Vehicular crowdsourcing networks (VCNs) enable vehicles to provide or obtain traffic-related services in a costefficient and flexible manner. Therefore, it is crucial to provide trusted management in VCNs for high reliability towards both service producers and consumers. However, most recent VCN platforms rely on a third party to manage crowdsourcing services which might be not fully trusted by users. For the issue, this paper proposes a blockchain-based trust management scheme for VCNs to provide a decentralized and trusted service management. A comprehensive trust evaluation model (TEM) is designed to quantify the trust degree of each vehicular node, and a vehicle-trust blockchain framework called VTchain is proposed to preserve the trust values of nodes while guaranteeing transparency and trustworthiness. Particularly, we leverage a trusted execution environment (TEE) to provide secure trust evaluation to tackle possible untrusted road-side units. In addition, we introduce TEM-based Proof of Trust to support blockchain maintenance, which works together with an efficient consensus algorithm Zyzzyva for improved scalability. Finally, extensive experiments are conducted by developing a testbed deployed on cloud servers for measurements.
{"title":"A Blockchain-based Vehicle-trust Management Framework Under a Crowdsourcing Environment","authors":"Dawei Wang, Xiao Chen, Haiqin Wu, Ruozhou Yu, Yishi Zhao","doi":"10.1109/TrustCom50675.2020.00266","DOIUrl":"https://doi.org/10.1109/TrustCom50675.2020.00266","url":null,"abstract":"Vehicular crowdsourcing networks (VCNs) enable vehicles to provide or obtain traffic-related services in a costefficient and flexible manner. Therefore, it is crucial to provide trusted management in VCNs for high reliability towards both service producers and consumers. However, most recent VCN platforms rely on a third party to manage crowdsourcing services which might be not fully trusted by users. For the issue, this paper proposes a blockchain-based trust management scheme for VCNs to provide a decentralized and trusted service management. A comprehensive trust evaluation model (TEM) is designed to quantify the trust degree of each vehicular node, and a vehicle-trust blockchain framework called VTchain is proposed to preserve the trust values of nodes while guaranteeing transparency and trustworthiness. Particularly, we leverage a trusted execution environment (TEE) to provide secure trust evaluation to tackle possible untrusted road-side units. In addition, we introduce TEM-based Proof of Trust to support blockchain maintenance, which works together with an efficient consensus algorithm Zyzzyva for improved scalability. Finally, extensive experiments are conducted by developing a testbed deployed on cloud servers for measurements.","PeriodicalId":221956,"journal":{"name":"2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129262635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-01DOI: 10.1109/TrustCom50675.2020.00132
Zhujun Zhang, Dali Zhu, Weiping Fan
Practical Byzantine Fault Tolerance (PBFT) is an optional consensus protocol for consortium blockchains scenarios where strong consistency is required. However, it also inevitably incurs high energy consumption, low efficiency and poor scalability. What is more, the reliability of the consensus node cannot be guaranteed by itself. For addressing these problems, this paper proposes practical byzantine consensus algorithm based on quantified-role (QPBFT), which can achieve the following advantages: (1) Improving the security and reliability of the blockchain. The reliability attributes of nodes are quantified based on analytic hierarchy process (AHP), those nodes with high reliability evaluation scores are more likely to participate in block production by introduction of the quantified-role, which can ensure the reliability of blockchain network; (2) Realizing high efficiency and low energy consumption. Voting mechanism is adopted to simplify and optimize the PBFT consensus process; (3) Implementing adaptation to dynamic network environments. Management nodes, voting nodes, candidate nodes, and ordinary nodes are dynamically adjusted according to node reliability evaluation score for optimizing consensus performance. The paper demonstrates the security feature including reliability and fault tolerance. Meanwhile, simulation experiments are conducted to validate the higher efficiency and less resource consumption of QPBFT compared with PBFT.
{"title":"QPBFT: Practical Byzantine Fault Tolerance Consensus Algorithm Based on Quantified-role","authors":"Zhujun Zhang, Dali Zhu, Weiping Fan","doi":"10.1109/TrustCom50675.2020.00132","DOIUrl":"https://doi.org/10.1109/TrustCom50675.2020.00132","url":null,"abstract":"Practical Byzantine Fault Tolerance (PBFT) is an optional consensus protocol for consortium blockchains scenarios where strong consistency is required. However, it also inevitably incurs high energy consumption, low efficiency and poor scalability. What is more, the reliability of the consensus node cannot be guaranteed by itself. For addressing these problems, this paper proposes practical byzantine consensus algorithm based on quantified-role (QPBFT), which can achieve the following advantages: (1) Improving the security and reliability of the blockchain. The reliability attributes of nodes are quantified based on analytic hierarchy process (AHP), those nodes with high reliability evaluation scores are more likely to participate in block production by introduction of the quantified-role, which can ensure the reliability of blockchain network; (2) Realizing high efficiency and low energy consumption. Voting mechanism is adopted to simplify and optimize the PBFT consensus process; (3) Implementing adaptation to dynamic network environments. Management nodes, voting nodes, candidate nodes, and ordinary nodes are dynamically adjusted according to node reliability evaluation score for optimizing consensus performance. The paper demonstrates the security feature including reliability and fault tolerance. Meanwhile, simulation experiments are conducted to validate the higher efficiency and less resource consumption of QPBFT compared with PBFT.","PeriodicalId":221956,"journal":{"name":"2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116769254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-01DOI: 10.1109/TrustCom50675.2020.00209
Hongzhaoning Kang, Gang Liu, Quan Wang, Runnan Zhang, Zichao Zhong, Yu-min Tian
As a widely recognized policy language of access control, the eXtensible Access Control Markup Language (XACML) is widely used with its fine-grained and easy-to-read. With the application of XACML, researchers find that the XACML based policy evaluation and policy management methods can no longer meet the current large-scale requests for efficient access and dynamic management requirements. To improve the performance of policy evaluation based on XACML, we propose a policy evaluation method based on the matching tree to search policy efficiently and avoid the extra consumption of invalid policy participation. Furthermore, we propose a policy dynamic management method based on the matching tree to reduce the scale of the policy to be disabled for management, by adding locks in the tree node and the information mapping table. Through theoretical derivation and the factors that may affect its evaluation performance, we verify the improvement of evaluation efficiency. The simulation also shows the improvement of the evaluation engine based on the matching tree compared with OuenAz.
