Detecting (Absent) App-to-app authentication on cross-device short-distance channels

Short-distance or near-field communication is increasingly used by mobile apps for interacting or exchanging data in a cross-device fashion. In this paper, we identify a security issue, namely cross-device app-to-app communication hijacking (or CATCH), that affect Android apps using short-distance channels (e.g., Bluetooth and Wi-Fi-Direct). This issue causes unauthenticated or malicious app-to-app interactions even when the underlying communication channels are authenticated and secured. In addition to discovering the security issue, we design an algorithm based on data-flow analysis for detecting the presence of CATCH in Android apps. Our algorithm checks if a given app contains an app-to-app authentication scheme, necessary for preventing CATCH. We perform experiments on a set of Android apps and show the CATCH problem is always present on the whole analyzed applications set. We also discuss the impact of the problem in real scenarios by presenting two real case studies. At the end of the paper we reported limitations of our model along with future improvements

Ant Colony Heuristic for Mapping and Scheduling Tasks and Communications on Heterogeneous Embedded Systems

To exploit the power of modern heterogeneous multiprocessor embedded platforms on partitioned applications, the designer usually needs to efficiently map and schedule all the tasks and the communications of the application, respecting the constraints imposed by the target architecture. Since the problem is heavily constrained, common methods used to explore such design space usually fail, obtaining low-quality solutions. In this paper, we propose an ant colony optimization (ACO) heuristic that, given a model of the target architecture and the application, efficiently executes both scheduling and mapping to optimize the application performance. We compare our approach with several other heuristics, including simulated annealing, tabu search, and genetic algorithms, on the performance to reach the optimum value and on the potential to explore the design space. We show that our approach obtains better results than other heuristics by at least 16% on average, despite an overhead in execution time. Finally, we validate the approach by scheduling and mapping a JPEG encoder on a realistic target architecture

Recombinants between Deformed wing virus and Varroa destructor virus-1 may prevail in Varroa destructor-infested honeybee colonies

We have used high-throughput Illumina sequencing to identify novel recombinants between deformed wing virus (DWV) and Varroa destructor virus-1 (VDV-1), which accumulate to higher levels than DWV in both honeybees and Varroa destructor mites. The recombinants, VDV-1VVD and VDV-1DVD, exhibit crossovers between the 5’-untranslated region (5’-UTR), and/or the regions encoding the structural (capsid) and non-structural viral proteins. This implies the genomes are modular and that each region may evolve independently, as demonstrated in human enteroviruses. Individual honeybee pupae were infected with a mixture of observed recombinants and DWV. The strong correlation between VDV-1DVD levels in honeybee pupae and the associated mites was observed, suggesting that this recombinant, with a DWV-derived 5’-UTR and non-structural protein region flanking VDV- 1-derived capsid encoding region, is better adapted to transmission between V. destructor and honeybees than the parental DWV or a recombinant bearing the VDV-1-derived 5’-UTR (VDV-1VVD)