Search

In the domain of backdoor attacks, accurate labeling of injected data is essential for evading rudimentary detection mechanisms. This imperative has catalyzed the development of clean-label attacks, which are notably more elusive as they preserve the original labels of the injected data. Current clean-label attack methodologies primarily depend on extensive knowledge of the training dataset. However, practically, such comprehensive dataset access is often unattainable, given that training datasets are typically compiled from various independent sources. Departing from conventional clean-label attack methodologies, our research introduces DFB, a data-free, low-budget, and high-efficacy clean-label backdoor Attack. DFB is unique in its independence from training data access, requiring solely the knowledge of a specific target class. Tested on CIFAR10, Tiny-ImageNet, and TSRD, DFB demonstrates remarkable efficacy with minimal poisoning rates of just 0.1%, 0.025%, and 0.4%, respectively. These rates are significantly lower than those required by existing methods such as LC, HTBA, BadNets, and Blend, yet DFB achieves superior attack success rates. Furthermore, our findings reveal that DFB poses a formidable challenge to four established backdoor defense algorithms, indicating its potential as a robust tool in advanced clean-label attack strategies.

The structures, point defects and impacts of fission products for U3Si (\b{eta}-U3Si and {\gamma}-U3Si) and USi2 ({\alpha}-USi2 and \b{eta}-USi2) are studied by first-principles calculations. The lattice parameters of U3Si and USi2 are calculated and the stability of different types of point defects is predicted by their formation energies. The results show that silicon vacancies are more prone to be produced than uranium vacancies in \b{eta}-USi2 matrix, while uranium vacancies are the most stable defects of other three types of crystallographic structures. The most favorable sites of fission products (strontium, barium, cerium and neodymium) are determined in this work as well. By calculating incorporation energies of fission products, we demonstrate that the uranium site is the most favored for all the fissions products. Comparing the structural changes influenced by different fission products, it is also found that the highest volume change is caused by barium interstitials. According to the current data, rare earth elements cerium and neodymium are found to be more stable than alkaline earth metals strontium and barium in a given nuclear matrix. Finally, it is also determined that in USi2 crystal lattice fission products tend to be stabilized in uranium substitution sites, while they are likely to form precipitates from the U3Si matrix. It is expected that this work may provide new insight into the mechanism for structural evolutions of silicide nuclear fuels in a reactor.

It is important to enable reasoning about the meaning and possible effects of updates to ensure that the updated system operates correctly. A formal, mathematical model of dynamic update should be developed, in order to understand by both users and implementors of update technology what design choices can be considered. In this paper, we define a formal calculus $update\pi$, a variant extension of higher-order $\pi$ calculus, to model dynamic updates of component-based software, which is language and technology independent. The calculus focuses on following main concepts: proper granularity of update, timing of dynamic update, state transformation between versions, update failure check and recovery. We describe a series of rule on safe component updates to model some general processes of dynamic update and discuss its reduction semantics coincides with a labelled transition system semantics that illustrate the expressive power of these calculi., Comment: 11 pages