin A was investigated

A flexible framework for mobile device forensics based on cold boot attacks

Mobile devices, like tablets and smartphones, are common place in everyday life. Thus, the degree of security these devices can provide against digital forensics is of particular interest. A common method to access arbitrary data in main memory is the cold boot attack. The cold boot attack exploits the remanence effect that causes data in DRAM modules not to lose the content immediately in case of a power cut-off. This makes it possible to restart a device and extract the data in main memory. In this paper, we present a novel framework for cold boot-based data acquisition with a minimal bare metal application on a mobile device. In contrast to other cold boot approaches, our forensics tool overwrites only a minimal amount of data in main memory. This tool requires no more than three kilobytes of constant data in the kernel code section. We hence sustain all of the data relevant for the analysis of the previously running system. This makes it possible to analyze the memory with data acquisition tools. For this purpose, we extend the memory forensics tool Volatility in order to request parts of the main memory dynamically from our bare metal application. We show the feasibility of our approach on the Samsung Galaxy S4 and Nexus 5 mobile devices along with an extensive evaluation. First, we compare our framework to a traditional memory dump-based analysis. In the next step, we show the potential of our framework by acquiring sensitive user data