Analysis of Techniques for Detection and Removal of Zero-Day Attacks (ZDA)

Hamid, Khalid; Iqbal, Muhammad Waseem; Aqeel, Muhammad; Liu, Xiangyong; Arif, Muhammad

doi:10.1007/978-981-99-0272-9_17

Cited by 13 publications

(9 citation statements)

References 23 publications

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“…Inferring System Determining the System State The complexity and scope of the following systems that require maintenance increase, making manual notification management less feasible. Many glitch finding techniques based on automated log analysis have been proposed (Hamid, Iqbal, Aqeel, Liu, et al, 2023) and may eventually replace manually generated notifications, even though they haven't been used frequently in the events we've looked at. A lot of earlier work on anomaly identification takes a generic approach, labeling an event as anomalous.…”

Section: Methodsmentioning

confidence: 99%

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Failures and Repairs: An Examination of Software System Failure

Rahman,

Arshid,

Ayaz

et al. 2024

BBE

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The central theme of the article is to provide a better knowledge of software system failures and how to assure, maintain, and provide the support software systems that are in production. It includes the results of our search study. We conducted a qualitative analysis of thirty cases: fifteen from public incident reports and fifteen from in-depth interviews with engineers. Understanding and classifying failures as well as their identification, investigation, and mitigation were the main goals of our study. Furthermore, we obtained important analytical insights that are pertinent to the condition of practice as it is now and related problems. It is common for engineers to be unaware of the scaling limitations of the systems they support until those limits are exceeded, and failures have the potential to cascade across a system and cause catastrophic outages.We argue that the difficulties we've discovered may lead to changes in how systems are designed and supported.

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Section: Methodsmentioning

confidence: 99%

“…If the system has several components, faults in the system will result in component failure. Because the system's components interact with one another, the failure of one component may be accountable for causing one or more problems in the system (Hamid, Iqbal, Aqeel, Rana, et al, 2023).…”

Section: Testing Modelsmentioning

confidence: 99%

Failures and Repairs: An Examination of Software System Failure

Rahman,

Arshid,

Ayaz

et al. 2024

BBE

Self Cite

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“…Historical analyses of ransomware mitigation strategies highlighted the initial reliance on signature-based detection methods, which were quickly found to be ineffective against polymorphic and zero-day attacks [26,27,28,29]. The development of behavior-based detection tools represented a significant advancement, offering the ability to identify ransomware based on its actions rather than its signature [1,30,31].…”

Section: Existing Ransomware Detection and Prevention Toolsmentioning

confidence: 99%

RanAway: A Novel Ransomware-Resilient ReFS File System

Long,

Liang

2024

Preprint

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Ransomware has emerged as a pervasive threat in the cybersecurity landscape, characterized by its ability to encrypt critical data and demand ransom for its release. Traditional cybersecurity defenses often fall short against sophisticated ransomware attacks due to their reliance on signature-based detection mechanisms and inadequate preventive measures. This paper introduces RanAway, an innovative solution designed to enhance ransomware resilience by leveraging the advanced features of the Microsoft Resilient File System (ReFS). Unlike conventional file systems, ReFS offers enhanced data integrity, automatic error correction, and robust resistance to data degradation—features that are crucial for mitigating the impact of ransomware attacks. RanAway integrates with ReFS to provide real-time monitoring of file system operations, employing heuristic and behavior-based algorithms to detect and prevent ransomware activities effectively. Our findings demonstrate RanAway's significant potential in reducing the risk of ransomware attacks, highlighting its contributions to the field of cybersecurity through innovative use of file system technologies for threat resilience. The deployment of RanAway represents a paradigm shift towards a more integrated and system-level approach in combating ransomware, offering a blueprint for future developments in cybersecurity defenses.

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“…Researchers fine-tune models like ResNet, InceptionNet, or EfficientNet on Xray images to detect COVID-19. Autoencoders, including convolutional variants, have been utilized to learn compressed representations of normal and COVID-19 X-ray images (Hamid, Iqbal, et al, 2023a). These learned representations can aid in classification tasks.…”

Section: Existing Architecture Frameworkmentioning

confidence: 99%

“…More investigation and discussion are needed on how these circumstances should be handled and how to satisfy both functional and non-functional requirements by resolving them. ML models that are employed to detect COVID-19 may be frequently retrained or adjusted using fresh data (Hamid, Iqbal, et al, 2023b). The model may learn from additional samples of tagged X-ray pictures as they become available, allowing it to detect patterns better and improve detection accuracy.…”

Section: Architecture Evolutionmentioning

confidence: 99%

Analyzing the Software Architecture of ML-based Covid-19 Detection System: Future Challenges and Opportunities

Sabir,

Hassan,

Ittifaq

et al. 2024

BBE

Self Cite

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Two major study topics have emerged because of the challenges in software architecture and ML working together, as modern software systems produce a vast amount of data that is supported particularly by machine learning (ML), and artificial intelligence (AI) to produce useful insights. Software architecture for machine learning systems that primarily concerned with creating architectural methods for creating ML systems more effectively; ii) ML for Software architectures is concerned with creating ML methods for better-developing software systems. This study focuses on the ML-based software systems' architecture to highlight the many architectural methods currently in use. To more clearly identify a set of acceptable standards for designing ML-based software systems, we explore four crucial components of software architecture in this work that demand the focus of ML and software developers. These areas are based on an ML-based software system for addressing challenges in the COVID-19 detecting system.

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Analysis of Techniques for Detection and Removal of Zero-Day Attacks (ZDA)

Cited by 13 publications

References 23 publications

Failures and Repairs: An Examination of Software System Failure

Failures and Repairs: An Examination of Software System Failure

RanAway: A Novel Ransomware-Resilient ReFS File System

Analyzing the Software Architecture of ML-based Covid-19 Detection System: Future Challenges and Opportunities

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