Mal-Netminer: Malware Classification Approach based on Social Network Analysis of System Call Graph

As the security landscape evolves over time, where thousands of species of malicious codes are seen every day, antivirus vendors strive to detect and classify malware families for efficient and effective responses against malware campaigns. To enrich this effort, and by capitalizing on ideas from the social network analysis domain, we build a tool that can help classify malware families using features driven from the graph structure of their system calls. To achieve that, we first construct a system call graph that consists of system calls found in the execution of the individual malware families. To explore distinguishing features of various malware species, we study social network properties as applied to the call graph, including the degree distribution, degree centrality, average distance, clustering coefficient, network density, and component ratio. We utilize features driven from those properties to build a classifier for malware families. Our experimental results show that influence-based graph metrics such as the degree centrality are effective for classifying malware, whereas the general structural metrics of malware are less effective for classifying malware. Our experiments demonstrate that the proposed system performs well in detecting and classifying malware families within each malware class with accuracy greater than 96%.Comment: Mathematical Problems in Engineering, Vol 201

Dense Text-to-Image Generation with Attention Modulation

Existing text-to-image diffusion models struggle to synthesize realistic images given dense captions, where each text prompt provides a detailed description for a specific image region. To address this, we propose DenseDiffusion, a training-free method that adapts a pre-trained text-to-image model to handle such dense captions while offering control over the scene layout. We first analyze the relationship between generated images' layouts and the pre-trained model's intermediate attention maps. Next, we develop an attention modulation method that guides objects to appear in specific regions according to layout guidance. Without requiring additional fine-tuning or datasets, we improve image generation performance given dense captions regarding both automatic and human evaluation scores. In addition, we achieve similar-quality visual results with models specifically trained with layout conditions.Comment: Accepted by ICCV2023. Code and data are available at https://github.com/naver-ai/DenseDiffusio

Broussonetia papyrifera Root Bark Extract Exhibits Anti-inflammatory Effects on Adipose Tissue and Improves Insulin Sensitivity Potentially Via AMPK Activation

The chronic low-grade inflammation in adipose tissue plays a causal role in obesity-induced insulin resistance and its associated pathophysiological consequences. In this study, we investigated the effects of extracts of Broussonetia papyrifera root bark (PRE) and its bioactive components on inflammation and insulin sensitivity. PRE inhibited TNF-alpha-induced NF-kappa B transcriptional activity in the NF-kappa B luciferase assay and pro-inflammatory genes' expression by blocking phosphorylation of I kappa B and NF-kappa B in 3T3-L1 adipocytes, which were mediated by activating AMPK. Ten-week-high fat diet (HFD)-fed C57BL6 male mice treated with PRE had improved glucose intolerance and decreased inflammation in adipose tissue, as indicated by reductions in NF-kappa B phosphorylation and pro-inflammatory genes' expression. Furthermore, PRE activated AMP-activated protein kinase (AMPK) and reduced lipogenic genes' expression in both adipose tissue and liver. Finally, we identified broussoflavonol B (BF) and kazinol J (KJ) as bioactive constituents to suppress pro-inflammatory responses via activating AMPK in 3T3-L1 adipocytes. Taken together, these results indicate the therapeutic potential of PRE, especially BF or KJ, in metabolic diseases such as obesity and type 2 diabetes

Energy band-gap engineering of conjugated microporous polymers via acidity-dependent in situ cyclization

Conjugated microporous polymers (CMPs) offer a unique structure integrating π- conjugated backbone into a porous network for the simultaneous transport of charges and materials. However, tuning electronic properties of CMPs so far has been limited to an approach of varying the monomers, and the precious metal catalysts are inevitably needed for the C–C coupling reaction. Here, we present a powerful strategy to synthesize CMPs and precisely tune their optical band gap and surface area through metal-free in situ cyclization reaction controlled by the acid strength of acid catalysts. Notably, the optical band gap of CMPs showed a linear relationship with the pKa of acid catalysts, which provides us with the ability to obtain the desired band gap between 2.07 and 3.35 eV, falling in the range of the visible solar spectrum. Moreover, CMPs exhibited excellent textural properties such as microporosity and high specific surface area

Leading With Callings: Effects of Leader’s Calling on Followers’ Team Commitment, Voice Behavior, and Job Performance

Viewing work as a calling has been considered to be beneficial to individuals and organizations. However, research to date has largely focused on the effects of individuals’ own callings on themselves, leaving the effects of one’s calling on others unexplored. Based on research that demonstrates prevalent effects of callings and leader’s influences on followers at work, we assumed that leader calling might have positive effects on followers’ outcomes. Specifically, we hypothesized that the extent to which leaders view their work as a calling have positive influences on followers’ team commitment, leader-rated voice behavior, and job performance. We also examined a mediating effect of transformational leadership on the relations between leader’s calling and the three follower’s outcomes. Using data on 284 leader-follower pairs from the South Korean Air Force, we found that leader’s calling was positively associated with followers’ team commitment, voice behaviors, and job performance. The effects of leader’s calling on follower commitment and voice behavior were partly accounted for by follower perceptions of transformational leadership. However, a mediating role of transformational leadership on the link between leader’s calling and job performance was not supported. The implications of these findings are discussed

Phospholipase A2β mediates light-induced stomatal opening in Arabidopsis

Phospholipase A2 (PLA2) catalyses the hydrolysis of phospholipids into lysophospholipids and free fatty acids. Physiological studies have indicated that PLA2 is involved in stomatal movement. However, genetic evidence of a role of PLA2 in guard cell signalling has not yet been reported. To identify PLA2 gene(s) that is (are) involved in light-induced stomatal opening, stomatal movement was examined in Arabidopsis thaliana plants in which the expression of PLA2 isoforms was reduced or knocked-out. Light-induced stomatal opening in PLA2α knockout plants did not differ from wild-type plants. Plants in which PLA2β was silenced by RNA interference exhibited delayed light-induced stomatal opening, and this phenotype was reversed by exogenous lysophospholipids, which are products of PLA2. Stomatal opening in transgenic plants that over-expressed PLA2β was faster than wild-type plants. The expression of PLA2β was localized to the endoplasmic reticulum of guard cells, and increased in response to light in the mature leaf. Aristolochic acid, which inhibits light-induced stomatal opening, inhibited the activity of purified PLA2β. Collectively, these results provide evidence that PLA2β is involved in light-induced stomatal opening in Arabidopsis