Leveraging LSTM and GAN for Modern Malware Detection

The malware booming is a cyberspace equal to the effect of climate change to ecosystems in terms of danger. In the case of significant investments in cybersecurity technologies and staff training, the global community has become locked up in the eternal war with cyber security threats. The multi-form and changing faces of malware are continuously pushing the boundaries of the cybersecurity practitioners employ various approaches like detection and mitigate in coping with this issue. Some old mannerisms like signature-based detection and behavioral analysis are slow to adapt to the speedy evolution of malware types. Consequently, this paper proposes the utilization of the Deep Learning Model, LSTM networks, and GANs to amplify malware detection accuracy and speed. A fast-growing, state-of-the-art technology that leverages raw bytestream-based data and deep learning architectures, the AI technology provides better accuracy and performance than the traditional methods. Integration of LSTM and GAN model is the technique that is used for the synthetic generation of data, leading to the expansion of the training datasets, and as a result, the detection accuracy is improved. The paper uses the VirusShare dataset which has more than one million unique samples of the malware as the training and evaluation set for the presented models. Through thorough data preparation including tokenization, augmentation, as well as model training, the LSTM and GAN models convey the better performance in the tasks compared to straight classifiers. The research outcomes come out with 98% accuracy that shows the efficiency of deep learning plays a decisive role in proactive cybersecurity defense. Aside from that, the paper studies the output of ensemble learning and model fusion methods as a way to reduce biases and lift model complexity.Comment: 11 page

A Review On Phytosterol (Ps) Enriched Mayonnaise

This study focuses on the nutritional significance of phytosterol (PS) enriched mayonnaise in our everyday diets. We have explored various methods for creating PS-enriched mayonnaise and evaluated their sensory characteristics. Phytosterols are natural compounds present in plant-based foods. Sources of phytosterols include unrefined plant lecithin, nuts, legumes, wheat germ, seeds, whole grains, plant-based fruits, and vegetables. Phytosterols share a similar structural composition with cholesterol, but they are not absorbed in substantial amounts by the body. Phytosterols play a vital role in human health, particularly in lowering cholesterol levels. It is recommended that a daily intake of approximately 2 grams of phytosterols (sterols and stanols) can lead to a reduction of approximately 10% in LDL cholesterol levels. This article delves into the preparation of phytosterol-enriched mayonnaise and highlights its nutritional benefits in our daily lives

Mnogofraktalnost i tvorba sporih čestica u sudarima 24Mg–AgBr na energiji 4.5 AGeV

We investigated the multifractality of target fragments of 24Mg-AgBr interaction at low energy (4.5 AGeV) in emission angle phase space, using a new method as proposed by Takagi. The analysis involves the step of measuring the generalised dimension Dq, which in turn deducts the multifractal behaviour of target fragments. We also determine the multifractal specific heat.Istražujemo mnogofraktalnost izlaznih sporih čestica u sudarima 24Mg–AgBr na niskoj energiji (4.5 AGeV) u faznom prostoru kuta emisije, primjenom nove metode koju je predložio Takagi. U analizi se određuje poopćena dimenzija Dq iz koje se izvode mnogofraktalna svojstva izlaznih čestica. Također izvodimo mnogofraktalnu specifičnu toplinu

Multifractality and multifractal specific heat in fragmentation process in

We have investigated the multifractality of target fragments of 24Mg-AgBr interaction at low energy (4.5AGeV) using a new method as proposed by Takagi. The analysis involves the step of measuring the generalised dimension Dq, which in turn, deduce the multifractal behaviour of target fragments. Ultimately we determine multifractal specific heat. A comparison with other data is also done.Author Affiliation: Dipak Ghosh, Argha Deb, Keya Dutta (Chattopadhyay), Rinku Sarkar, Ishita Dutta and Mitali Mondal 1.Nuclear and Particle Physics Research Centre, Department of Physics, Jadavpur University, Kolkata-700 032, India E-mail : [email protected] and Particle Physics Research Centre, Department of Physics, Jadavpur University, Kolkata-700 032, Indi

NEK1 Phosphorylation of YAP Promotes Its Stabilization and Transcriptional Output

Most prostate cancer (PCa) deaths result from progressive failure in standard androgen deprivation therapy (ADT), leading to metastatic castration-resistant PCa (mCRPC); however, the mechanism and key players leading to this are not fully understood. While studying the role of tousled-like kinase 1 (TLK1) and never in mitosis gene A (NIMA)-related kinase 1 (NEK1) in a DNA damage response (DDR)-mediated cell cycle arrest in LNCaP cells treated with bicalutamide, we uncovered that overexpression of wt-NEK1 resulted in a rapid conversion to androgen-independent (AI) growth, analogous to what has been observed when YAP1 is overexpressed. We now report that overexpression of wt-NEK1 results in accumulation of YAP1, suggesting the existence of a TLK1\u3eNEK1\u3eYAP1 axis that leads to adaptation to AI growth. Further, YAP1 is co-immunoprecipitated with NEK1. Importantly, NEK1 was able to phosphorylate YAP1 on six residues in vitro, which we believe are important for stabilization of the protein, possibly by increasing its interaction with transcriptional partners. In fact, knockout (KO) of NEK1 in NT1 PCa cells resulted in a parallel decrease of YAP1 level and reduced expression of typical YAP-regulated target genes. In terms of cancer potential implications, the expression of NEK1 and YAP1 proteins was found to be increased and correlated in several cancers. These include PCa stages according to Gleason score, head and neck squamous cell carcinoma, and glioblastoma, suggesting that this co-regulation is imparted by increased YAP1 stability when NEK1 is overexpressed or activated by TLK1, and not through transcriptional co-expression. We propose that the TLK1\u3eNEK1\u3eYAP1 axis is a key determinant for cancer progression, particularly during the process of androgen-sensitive to -independent conversion during progression to mCRPC