A5043125298- Advanced Malware Detection Techniques
- Adversarial Robustness in Machine Learning
- User Authentication and Security Systems
- Anomaly Detection Techniques and Applications
- Network Security and Intrusion Detection
- Biometric Identification and Security
- SARS-CoV-2 and COVID-19 Research
- Vaccine Coverage and Hesitancy
- Explainable Artificial Intelligence (XAI)
- Vehicular Ad Hoc Networks (VANETs)
- Domain Adaptation and Few-Shot Learning
- Spam and Phishing Detection
- Dietary Effects on Health
- Analog and Mixed-Signal Circuit Design
- COVID-19 Impact on Reproduction
- ECG Monitoring and Analysis
- Blind Source Separation Techniques
Meir Medical Center
2023
Tel Aviv University
2023
Herzliya Medical Center
2022
Ben-Gurion University of the Negev
2003-2021
The development of covid-19 vaccinations represents a notable scientific achievement. Nevertheless, concerns have been raised regarding their possible detrimental impact on male fertility OBJECTIVE: To investigate the effect BNT162b2 (Pfizer) vaccine semen parameters among donors (SD).Thirty-seven SD from three sperm banks that provided 216 samples were included in retrospective longitudinal multicenter cohort study. vaccination two doses, and completion was scheduled 7 days after second...
The vehicular connectivity revolution is fueling the automotive industry's most significant transformation seen in decades. However, as modern vehicles become more connected, they also much vulnerable to cyber-attacks. In this paper, a fully working machine learning approach proposed protect connected (fleets and individuals) against such attacks. We present system that monitors different vehicle interfaces (Network, CAN, OS), extracts relevant information based on configurable rules, sends...
The vehicular connectivity revolution is fueling the automotive industry's most significant transformation seen in decades. However, as modern vehicles become more connected, they also much vulnerable to cyber-attacks. In this paper, a fully working machine learning approach proposed protect connected (fleets and individuals) against such attacks. We present system that monitors different vehicle's interfaces (Network, CAN OS), extracts relevant information based on configurable rules sends...
Most of today's sensitive systems offer receiving information and performing actions remotely through the company's website by using authentication mechanisms such as username password, one-time tokens, etc. However, these methods are not immune against credentials theft. Authenticated sessions can be subjected to session hijacking stolen cookies, man in middle (MitM) attacks, social Engineering more. Behavioral biometrics models within help continuously verify user's identity throughout...
<b><i>Objective:</i></b> The aim of the study was to determine whether Ramadan month-long daily fasting affects semen analysis parameters. <b><i>Methods:</i></b> This retrospective cohort conducted in tertiary academic medical center. Medical records 97 Muslim patients who were admitted IVF unit from May 2011 2021 reviewed. Only men provided at least one sample during period (Ramadan month +70 days after) and not included. Semen characteristics...
The phenomenon of adversarial examples illustrates one the most basic vulnerabilities deep neural networks. Among variety techniques introduced to surmount this inherent weakness, training has emerged as effective strategy for learning robust models. Typically, is achieved by balancing and natural objectives. In work, we aim further optimize trade-off between standard accuracy enforcing a domain-invariant feature representation. We present new method, Domain Invariant Adversarial Learning...
The existence of adversarial examples points to a basic weakness deep neural networks. One the most effective defenses against such examples, training, entails training models with some degree robustness, usually at expense degraded natural accuracy. Most methods aim learn model that finds, for each class, common decision boundary encompassing both clean and perturbed examples. In this work, we take fundamentally different approach by treating class as separate be learned, effectively...
A novel computer method for ECG (electrocardiographic) signal filtering is discussed. This based on a concept called the prior knowledge principle (PKP). The PKP assumes that measured contains itself and environmental noises. An artificial with amplitude time resembling real has been constructed. Cases of white network noise are analyzed, level varying from 0 to 100%. calculated errors techniques used do not exceed 20%.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML"...