software flaws pose a serious risk to the dependability and security of computersystems and applications in a variety of industries. Because they take a long time and are prone to errors, traditional techniques of fi...
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ISBN:
(数字)9798331505134
ISBN:
(纸本)9798331505141
software flaws pose a serious risk to the dependability and security of computersystems and applications in a variety of industries. Because they take a long time and are prone to errors, traditional techniques of finding these vulnerabilities-like human code reviews and static analysis tools-are frequently insufficient. In order to improve the precision, effectiveness, and scalability of vulnerability detection, this paper presents a thorough technique for creating a software vulnerability detection tool that uses machine learning (ML) methods. The tool uses machine learning (ML) to automatically evaluate code samples, find possible security holes, and give developers useful information. The suggested approach consists of multiple phases, such as gathering and preprocessing data, extracting features, training and assessing models, and integrating and deploying tools. To maximise detection performance, a variety of machine learning (ML) algorithms are investigated, such as logistic regression, decision trees, random forests, support vector machines, and deep learning models. The tool's ability to adjust to new threats is guaranteed by its feedback mechanisms and ongoing monitoring. With the help of this cutting-edge technique, software engineers and security experts will be able to detect and address flaws more effectively and automatically, strengthening softwaresystems' defences against ever-changing cyberattacks.
Aiming at solving the problem of low marine vessel detection accuracy in the sea fog environment, a deep learning-based anti-fog marine vessel detection method is proposed in this paper by combining defogging preproce...
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Recently, Unmanned Aerial Vehicles (UAVs) have entered the commercial market and have been adopted by both amateurs and experts. This proliferation of U A V s, now known as drones, is accompanied by a multiplicity of ...
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This research paper discusses the Real Time Operating systems;their types, software, benefits, and drawbacks, as well as how they work, including task states and control blocks. This research goes into great detail to...
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The proceedings contain 28 papers. The topics discussed include: calibrating deep learning-based code smell detection using human feedback;change pattern detection for optimizing incremental static analysis;how they r...
ISBN:
(纸本)9798350305067
The proceedings contain 28 papers. The topics discussed include: calibrating deep learning-based code smell detection using human feedback;change pattern detection for optimizing incremental static analysis;how they relate and leave: understanding atoms of confusion in open-source java projects;on developing and improving tools for architecture-smell tracking in Java systems;the docker hub image inheritance network: construction and empirical insights;leveraging user-defined identifiers for counterfactual data generation in source code vulnerability detection;do code quality and style issues differ across (non-)machine learning notebooks? yes!;quality assurance awareness in open source software projects on GitHub;explaining transformer-based code models: what do they learn? when they do not work?;can we trust the default vulnerabilities severity?;and CIGAR: contrastive learning for GitHub action recommendation.
The proceedings contain 46 papers. The special focus in this conference is on Science, engineering Management and Information Technology. The topics include: Verification and Validation of Knowledge engineering System...
ISBN:
(纸本)9783031722868
The proceedings contain 46 papers. The special focus in this conference is on Science, engineering Management and Information Technology. The topics include: Verification and Validation of Knowledge engineeringsystems: A Life Cycle Framework;The Critical Factors of Success of Gamification in Digital Banking Services: Using Analytic Hierarchy Process (AHP) Approach;e-Shopping Sites Preference Analysis with Multi-criteria Decision-Making Methods;advancing Anemia Diagnosis: Harnessing Machine Learning Methods for Accurate Detection;monkeypox Detection with K-mer Using Machine Learning Algorithms;cloud Computing Model for Handling Medical Big Data: A Mobile Hospital Pervasive Healthcare Application;Harnessing Advanced AI Techniques: An In-Depth Analysis of Machine Learning Models for Improved Diabetes Prediction;image Processing in Toxicology: A Systematic Review;augmented Reality Immersive World with Hologram Special Effect in Early Childhood Education;improving the Visual Ergonomics of computerised Workplaces Through the Use of Specialised Eye-Rest software;a Diagnosis Model Based on Federated Learning for Lung Cancer Classification;Arrhythmia Detection from ECG Traces Images Using Transfer Learning Approach;enhancing Traffic Flow Prediction in Urban Areas Through Deep Learning and Probe Information: A Comparative Study;an Approach to Multi-agent Deep Q-Network Optimization of Signal Control in Multi-intersection Road Environments to Enhance Urban Traffic Flow;blockchain-Driven Smart Contracts: An Overview of Application Areas and Gap Identification in Construction Management Literature;stochastic Optimization Methodology for Production Planning with Uncertain Demand and Lead Time Based on the Digital Twin;role of Top Management Commitment and Information Technology Investment in Digital Transformation;antecedents of Mobile Banking Apps Adoption Among Consumers in Ghana.
Password Managers are software tools designed to help users easily store and access credentials across devices while also reducing, if not eliminating, reuse of passwords across different service providers. Previous r...
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ISBN:
(纸本)9783031490989;9783031490996
Password Managers are software tools designed to help users easily store and access credentials across devices while also reducing, if not eliminating, reuse of passwords across different service providers. Previous research has identified several security vulnerabilities with desktop and browser-based password managers;however, aside from research on possibilities of phishing, the security of password manager applications on mobile devices had never been investigated comprehensively prior to this paper. We present a study of three of the most popular password managers on the Google Play Store including but not limited to their password generators, vault and metadata storage, and autofill capabilities. By building upon past findings, we identify several weaknesses in password managers including generation of weak and statistically non-random passwords, unencrypted storage of metadata and application settings, and possibilities for credential phishing. In addition, we suggest several improvements to mobile password managers, other Android applications, and the Android operating system that can improve the user experience and security of password managers on Android devices. From our observations, we also determine areas for future research that can help improve the security of password managers.
The use of functional magnetic resonance imaging (fMRI) has been widely used to detect brain abnormalities linked to Bipolar Disorder. These borderline diseases are either inherited or the result of parental exposure ...
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On the basis of successive way points (WPs) and piecewise reference speed, a trajectory generator (TG) is elaborately devised to generate a smooth trajectory for an unmanned surface vehicle (USV) in this paper. Firstl...
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As Internet of Things (IoT) devices become more commonplace and are used in more aspects of daily life, a bright future for people, data, and processes is emerging. Because of its potential to enhance patient care as ...
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