The Experts below are selected from a list of 237 Experts worldwide ranked by ideXlab platform
Yin Xiong - One of the best experts on this subject based on the ideXlab platform.
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project achilles a prototype tool for static method level vulnerability detection of java source code using a recurrent neural network
Automated Software Engineering, 2019Co-Authors: Nicholas Saccente, Josh Dehlinger, Lin Deng, Suranjan Chakraborty, Yin XiongAbstract:Software has become an essential component of modern life, but when software vulnerabilities threaten the security of users, new ways of analyzing for software security must be explored. Using the National Institute of Standards and Technology's Juliet Java Suite, containing thousands of examples of defective Java methods for a variety of vulnerabilities, a prototype tool was developed implementing an array of Long-Short Term Memory Recurrent Neural Networks to detect vulnerabilities within source code. The tool employs various data preparation methods to be independent of coding style and to automate the process of extracting methods, labeling data, and partitioning the dataset. The result is a prototype Command-Line Utility that generates an n-dimensional vulnerability prediction vector. The experimental evaluation using 44,495 test cases indicates that the tool can achieve an accuracy higher than 90% for 24 out of 29 different types of CWE vulnerabilities.
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ASE Workshops - Project Achilles: A Prototype Tool for Static Method-Level Vulnerability Detection of Java Source Code Using a Recurrent Neural Network
2019 34th IEEE ACM International Conference on Automated Software Engineering Workshop (ASEW), 2019Co-Authors: Nicholas Saccente, Josh Dehlinger, Lin Deng, Suranjan Chakraborty, Yin XiongAbstract:Software has become an essential component of modern life, but when software vulnerabilities threaten the security of users, new ways of analyzing for software security must be explored. Using the National Institute of Standards and Technology's Juliet Java Suite, containing thousands of examples of defective Java methods for a variety of vulnerabilities, a prototype tool was developed implementing an array of Long-Short Term Memory Recurrent Neural Networks to detect vulnerabilities within source code. The tool employs various data preparation methods to be independent of coding style and to automate the process of extracting methods, labeling data, and partitioning the dataset. The result is a prototype Command-Line Utility that generates an n-dimensional vulnerability prediction vector. The experimental evaluation using 44,495 test cases indicates that the tool can achieve an accuracy higher than 90% for 24 out of 29 different types of CWE vulnerabilities.
Peter Athron - One of the best experts on this subject based on the ideXlab platform.
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specbit decaybit and precisionbit gambit modules for computing mass spectra particle decay rates and precision observables
European Physical Journal C, 2018Co-Authors: Peter Athron, Csaba Balazs, Lars A Dal, Joakim Edsjo, Ben Farmer, Tomas E Gonzalo, Anders Kvellestad, James MckayAbstract:We present the GAMBIT modules SpecBit, DecayBit and PrecisionBit. Together they provide a new framework for linking publicly available spectrum generators, decay codes and other precision observable calculations in a physically and statistically consistent manner. This allows users to automatically run various combinations of existing codes as if they are a single package. The modular design allows software packages fulfilling the same role to be exchanged freely at runtime, with the results presented in a common format that can easily be passed to downstream dark matter, collider and flavour codes. These modules constitute an essential part of the broader GAMBIT framework, a major new software package for performing global fits. In this paper we present the observable calculations, data, and likelihood functions implemented in the three modules, as well as the conventions and assumptions used in interfacing them with external codes. We also present 3-BIT-HIT, a Command-Line Utility for computing mass spectra, couplings, decays and precision observables in the MSSM, which shows how the three modules can easily be used independently of GAMBIT.
Nicholas Saccente - One of the best experts on this subject based on the ideXlab platform.
