Automated Vulnerability Detection in Source Code Using Minimum Intermediate Representation Learning
نویسندگان
چکیده
منابع مشابه
(CLSCR) Cross Language Source Code Reuse Detection Using Intermediate Language
In today's digital era information access is just a click away. so computer science students also have easy access to all the source codes from different websites thus it has become difficult for academicians to detect source code reuse in students programming assignments. The new trend in the area of source code reuse is using the source code by translating it in another programming language p...
متن کاملAutomated software vulnerability detection with machine learning
Thousands of security vulnerabilities are discovered in production software each year, either reported publicly to the Common Vulnerabilities and Exposures database or discovered internally in proprietary code. Vulnerabilities often manifest themselves in subtle ways that are not obvious to code reviewers or the developers themselves. With the wealth of open source code available for analysis, ...
متن کاملUsing Automated Source Code Analysis for Software Evolution
Software maintenance is one of the most expensive and time-consuming phases in the software life-cycle. The size and complexity of commercial applications probably present the greatest difficulty that maintainers face when making changes to their applications. As a result of the corresponding loss of understanding, business knowledge encapsulated within the system becomes fragmented, and any ch...
متن کاملMalicious Code Detection Using Active Learning
The recent growth in network usage has motivated the creation of new malicious code for various purposes, including economic and other malicious purposes. Currently, dozens of new malicious codes are created every day and this number is expected to increase in the coming years. Today’s signature-based anti-viruses and heuristic-based methods are accurate, but cannot detect new malicious code. R...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Applied Sciences
سال: 2020
ISSN: 2076-3417
DOI: 10.3390/app10051692