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Artificial Intelligence (AI) is changing the way various industries operate, and cybersecurity is no exception. Over the years, cyber threats have been complex and frequent, and the need for advanced, adaptive security measures is greater than ever. AI and Machine Learning (ML) offer powerful tools to enhance cybersecurity defenses, but they also bring new challenges and risks.  This article examines how AI will impact cybersecurity, highlighting its implications for Security Information and Event Management (SIEM) systems. Main Challenges Cybersecurity Faces Today Imagine a situation where an organization is facing a complex, multi-vector cyber attack, and AI is incorporated into the…

arXiv:2405.20419v1 Announce Type: new Abstract: The rapid emergence of antibiotic-resistant bacteria is recognized as a global healthcare crisis, undermining the efficacy of life-saving antibiotics. This crisis is driven by the improper and overuse of antibiotics, which escalates bacterial resistance. In response, this study explores the use of clinical decision support systems, enhanced through the integration of electronic health records (EHRs), to improve antibiotic stewardship. However, EHR systems present numerous data-level challenges, complicating the effective synthesis and utilization of data. In this work, we transform EHR data into a serialized textual representation and employ pretrained foundation models to demonstrate how this…

[Submitted on 30 May 2024] View a PDF of the paper titled Is Synthetic Data all We Need? Benchmarking the Robustness of Models Trained with Synthetic Images, by Krishnakant Singh and 4 other authors View PDF HTML (experimental) Abstract:A long-standing challenge in developing machine learning approaches has been the lack of high-quality labeled data. Recently, models trained with purely synthetic data, here termed synthetic clones, generated using large-scale pre-trained diffusion models have shown promising results in overcoming this annotation bottleneck. As these synthetic clone models progress, they are likely to be deployed in challenging real-world settings, yet their suitability remains…