With the increasing use of web applications,challenges in the field of cybersecurity are becoming more complex.This paper explores the application of fine-tuned large language models(LLMs)for the automatic generation ...With the increasing use of web applications,challenges in the field of cybersecurity are becoming more complex.This paper explores the application of fine-tuned large language models(LLMs)for the automatic generation of synthetic attacks,including XSS(Cross-Site Scripting),SQL Injections,and Command Injections.A web application has been developed that allows penetration testers to quickly generate high-quality payloads without the need for in-depth knowledge of artificial intelligence.The fine-tuned language model demonstrates the capability to produce synthetic payloads that closely resemble real-world attacks.This approach not only improves the model’s precision and dependability but also serves as a practical resource for cybersecurity professionals to enhance the security of web applications.The methodology and structured implementation underscore the importance and potential of advanced language models in cybersecurity,illustrating their effectiveness in generating high-quality synthetic data for penetration testing purposes.The research results demonstrate that this approach enables the identification of vulnerabilities that traditional methods may not uncover,providing deeper insights into potential threats and enhancing overall security measures.The performance evaluation of the model indicated satisfactory results,while further hyperparameter optimization could improve accuracy and generalization capabilities.This research represents a significant step forward in improving web application security and opens new opportunities for the use of LLMs in security testing,thereby contributing to the development of more effective cybersecurity strategies.展开更多
The depletion of fossil diesel fuels, global warming concerns and strict limits on regulated pollutant emissions are encouraging the use of renewable fuels. Biodiesel is the most used renewable fuel in compression ign...The depletion of fossil diesel fuels, global warming concerns and strict limits on regulated pollutant emissions are encouraging the use of renewable fuels. Biodiesel is the most used renewable fuel in compression ignition (CI) engine. The majority of literature agrees that the particulate matter (PM), unburnt total hydrocarbons (THC) and carbon dioxide (CO) emission from biodiesel are lower than from conventional diesel fuel. One of the most important reasons for this is the oxygen content of the biodiesel. This induces a more complete and cleaner combustion process. In addition to this the absence of aromatic compounds in biodiesel leads to particulate matter reduction with respect to diesel fuel. The potential emission benefits induced by the presence of oxygen in fuel molecules has increased the interest in using the bio-alcohols fuel blends in CI engines such as ethanol. Although alcohols are more suitable for blending with diesel fuel, properties like lubricity, viscosity, stability, heating value and cetane number of diesel-alcohol (Diesohol) still require improvement. One of the techniques is addition of biodiesel which can improve all of these properties forming diesel-biodiesel-alcohol (ternary) blends. The blends of diesel-biodiesel-ethanol can be used in the existing CI engines without any major modifications and most significant result of using this blend is the lower emission with almost the same performance as of diesel fuel alone. The present study focused on investigation of performance and combustion characteristics of ternary fuel blend in DI diesel engine operating at different injection opening pressure (IOP). The different injection opening pressures are: 180 bar, 200 bar and 220 bar.展开更多
基金supported by the Ministry of Science,Technological Development and Innovation of the Republic of Serbia,and these results are parts of Grant No.451-03-66/2024-03/200132 with the University of Kragujevac-Faculty of Technical Sciences Cacak.
文摘With the increasing use of web applications,challenges in the field of cybersecurity are becoming more complex.This paper explores the application of fine-tuned large language models(LLMs)for the automatic generation of synthetic attacks,including XSS(Cross-Site Scripting),SQL Injections,and Command Injections.A web application has been developed that allows penetration testers to quickly generate high-quality payloads without the need for in-depth knowledge of artificial intelligence.The fine-tuned language model demonstrates the capability to produce synthetic payloads that closely resemble real-world attacks.This approach not only improves the model’s precision and dependability but also serves as a practical resource for cybersecurity professionals to enhance the security of web applications.The methodology and structured implementation underscore the importance and potential of advanced language models in cybersecurity,illustrating their effectiveness in generating high-quality synthetic data for penetration testing purposes.The research results demonstrate that this approach enables the identification of vulnerabilities that traditional methods may not uncover,providing deeper insights into potential threats and enhancing overall security measures.The performance evaluation of the model indicated satisfactory results,while further hyperparameter optimization could improve accuracy and generalization capabilities.This research represents a significant step forward in improving web application security and opens new opportunities for the use of LLMs in security testing,thereby contributing to the development of more effective cybersecurity strategies.
文摘The depletion of fossil diesel fuels, global warming concerns and strict limits on regulated pollutant emissions are encouraging the use of renewable fuels. Biodiesel is the most used renewable fuel in compression ignition (CI) engine. The majority of literature agrees that the particulate matter (PM), unburnt total hydrocarbons (THC) and carbon dioxide (CO) emission from biodiesel are lower than from conventional diesel fuel. One of the most important reasons for this is the oxygen content of the biodiesel. This induces a more complete and cleaner combustion process. In addition to this the absence of aromatic compounds in biodiesel leads to particulate matter reduction with respect to diesel fuel. The potential emission benefits induced by the presence of oxygen in fuel molecules has increased the interest in using the bio-alcohols fuel blends in CI engines such as ethanol. Although alcohols are more suitable for blending with diesel fuel, properties like lubricity, viscosity, stability, heating value and cetane number of diesel-alcohol (Diesohol) still require improvement. One of the techniques is addition of biodiesel which can improve all of these properties forming diesel-biodiesel-alcohol (ternary) blends. The blends of diesel-biodiesel-ethanol can be used in the existing CI engines without any major modifications and most significant result of using this blend is the lower emission with almost the same performance as of diesel fuel alone. The present study focused on investigation of performance and combustion characteristics of ternary fuel blend in DI diesel engine operating at different injection opening pressure (IOP). The different injection opening pressures are: 180 bar, 200 bar and 220 bar.
