ESEC/FSE 2019 – DISCOVER: Detecting Algorithmic Complexity Vulnerabilities
Abstract: Algorithmic Complexity Vulnerabilities (ACV) are a class of vulnerabilities that enable Denial of Service Attacks. ACVs stem from asymmetric consumption of resources due to complex loop termination logic, recursion, and/or resource intensive library APIs. Completely automated detection of ACVs is intractable and it calls for tools that assist human analysts. We present DISCOVER, a […]
ICSE 2019 – Mockingbird: A Framework for Enabling Targeted Dynamic Analysis of Java Programs
Abstract: The paper presents the Mockingbird framework that combines static and dynamic analyses to yield an efficient and scalable approach to analyze large Java software. The framework is an innovative integration of existing static and dynamic analysis tools and a newly developed component called the Object Mocker that enables the integration. The static analyzers are […]
Science of Computer Programming – Projected Control Graph for Computing Relevant Program Behaviors
Abstract: Many software engineering tasks require analysis and verification of all behaviors relevant to the task. For example, all relevant behaviors must be analyzed to verify a safety or security property. An efficient algorithm must compute the relevant behaviors directly without computing all the behaviors. This is crucial in practice because it is computationally intractable […]
DySDoc3 – DynaDoc: Automated On-Demand Context-Specific Documentation
Abstract: This 2018 DOCGEN Challenge paper describes DynaDoc, an automated documentation system for on-demand context-specific documentation. A key novelty is the use of graph database technology with an eXtensible Common Software Graph Schema (XCSG). Using XCSG-based query language, DynaDoc can mine efficiently and accurately a variety of program artifacts and graph abstractions from millions of […]
ICSE 2018 – Demystifying Cyber-Physical Malware
Abstract: The traditional notion of malware is too narrow, and the prevalent characterizations (virus, worm, trojan horse, spyware etc.) are neither precise nor comprehensive enough to characterize cyber-physical malware (CPM). Detecting sophisticated CPM is like searching for a needle in the haystack without knowing what the needle looks like. This technical briefing congregates interdisciplinary knowledge […]
ICSE 2018 – COMB: Computing Relevant Program Behaviors
Abstract: The paper presents COMB, a tool to improve accuracy and efficiency of software engineering tasks that hinge on computing all relevant program behaviors. Computing all behaviors and selecting the relevant ones is computationally intractable. COMB uses Projected Control Graph (PCG) abstraction to derive the relevant behaviors directly and efficiently. The PCG is important as […]
ICISS 2017 – Human-on-the-loop Automation for Detecting Software Side-Channel Vulnerabilities
Abstract: Software side-channel vulnerabilities (SSCVs) allow an attacker to gather secrets by observing the differential in the time or space required for executing the program for different inputs. Detecting SSCVs is like searching for a needle in the haystack, not knowing what the needle looks like. Detecting SSCVs requires automation that supports systematic exploration to […]
APSEC 2017 – Intelligence Amplifying Loop Characterizations for Detecting Algorithmic Complexity Vulnerabilities
Abstract: Algorithmic complexity vulnerabilities (ACVs) can be exploited to cause denial-of-service. Detecting ACVs is hard because of the numerous kinds of loop complexities that cause ACVs. This renders automatic detection intractable for ACVs. State-of-the-art loop analyses aim to obtain precise loop iteration bounds automatically; they can do so for relatively simple loops. This research focuses […]
2017 Winter Simulation Conference – Modeling Lessons from Verifying Large Software Systems for Safety and Security
Abstract: Verifying software in mission-critical Cyber-Physical Systems (CPS) is an important but daunting task with challenges of accuracy and scalability. This paper discusses lessons learned from verifying properties of the Linux kernel. These lessons have raised questions about traditional verification approaches, and have led us to a model-based approach for software verification. These models are […]
VizSec 2017 – Interactive Visualization Toolbox to Detect Sophisticated Android Malware
Abstract: Detecting zero-day sophisticated malware is like searching for a needle in the haystack, not knowing what the needle looks like. This paper describes Android Malicious Flow Visualization Toolbox that empowers a human analyst to detect such malware. Detecting sophisticated malware requires systematic exploration of the code to identify potentially malignant code, conceiving plausible malware […]