Related papers: How to Find Actionable Static Analysis Warnings: A…

Android is present in more than 85% of mobile devices, making it a prime target for malware. Malicious code is becoming increasingly sophisticated and relies on logic bombs to hide itself from dynamic analysis. In this paper, we perform a…

A widespread belief in the blockchain security community is that automated techniques are only good for detecting shallow bugs, typically of small value. In this paper, we present the techniques and insights that have led us to repeatable…

Eliminating vulnerabilities from low-level code is vital for securing software. Static analysis is a promising approach for discovering vulnerabilities since it can provide developers early feedback on the code they write. But, it presents…

We propose a new static approach to Role-Based Access Control (RBAC) policy enforcement. The static approach we advocate includes a new design methodology, for applications involving RBAC, which integrates the security requirements into the…

The main stretch in the paper is buffer overflow anomaly occurring in major source codes, designed in various programming language. It describes the various as to how to improve your code and increase its strength to withstand security…

Neural networks are increasingly applied to support decision making in safety-critical applications (like autonomous cars, unmanned aerial vehicles and face recognition based authentication). While many impressive static verification…

Active learning algorithms automatically identify the most informative samples from large amounts of unlabeled data and tremendously reduce human annotation effort in inducing a machine learning model. In a conventional active learning…

A framework is introduced for actively and adaptively solving a sequence of machine learning problems, which are changing in bounded manner from one time step to the next. An algorithm is developed that actively queries the labels of the…

In this work, we propose an automated method to identify semantic bugs in student programs, called ATAS, which builds upon the recent advances in both symbolic execution and active learning. Symbolic execution is a program analysis…

Adversarial attacks pose significant challenges for detecting adversarial attacks at an early stage. We propose attack-agnostic detection on reinforcement learning-based interactive recommendation systems. We first craft adversarial…

Deep learning vulnerability detection tools are increasing in popularity and have been shown to be effective. These tools rely on large volume of high quality training data, which are very hard to get. Most of the currently available…

Static analysis is a powerful technique for automatic verification of programs but raises major engineering challenges when developing a full-fledged analyzer for a realistic language such as Java. This paper describes the Sawja library: a…

The widespread adoption of smartphones dramatically increases the risk of attacks and the spread of mobile malware, especially on the Android platform. Machine learning-based solutions have been already used as a tool to supersede…

This paper describes how to adapt a static code analyzer to help novice programmers. Current analyzers have been built to give feedback to experienced programmers who build new applications or systems. The type of feedback and the type of…

Industry can get any research it wants, just by publishing a baseline result along with the data and scripts need to reproduce that work. For instance, the paper ``Data Mining Static Code Attributes to Learn Defect Predictors'' presented…

Evaluating the correctness of code generated by AI is a challenging open problem. In this paper, we propose a fully automated method, named ACCA, to evaluate the correctness of AI-generated code for security purposes. The method uses…

Static analysis of structures is a fundamental step for determining the stability of structures. Both linear and non-linear static analyses consist of the resolution of sparse linear systems obtained by the finite element method. The…

Fix pattern-based patch generation is a promising direction in Automated Program Repair (APR). Notably, it has been demonstrated to produce more acceptable and correct patches than the patches obtained with mutation operators through…

Java static analysis frameworks are commonly compared under the assumption that analysis algorithms and configurations compose monotonically and yield semantically comparable results across tools. In this work, we show that this assumption…

Context: Data miners have been widely used in software engineering to, say, generate defect predictors from static code measures. Such static code defect predictors perform well compared to manual methods, and they are easy to use and…