Research on Mobile Application Local Denial of Service Vulnerability Detection Technology Based on Rule Matching

Cross-site scripting vulnerabilities are among the top ten security vulnerabilities affecting web applications for the past decade and mobile version web applications more recently. They can cause serious problems for web users such as loss of personal information to web attackers, including financial and health information, denial of service attacks, and exposure to malware and viruses. Most of the proposed solutions focused only on the Desktop versions of web applications and overlooked the mobile versions. Increasing use of mobile phones to access web applications increases the threat of cross-site scripting attacks on mobile phones. This paper presents work in progress on detecting cross-site scripting vulnerabilities in mobile versions of web applications. It proposes an enhanced genetic algorithm-based approach that detects cross-site scripting vulnerabilities in mobile versions of web applications. This approach has been used in our previous work and successfully detected the said vulnerabilities in Desktop web applications. It has been enhanced and is currently being tested in mobile versions of web applications. Preliminary results have indicated success in the mobile versions of web applications also. This approach will enable web developers find cross-site scripting vulnerabilities in the mobile versions of their web applications before their release.

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A Heuristic Local-sensitive Program-Wide Diffing Method for IoT Binary Files

Arabian Journal for Science and Engineering ◽

10.1007/s13369-021-06342-8 ◽

2021 ◽

Author(s):

Lu Yu ◽

Yuliang Lu ◽

Yi Shen ◽

Zulie Pan ◽

Hui Huang

Keyword(s):

Denial Of Service ◽

Third Party ◽

Semantic Features ◽

Proof Of Concept ◽

Vulnerability Detection ◽

Source Codes ◽

Flow Dependence ◽

Iot Devices ◽

The Impact ◽

Earth Mover

AbstractCode reuse brings vulnerabilities in third-party library to many Internet of Things (IoT) devices, opening them to attacks such as distributed denial of service. Program-wide binary diffing technology can help detect these vulnerabilities in IoT devices whose source codes are not public. Considering the architectures of IoT devices may vary, we propose a data-aware program-wide diffing method across architectures and optimization levels. We rely on the defined anchor functions and call relationship to expand the comparison scope within the target file, reducing the impact of different architectures on the diffing result. To make the diffing result more accurate, we extract the semantic features that can represent the code by data flow dependence analysis. Earth mover distance is used to calculate the similarity of functions in two files based on semantic features. We implemented a proof-of-concept DAPDiff and compared it with baseline BinDiff, TurboDiff and Asm2vec. Experiments showed the availability and effectiveness of our method across optimization levels and architectures. DAPDiff outperformed BinDiff in recall and precision by 41.4% and 9.2% on average when making diffing between standard third-party library and the real-world firmware files. This proves that DAPDiff can be applicable for the vulnerability detection in IoT devices.

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Research on A Vulnerability Detection Technology for Network Topology Security

10.1109/nana53684.2021.00064 ◽

2021 ◽

Author(s):

Jianxin Ji ◽

Chunli Xia ◽

Tong Zhang ◽

Yichuan Wang ◽

Sheng Liu

Keyword(s):

Network Topology ◽

Vulnerability Detection ◽

Detection Technology

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PSOFuzzer: A Target-Oriented Software Vulnerability Detection Technology Based on Particle Swarm Optimization

Applied Sciences ◽

10.3390/app11031095 ◽

2021 ◽

Vol 11 (3) ◽

pp. 1095

Author(s):

Chen Chen ◽

Han Xu ◽

Baojiang Cui

Keyword(s):

Particle Swarm Optimization ◽

Particle Swarm ◽

Target Point ◽

Vulnerability Detection ◽

High Quality ◽

Swarm Optimization ◽

Detection Technology ◽

Test Process ◽

Quality Features ◽

Historical Samples

Coverage-oriented and target-oriented fuzzing are widely used in vulnerability detection. Compared with coverage-oriented fuzzing, target-oriented fuzzing concentrates more computing resources on suspected vulnerable points to improve the testing efficiency. However, the sample generation algorithm used in target-oriented vulnerability detection technology has some problems, such as weak guidance, weak sample penetration, and difficult sample generation. This paper proposes a new target-oriented fuzzer, PSOFuzzer, that uses particle swarm optimization to generate samples. PSOFuzzer can quickly learn high-quality features in historical samples and implant them into new samples that can be led to execute the suspected vulnerable point. The experimental results show that PSOFuzzer can generate more samples in the test process to reach the target point and can trigger vulnerabilities with 79% and 423% higher probability than AFLGo and Sidewinder, respectively, on tested software programs.

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Research on software security vulnerability detection technology

Proceedings of 2011 International Conference on Computer Science and Network Technology ◽

10.1109/iccsnt.2011.6182335 ◽

2011 ◽

Cited By ~ 1

Author(s):

Liu Ping ◽

Su Jin ◽

Yang Xinfeng

Keyword(s):

Software Security ◽

Vulnerability Detection ◽

Security Vulnerability ◽

Detection Technology

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NETWORK DEFENSE SYSTEM MONITORING THROUGH A MOBILE APPLICATION

IT for Society ◽

10.33021/itfs.v4i2.1185 ◽

2020 ◽

Vol 4 (2) ◽

Author(s):

Lalu Muhammad Aryandi Azrin ◽

Abdul Ghofir

Keyword(s):

Mobile Device ◽

Mobile Application ◽

Denial Of Service ◽

Defense System ◽

System Monitoring ◽

Network Defense ◽

Computer Attacks ◽

Log Management ◽

Log File

paper proposed a way to secure and protect pc or laptop remotely via mobile device. These two device communicate by exchanging information or data using database connection. There will be two applications that are developed, windows-based application and mobile application. The proposed scheme used some firewall configuration and log management to complete the process. The firewall configuration will block computer attacks such as Denial of Service. Log management is to generate a specific log file if there is a possible threat. It will then invoke. the windows application to update the database which is regularly accessed by mobile application. It then alerts user on possible attack or threat.

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