Results 31 to 40 of about 118,924 (255)
Hardcoded vulnerability detection approach for IoT device firmware
With the popularization of IoT devices, more and more valuable data is generated.Analyzing and mining big data based on IoT devices has become a hot topic in the academic and industrial circles in recent years.However, due to the lack of necessary ...
Chao MU +5 more
doaj
With the rapid growth of IoT devices, ensuring the security of embedded firmware has become a critical concern. Despite advances in existing vulnerability discovery methods, previous research has been limited to vulnerabilities occurring in binary ...
Xixing Li, Qiang Wei, Zehui Wu, Wei Guo
doaj +1 more source
Characterizing Buffer Overflow Vulnerabilities in Large C/C++ Projects
Security vulnerabilities are present in most software systems, especially in projects with a large codebase, with several versions over the years, developed by many developers.
Jose D'Abruzzo Pereira +2 more
doaj +1 more source
ABSTRACT Background Shwachman–Diamond syndrome (SDS) is a rare autosomal recessive ribosomopathy characterized by bone marrow failure and multisystem involvement, with emerging evidence of associated neurocognitive impairment. Methods We conducted a retrospective study of 240 individuals with biallelic Shwachman–Bodian–Diamond syndrome (SBDS) mutations
Jane Koo +11 more
wiley +1 more source
ABSTRACT Background Patients with chronic kidney disease undergoing hemodialysis commonly experience reduced physical function, fatigue, poor sleep quality, and impaired health‐related quality of life. Intradialytic exercise has been proposed as a non‐pharmacological strategy to improve these outcomes.
Klebson da Silva Almeida +6 more
wiley +1 more source
Vulnerabilities Detection by Matching with known Vulnerabilities
Vulnerability Matcher is a tool designed to identify and prioritize security vulnerabilities in software systems. This intelligent system leverages advanced machine learning algorithms to analyze and match identified vulnerabilities with known security threats and exploits.
Precious Jeo John, Sumit Surendran
openaire +1 more source
A Context-Aware Neural Embedding for Function-Level Vulnerability Detection
Exploitable vulnerabilities in software systems are major security concerns. To date, machine learning (ML) based solutions have been proposed to automate and accelerate the detection of vulnerabilities. Most ML techniques aim to isolate a unit of source
Hongwei Wei +3 more
doaj +1 more source
ABSTRACT Background Maintenance hemodialysis (MHD) patients frequently suffer from frailty, characterized by reduced physical function and poor prognosis. Myokines, such as myonectin, secreted by muscle, are emerging regulators of systemic health. This study investigated the relationship between serum myonectin, adipokines (adiponectin, omentin), and ...
Kenichi Kono +7 more
wiley +1 more source
ABSTRACT Background Chronic micro‐inflammation in patients with end‐stage renal disease (ESRD) is a significant driver of cardiovascular complications and diminished quality of life. While standard hemodialysis (SHD) effectively manages small‐molecule clearance, its ability to remove medium‐to‐large uremic toxins—the primary catalysts of systemic ...
Hongwei Zuo +5 more
wiley +1 more source
Binary vulnerability detection plays an important role in the field of program security. In order to deal with large-scale vulnerability detection tasks, more and more neural network technologies are applied to cross-architectures vulnerability detection.
Yingmei Han +3 more
doaj +1 more source

