An Intrusion Tracking Watermarking Scheme

Hou, Jun; Li, Qianmu; Tan, Rong; Meng, Shunmei; Zhang, Hanrui; Zhang, Sainan

doi:10.1109/access.2019.2943493

Cited by 19 publications

(7 citation statements)

References 36 publications

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“…Besides, we can see the number of test cases generated by AFL-fuzzer grows steadily as the number of samples increases, because Afl-fuzzer prunes input samples in consideration of that users may offer low-quality initial samples and thus cause the possible data redundancy in some types of variations. Although depending more on the number of samples, the method proposed adopts a more pertinent generation strategy [35][36][37][38][39][40][41][42][43][44][45][46][47][48][49]. Figure 11 shows the coverage rate of code.…”

Section: Methods and Experimentalmentioning

confidence: 99%

A dynamic taint tracking optimized fuzz testing method based on multi-modal sensor data fusion

Liu

Meng

et al. 2020

J Wireless Com Network

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The safety of the Industrial Internet Control Systems has been a hotspot in the information security. To meet the needs of communication, a large variety of proprietary protocols have emerged in the field of industrial control. The protocol field is often trusted in the implementation of industrial control terminal code. If attackers modify the data of these fields using the protocol defect, the operation of the program can be controlled and the entire system will be affected. To cope with such security threats, academia and industry generally adopt fuzz test methods. However, the current industrial control protocol fuzz test methods generally have low code coverage, where unified description models are missing and test cases are not targeted. A method of fuzzification processing combined with dynamic multimodal sensor communication data is proposed. To track the program execution, the dynamic pollution analysis is used to search for the input fields that affect the execution of the conditional branch and capture the dependencies between the conditional branches to guide the grammar generation of test cases, which can increase the chances of executing deep code. The experimental results show that the proposed method improves the validity and code coverage of test cases to a certain extent and greatly increases the probability of anomaly detection in the protocol implementation.

show abstract

Section: Methods and Experimentalmentioning

confidence: 99%

A dynamic taint tracking optimized fuzz testing method based on multi-modal sensor data fusion

Liu

Meng

et al. 2020

J Wireless Com Network

Self Cite

View full text Add to dashboard Cite

show abstract

Section: Methods and Experimentalmentioning

confidence: 99%

A Dynamic Taint Tracking Optimized Fuzz Testing Method based on Multi-modal Sensor Data Fusion

Meng

Zhang

et al. 2020

Preprint

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The safety of Industrial Internet Control Systems has been a hotspot in the information security. To meet needs of communication, a large variety of proprietary protocols have emerged in the field of industrial control. The protocol field is often trusted in the implementation of industrial control terminal code. If attackers modify the data of these fields using the protocol defect, the operation of the program can be controlled and the entire system will be affected. To cope with such security threats, academia and industry generally adopt fuzzy test methods. However, the current industrial control protocol fuzzy test methods generally have low code coverage, where unified description models are missing and test cases are not targeted. A method of fuzzification processing combined with dynamic multi-modal sensor communication data is proposed. To track the program execution, the dynamic pollution analysis is used to search for the input fields that affect the execution of the conditional branch, and capture the dependencies between the conditional branches to guide the grammar generation of test cases, which can increase the chances of executing deep code. The experimental results show that the proposed method improves the validity and code coverage of test cases to a certain extent, and greatly increases the probability of anomaly detection in the protocol implementation.

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“…(2) The user certificate and attributes are not obvious [18,19]. (3) Defects in multi-machine deployment [20][21][22]. This paper uses CouchDB as the user StateStore.…”

Section: User State Storementioning

confidence: 99%

Security Control Components for Epidemic Prevention Donation Management Blockchain

Wang

Hou

et al. 2020

Proceedings of the 2nd ACM International Symposium on Blockchain and Secure Critical Infrastructure

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After the outbreak of the new coronavirus pneumonia, it has been broadcasting soon. Medical supplies are out of used. Chinese people have provided medical supplies and raised donations to help Hubei Province, China. While, Red Cross Society of Hubei Branch and Wuhan Branch were suspected for unfair distribution of donated materials, the backlog of donated items, and inefficient assignment. These problems exposed public welfare organizations to the public sights. For information sharing, Jiangsu Province developed a new COVID-19 Donation Management Blockchain System (CDMBS). The system improves the transparency and credibility of donation information with the blockchain. Based on the overall architecture of Jiangsu's new coronavirus charity donation management blockchain, this paper designs various types of security control components. The components include the middleware for secure connection to protect the user certificate security. We designed CA certificate user management middleware to realize more secure registration and query functions for users with extended attributes. There is also a blockchain query middle with access control Software to ensure that important blockchain information is viewed securely. Experiments have verified the effectiveness and applicability of these security control components. It can be applied into a variety of scenarios in the CDMBS.

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An Intrusion Tracking Watermarking Scheme

Cited by 19 publications

References 36 publications

A dynamic taint tracking optimized fuzz testing method based on multi-modal sensor data fusion

A dynamic taint tracking optimized fuzz testing method based on multi-modal sensor data fusion

A Dynamic Taint Tracking Optimized Fuzz Testing Method based on Multi-modal Sensor Data Fusion

Security Control Components for Epidemic Prevention Donation Management Blockchain

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