A5101680618- Advanced Malware Detection Techniques
- Software Engineering Research
- Technology and Data Analysis
- Digital and Cyber Forensics
- Hematological disorders and diagnostics
- Advanced Data Storage Technologies
- Traditional Chinese Medicine Studies
- Anomaly Detection Techniques and Applications
- Adversarial Robustness in Machine Learning
- Covalent Organic Framework Applications
- Software Testing and Debugging Techniques
- Security and Verification in Computing
- Advanced Neural Network Applications
- Metal-Organic Frameworks: Synthesis and Applications
- Software Reliability and Analysis Research
- Algorithms and Data Compression
- Sulfur Compounds in Biology
- Web Applications and Data Management
- Web Application Security Vulnerabilities
- Spam and Phishing Detection
- Network Security and Intrusion Detection
Xi'an Jiaotong University
2020-2025
Ministry of Education of the People's Republic of China
2021
Abstract Separating n‐butane/iso‐butane is a challenging and energy‐intensive task in the petrochemical industry. There have been only several adsorbents reported for C4 paraffins separation while they are confronted real‐world applications with either poor selectivity or low n‐butane uptake capacity. In this study, fluorinated zinc‐based metal‐organic framework (MOF), Znpyc‐CF 3 , derived from Znpyc‐CH developed, which has fluorine‐containing functional groups on pore surface that can...
Software reuse, especially partial poses legal and security threats to software development. Since its source codes are usually unavailable, reuse is hard be detected with interpretation. On the other hand, current approaches suffer from poor detection accuracy efficiency, far satisfying practical demands. To tackle these problems, in this paper, we propose ISRD, an interpretation-enabled approach based on a multi-level birthmark model that contains function level, basic block instruction...
Binary similarity analysis is critical to many code-reuse-related issues, where function matching its fundamental task. “ 1-to-1 ” mechanism has been applied in most binary works, which one a file matched against source or file. However, we discover that the mapping more complex problem of 1-to-n (one matches multiple functions functions) even n-to-n (multiple match due existence inlining , different from traditional understanding. In this article, investigate effect on analysis. We carry...
Binary function similarity detection plays an important role in a wide range of security applications. Existing works usually assume that the query and target share equal semantics compare their full to obtain similarity. However, we find mapping is more complex, especially when inlining happens.
Carefully perturbing adversarial inputs degrades the performance of traditional machine learning (ML) models. Adversarial (AML) that takes adversaries into account during training and emerges as a valid technique to defend against attacks. Due complexity uncertainty adversaries’ attack strategies, researchers utilize game theory study interactions between an adversary ML system designer. By configuring different rules analyzing outcomes in game, it is possible effectively predict strategies...
The great influence of Bitcoin has promoted the rapid development blockchain-based digital currencies, especially altcoins, since 2013. However, most altcoins share similar source codes, resulting in concerns about code innovations. In this paper, an empirical study on existing is carried out to offer a thorough understanding various aspects associated with altcoin Firstly, we construct dataset including repository, GitHub fork relation, and market capitalization (cap). Then, analyze...
Software plagiarism seriously impedes the healthy development of open source software. To fight against code obfuscation and inherent non-determinism thread scheduling applied software detection, we proposed a new dynamic birthmark called DYnamic Key Instruction Sequence (DYKIS) framework Thread-oblivious Birthmark (TOB) for purpose reviving existing birthmarks thread-aware Thread-related System call (TreSB). Though many approaches have been they are still limited to satisfy following highly...
Software vulnerabilities are easily propagated through code reuses, which pose dire threats to software system security. Automatic patch presence test offers an effective way detect whether have been patched, is significant for large-scale maintenance. However, most existing approaches cannot handle binary codes. They suffer from low accuracy and poor efficiency. None of them resilient version gap, function size, size. To tackle the above problems, we propose <i>PatchDiscovery</i> , a...
Deep learning systems are known to be vulnerable adversarial samples, which implemented change the prediction results by adding small perturbations benign samples. It is significant defend against an attack in critical fields such as automatic drive. In this paper, we propose interpretation area-guided detection method of can improve performance typical feature squeezing combining generated results. Specifically, divide input image into two main parts, part, and non-interpretation part. Then...
Software Side Channel Vulnerabilities (SSCVs) cause serious security threats, which introduces a big challenge to software development. With the sustaining growth of complexity and scale, SSCV detection has become tedious work. Existing methods suffer from efficiency, accuracy generality problems, ignore vulnerability variants. Applying machine learning is promising due high efficiency automation, but training an effective model still open issue lack side-channel data. In this paper, we...
Software reuse, especially partial poses legal and security threats to software development. Since its source codes are usually unavailable, reuse is hard be detected with interpretation. On the other hand, current approaches suffer from poor detection accuracy efficiency, far satisfying practical demands. To tackle these problems, in this paper, we propose \textit{ISRD}, an interpretation-enabled approach based on a multi-level birthmark model that contains function level, basic block...