Junaid Akram

Software security research & supervision

Advancing software security through source-code analysis, testing, and vulnerability research.

Led by Dr Junaid Akram at COMSATS University Islamabad, Lahore Campus, the SCSA Lab develops practical methods and tools for vulnerability detection, malware analysis, code-clone analysis, and automated software testing.

Postdoctoral research at SnT, University of Luxembourg
PhD from Tsinghua University
HEC-approved PhD Supervisor

Google Scholar COMSATS Profile

Explore Research Supervision Directory

Junaid Akram, PhDAssistant ProfessorCOMSATS University Islamabad, Lahore Campus

324B+Lines of Code IndexedHadoop IBFET code-clone analysis study

152,823+Repositories AnalyzedSQVDT open-source vulnerability platform

30,500+Android Apps AnalyzedDroidSD similarity detection evaluation

Interactive Vulnerability Inspection

Live AST Code Analysis & Remediation

SCSA Static Analysis Engine v2.4.0
// SCSA AUDITED & REMEDIATED CODE
void parse_input(const char *user_str) {
    char buffer[64];
    // Fixed: Bounded copy with null-termination
    if (snprintf(buffer, sizeof(buffer), "%s", user_str) >= sizeof(buffer)) {
        log_security_alert("Buffer truncation detected", user_str);
        return;
    }
    process_data(buffer);
}
Tool: SQVDT Core EngineCVE Ref: CVE-2024-30192Latency: 4.2 ms
Pass — Memory Safe

Research domains

Focused on practical software-security problems

View all research

01Explore Roadmap

Cyber Security

Source-level assessment methods for identifying, understanding, and mitigating software vulnerabilities.

02Explore Roadmap

Vulnerability Detection

Scalable techniques and tools that trace vulnerable code through patches, fingerprints, and code similarity.

03Explore Roadmap

Software Testing

Search-based testing, automated test-data generation, regression testing, and test-smell detection.

04Explore Roadmap

Malware Detection

Static and learning-based analysis of Android and cross-architecture malware at source-code level.

05Explore Roadmap

Code Clone Analysis

Large-scale detection of exact, near-miss, and obfuscated code clones across software systems.

06Explore Roadmap

Software Evolution & Reuse

Understanding how code, vulnerabilities, and reusable components propagate between systems.

Research Methodology

How Our Research Works

How our lab transforms source code repositories, patch data, and test suites into verified security benchmarks, published research, and student production systems.

SCSA Core Engine

Static Analysis · Vulnerability Scanning · Clone Detection

324B+ Lines Indexed

Source EvidenceINPUT

git clone & cve_parse_patch()

152,823+ Open Source Repositories

Security ToolsSQVDT

Vulnerability detection & obfuscation analyzer tools

99.4% Accuracy

PublicationsQ1 JOURNAL

Applied Soft Computing & IEEE Security papers

25+ Papers Published

Innovation & ImpactIMPACT

Practical contribution to researchers, developers, industry, and society

Supervision & Security Platforms

Full automated flow from code collection to publication & project deployment

View complete research architecture

Publications

Selected research output

View all publications

2025

An Advanced Ensemble Framework for Defending Against Obfuscated Windows, Android, and IoT Malware

Applied Soft Computing, Volume 173, 112908

2022

Obfuscated Code is Identifiable by a Token Based Clone Detection Technique

International Journal of Information and Computer Security, 19(3–4), 254–273

2021

DroidMD: An Efficient and Scalable Android Malware Detection Approach at Source Code Level

International Journal of Information and Computer Security, 16(3/4)

2021

SQVDT: Scalable Quantitative Vulnerability Detection Technique for Source Code Security Assessment

Software: Practice and Experience, 51(2), 294–318

Supervision

Research project supervision

Explore supervision directory

Fall 2020

Analysis and Detection of Fraudulent Transactions Using the PaySim Financial Simulator

Ouyang NingJing

Xiamen University Malaysia

Fall 2020

Malware Feature Extraction of Instruction Frequency

Wang Xiaowei

Xiamen University Malaysia

Fall 2020

Malware Feature Extraction via Machine Learning Algorithm

Eilsen Law Yi Sheng

Xiamen University Malaysia

Spring 2021

ElderlyCare — an Android-based Elderly Health Assistance Application

Chen WenLong

Xiamen University Malaysia

Collaborate with SCSA Lab

Interested in software security research or student supervision?

Dr Junaid Akram supervises BS, MS, and PhD students in software vulnerability detection, automated testing, malware analysis, and code clone research.

Contact the lab

Academic and research affiliations