A novel optimized neural network model for cyber attack detection using enhanced whale optimization algorithm.

Cybersecurity is critical in today's digitally linked and networked society. There is no way to overestimate the importance of cyber security as technology develops and becomes more pervasive in our daily lives. Cybersecurity is essential to people's protection. One type of cyberattack known as "credential stuffing" involves using previously acquired usernames and passwords by attackers to access user accounts on several websites without authorization. This is feasible as a lot of people use the same passwords and usernames on several different websites. Maintaining the security of online accounts requires defence against credential-stuffing attacks. The problems of credential stuffing attacks, failure detection, and prediction can be handled by the suggested EWOA-ANN model. Here, a novel optimization approach known as Enhanced Whale Optimization Algorithm (EWOA) is put on to train the neural network. The effectiveness of the suggested attack identification model has been demonstrated, and an empirical comparison will be carried out with respect to specific security analysis.

A Provocative Molecular Link between Mammographic Density and BRCA1-loss associated TNBC.

Triple-negative breast cancer (TNBC) is a highly aggressive form of breast cancer that has a high mortality rate and disproportionately affects young African American (AA) women who carry mutations in the BRCA1 gene. Approximately 80% of breast cancers which develop in BRCA1-mutant carriers will have TNBC and the molecular mechanism facilitating tumor development is unclear. Our earlier work suggested Ubc9 to play a critical role in BRCA1 loss mediated TNBC cell migration and metastasis. Collagen is one of the major components of the stromal extracellular matrix (ECM) network that influences tissue density. Its re-organization act as a scaffold aiding cancer cells to migrate causing metastasis. Ubc9 is known to increase the production of collagen, a key component of fibroglandular breast tissue, as well as tumorigenesis. Our work is based on the hypothesis that loss of BRCA1 in women with high breast density causes abnormal Ubc9 levels which upregulates collagen, fibronectin and inhibits SIRT1, ß-catenin expression facilitating TNBC. We tested this hypothesis by studying the expression of total collagen, fibronectin, Ubc9, SIRT1, ß-catenin in BRCA1 mutant TNBC cells and tumor sample derived from patient with dense breasts using immunofluorescence, immunohistochemistry, and collagen assay. Our results suggest for the first time that mutation or loss of BRCA1 function in women with fibrocystic breasts can lead to over expression of Ubc9, induction of collagen and; fibronectin, inhibition of SIRT1 and nuclear accumulation of ß-catenin which could contribute to TNBC development. This network will aid not only in the identification of potential mechanism-based biomarkers that could detect disease early, but also enforce preventive measures that could reduce the risk for TNBC in women with high MD thus reducing the mortality associated with these cancers to achieve health equity.