55 citations · 75 across the 18 of their papers we have counts for
19 papers
Escaping Python Dependency Hell: A Hybrid Replay-and-Repair Pipeline for Python Dependency Resolution
Veronica Poweska, Ariana Oyanguren, Jessica Pourleyli +2
Dependency conflicts in Python ecosystems arise from incompatible version constraints, missing packages, and undocumented compatibility relationships, causing many real-world code…
Selective Forgetting: A Graph-Based Memory Framework for Long-Term LLM Agents
Theo Rusu, Sourena Khanzadeh, Manar Alalfi
Knowledge graphs have been proposed as a structured alternative to flat retrieval-augmented generation for long-term agent memory, on the assumption that representing conversations…
Cracking IoT Security: Can LLMs Outsmart Static Analysis Tools?
Jason Quantrill, Noura Khajehnouri, Zihan Guo +1
Smart home IoT platforms such as openHAB rely on Trigger Action Condition (TAC) rules to automate device behavior, but the interplay among these rules can give rise to interaction…
Taught by the Flawed: How Dataset Insecurity Breeds Vulnerable AI Code
Catherine Xia, Manar H. Alalfi
AI programming assistants have demonstrated a tendency to generate code containing basic security vulnerabilities. While developers are ultimately responsible for validating and re…
GitHub's Copilot Code Review: Can AI Spot Security Flaws Before You Commit?
Amena Amro, Manar H. Alalfi
As software development practices increasingly adopt AI-powered tools, ensuring that such tools can support secure coding has become critical. This study evaluates the effectivenes…
SimSched: A tool for Simulating Autosar Implementaion in Simulink
Jian Chen, Manar H. Alalfi, Thomas R. Dean +1
AUTOSAR (AUTomotive Open System ARchitecture) is an open industry standard for the automotive sector. It defines the three-layered automotive software architecture. One of these la…
Opti Code Pro: A Heuristic Search-based Approach to Code Refactoring
Sourena Khanzadeh, Samad Alias Nyein Chan, Richard Valenzano +1
This paper presents an approach that evaluates best-first search methods to code refactoring. The motivation for code refactoring could be to improve the design, structure, or impl…
Timed Model-Based Mutation Operators for Simulink Models
Jian Chen, Manar H. Alalfi, Thomas R. Dean
Model-based mutation analysis is a recent research area, and real-time system testing can benefit from using model mutants. Model-based mutation testing (MBMT) is a particular bran…
A Model-Driven-Engineering Approach for Detecting Privilege Escalation in IoT Systems
Atheer Abu Zaid, Manar H. Alalfi, Ali Miri
Software vulnerabilities in access control models can represent a serious threat in a system. In fact, OWASP lists broken access control as number 5 in severity among the top 10 vu…
A Survey of Analysis Methods for Security and Safety verification in IoT Systems
Lobna Abuserrieh, Manar H. Alalfi
Internet of Things (IoT) has been rapidly growing in the past few years in all life disciplines. IoT provides automation and smart control to its users in different domains such as…
Mining Domain Models in Ethereum DApps using Code Cloning
Noama Fatima Samreen, Manar H. Alalfi
This research study explores the use of near-miss clone detection to support the characterization of domain models of smart contracts for each of the popular domains in which smart…
VOLCANO: Detecting Vulnerabilities of Ethereum Smart Contracts Using Code Clone Analysis
Noama Fatima Samreen, Manar H. Alalfi
Ethereum Smart Contracts based on Blockchain Technology (BT) enables monetary transactions among peers on a blockchain network independent of a central authorizing agency. Ethereum…
An Automated Approach for Privacy Leakage Identification in IoT Apps
Bara' Nazzal, Manar H. Alalfi
This paper presents a fully automated static analysis approach and a tool, Taint-Things, for the identification of tainted flows in SmartThings IoT apps. Taint-Things accurately id…
Predicting sensitive information leakage in IoT applications using flows-aware machine learning approach
Hajra Naeem, Manar H. Alalfi
This paper presents an approach for identification of vulnerable IoT applications. The approach focuses on a category of vulnerabilities that leads to sensitive information leakage…
A Mutation Framework for Evaluating Security Analysis tools in IoT Applications
Manar H. Alalfi, Sajeda Parveen, Bara Nazzal
With the growing and widespread use of Internet of Things (IoT) in our daily life, its security is becoming more crucial. To ensure information security, we require better security…
SmartScan: An approach to detect Denial of Service Vulnerability in Ethereum Smart Contracts
Noama Fatima Samreen, Manar H. Alalfi
Blockchain technology (BT) Ethereum Smart Contracts allows programmable transactions that involve the transfer of monetary assets among peers on a BT network independent of a centr…
A Survey of Security Vulnerabilities in Ethereum Smart Contracts
Noama Fatima Samreen, Manar H. Alalfi
Ethereum Smart Contracts based on Blockchain Technology (BT)enables monetary transactions among peers on a blockchain network independent of a central authorizing agency. Ethereum…
Reentrancy Vulnerability Identification in Ethereum Smart Contracts
Noama Fatima Samreen, Manar H. Alalfi
Ethereum Smart contracts use blockchain to transfer values among peers on networks without central agency. These programs are deployed on decentralized applications running on top…
An Approach for the Identification of Information Leakage in Automotive Infotainment systems
Abdul Moiz, Manar H. Alalfi
The advancements in the digitization world has revolutionized the automotive industry. Today's modern cars are equipped with internet, computers that can provide autonomous driving…