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project achilles a prototype tool for static method level vulnerability detection of java source code using a recurrent neural network
Automated Software Engineering, 2019Co-Authors: Nicholas Saccente, Josh Dehlinger, Lin Deng, Suranjan Chakraborty, Yin XiongAbstract:Software has become an essential component of modern life, but when software vulnerabilities threaten the security of users, new ways of analyzing for software security must be explored. Using the National Institute of Standards and Technology's Juliet Java Suite, containing thousands of examples of defective Java methods for a variety of vulnerabilities, a prototype tool was developed implementing an array of Long-Short Term Memory Recurrent Neural Networks to detect vulnerabilities within source code. The tool employs various data preparation methods to be independent of coding style and to automate the process of extracting methods, labeling data, and partitioning the dataset. The result is a prototype Command-Line Utility that generates an n-dimensional vulnerability prediction vector. The experimental evaluation using 44,495 test cases indicates that the tool can achieve an accuracy higher than 90% for 24 out of 29 different types of CWE vulnerabilities.
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ASE Workshops - Project Achilles: A Prototype Tool for Static Method-Level Vulnerability Detection of Java Source Code Using a Recurrent Neural Network
2019 34th IEEE ACM International Conference on Automated Software Engineering Workshop (ASEW), 2019Co-Authors: Nicholas Saccente, Josh Dehlinger, Lin Deng, Suranjan Chakraborty, Yin XiongAbstract:Software has become an essential component of modern life, but when software vulnerabilities threaten the security of users, new ways of analyzing for software security must be explored. Using the National Institute of Standards and Technology's Juliet Java Suite, containing thousands of examples of defective Java methods for a variety of vulnerabilities, a prototype tool was developed implementing an array of Long-Short Term Memory Recurrent Neural Networks to detect vulnerabilities within source code. The tool employs various data preparation methods to be independent of coding style and to automate the process of extracting methods, labeling data, and partitioning the dataset. The result is a prototype Command-Line Utility that generates an n-dimensional vulnerability prediction vector. The experimental evaluation using 44,495 test cases indicates that the tool can achieve an accuracy higher than 90% for 24 out of 29 different types of CWE vulnerabilities.
James Mckay - One of the best experts on this subject based on the ideXlab platform.
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specbit decaybit and precisionbit gambit modules for computing mass spectra particle decay rates and precision observables
European Physical Journal C, 2018Co-Authors: Peter Athron, Csaba Balazs, Lars A Dal, Joakim Edsjo, Ben Farmer, Tomas E Gonzalo, Anders Kvellestad, James MckayAbstract:We present the GAMBIT modules SpecBit, DecayBit and PrecisionBit. Together they provide a new framework for linking publicly available spectrum generators, decay codes and other precision observable calculations in a physically and statistically consistent manner. This allows users to automatically run various combinations of existing codes as if they are a single package. The modular design allows software packages fulfilling the same role to be exchanged freely at runtime, with the results presented in a common format that can easily be passed to downstream dark matter, collider and flavour codes. These modules constitute an essential part of the broader GAMBIT framework, a major new software package for performing global fits. In this paper we present the observable calculations, data, and likelihood functions implemented in the three modules, as well as the conventions and assumptions used in interfacing them with external codes. We also present 3-BIT-HIT, a Command-Line Utility for computing mass spectra, couplings, decays and precision observables in the MSSM, which shows how the three modules can easily be used independently of GAMBIT.
Csaba Balazs - One of the best experts on this subject based on the ideXlab platform.
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specbit decaybit and precisionbit gambit modules for computing mass spectra particle decay rates and precision observables
European Physical Journal C, 2018Co-Authors: Peter Athron, Csaba Balazs, Lars A Dal, Joakim Edsjo, Ben Farmer, Tomas E Gonzalo, Anders Kvellestad, James MckayAbstract:We present the GAMBIT modules SpecBit, DecayBit and PrecisionBit. Together they provide a new framework for linking publicly available spectrum generators, decay codes and other precision observable calculations in a physically and statistically consistent manner. This allows users to automatically run various combinations of existing codes as if they are a single package. The modular design allows software packages fulfilling the same role to be exchanged freely at runtime, with the results presented in a common format that can easily be passed to downstream dark matter, collider and flavour codes. These modules constitute an essential part of the broader GAMBIT framework, a major new software package for performing global fits. In this paper we present the observable calculations, data, and likelihood functions implemented in the three modules, as well as the conventions and assumptions used in interfacing them with external codes. We also present 3-BIT-HIT, a Command-Line Utility for computing mass spectra, couplings, decays and precision observables in the MSSM, which shows how the three modules can easily be used independently of GAMBIT.