XACML (eXtensible access control Markup language，可扩展访问控制标记语言)是一种被广泛认可的访问控制策略语言，它具有细粒度和易于阅读的特点，被广泛使用。随着XACML的应用，研究人员发现基于XACML的策略评估和策略管理方法已经不能满足当前大规模高效访问和动态管理的要求。为了提高基于XACML的策略评估性能，提出了一种基于匹配树的策略评估方法，有效地搜索策略，避免了无效策略参与的额外消耗。在此基础上，提出了一种基于匹配树的策略动态管理方法，通过在树节点和信息映射表中添加锁，减少了待禁用策略管理的规模。通过理论推导和可能影响其评价绩效的因素，验证了评价效率的提高。仿真结果表明，基于匹配树的评价引擎与OuenAz相比有了很大的改进。
{"title":"Policy Evaluation and Dynamic Management Based on Matching Tree for XACML","authors":"Hongzhaoning Kang, Gang Liu, Quan Wang, Runnan Zhang, Zichao Zhong, Yu-min Tian","doi":"10.1109/TrustCom50675.2020.00209","DOIUrl":"https://doi.org/10.1109/TrustCom50675.2020.00209","url":null,"abstract":"As a widely recognized policy language of access control, the eXtensible Access Control Markup Language (XACML) is widely used with its fine-grained and easy-to-read. With the application of XACML, researchers find that the XACML based policy evaluation and policy management methods can no longer meet the current large-scale requests for efficient access and dynamic management requirements. To improve the performance of policy evaluation based on XACML, we propose a policy evaluation method based on the matching tree to search policy efficiently and avoid the extra consumption of invalid policy participation. Furthermore, we propose a policy dynamic management method based on the matching tree to reduce the scale of the policy to be disabled for management, by adding locks in the tree node and the information mapping table. Through theoretical derivation and the factors that may affect its evaluation performance, we verify the improvement of evaluation efficiency. The simulation also shows the improvement of the evaluation engine based on the matching tree compared with OuenAz.","PeriodicalId":221956,"journal":{"name":"2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127161494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-01DOI: 10.1109/TrustCom50675.2020.00135
Yizhong Liu, Jianwei Liu, Yiming Hei, W. Tan, Qianhong Wu
In permissionless blockchains, due to the corruption attack of an adversary, nodes participating the protocol need to be updated regularly. In the process of node selection and committee reconfiguration, there may exist some problems. First, a complicated secure randomness generation protocol is in need. Besides, an adversary might obtain a mining puzzle in advance and start mining in ahead of honest nodes. Moreover, an adversary usually has an advantage of network delay. In order to solve the above problems, we conduct the following research. Firstly, we propose a PoW solution withhold attack against PoW-based member selection methods. An adversary might withhold his mining results in an epoch to obtain the mining puzzle of the next epoch in advance of honest nodes. Secondly, a secure shard reconfiguration protocol is designed, which does not rely on any complicated randomness generation protocol. Our shard reconfiguration protocol is proved rigorously to be secure, which means that in each selected committee, the honest node fraction exceeds a predefined target value. Thirdly, we implement our shard reconfiguration protocol. By carefully setting related system parameters, our protocol could be applied easily to most sharding blockchains. To our best knowledge, the shard reconfiguration protocol proposed in this paper is the first protocol that could safely implement node selection and committee reconfiguration of a sharding blockchain without using a secure randomness, which greatly reduces the communication and time overhead caused by the generation of a randomness.
{"title":"A Secure Shard Reconfiguration Protocol for Sharding Blockchains Without a Randomness","authors":"Yizhong Liu, Jianwei Liu, Yiming Hei, W. Tan, Qianhong Wu","doi":"10.1109/TrustCom50675.2020.00135","DOIUrl":"https://doi.org/10.1109/TrustCom50675.2020.00135","url":null,"abstract":"In permissionless blockchains, due to the corruption attack of an adversary, nodes participating the protocol need to be updated regularly. In the process of node selection and committee reconfiguration, there may exist some problems. First, a complicated secure randomness generation protocol is in need. Besides, an adversary might obtain a mining puzzle in advance and start mining in ahead of honest nodes. Moreover, an adversary usually has an advantage of network delay. In order to solve the above problems, we conduct the following research. Firstly, we propose a PoW solution withhold attack against PoW-based member selection methods. An adversary might withhold his mining results in an epoch to obtain the mining puzzle of the next epoch in advance of honest nodes. Secondly, a secure shard reconfiguration protocol is designed, which does not rely on any complicated randomness generation protocol. Our shard reconfiguration protocol is proved rigorously to be secure, which means that in each selected committee, the honest node fraction exceeds a predefined target value. Thirdly, we implement our shard reconfiguration protocol. By carefully setting related system parameters, our protocol could be applied easily to most sharding blockchains. To our best knowledge, the shard reconfiguration protocol proposed in this paper is the first protocol that could safely implement node selection and committee reconfiguration of a sharding blockchain without using a secure randomness, which greatly reduces the communication and time overhead caused by the generation of a randomness.","PeriodicalId":221956,"journal":{"name":"2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125712450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-01DOI: 10.1109/TrustCom50675.2020.00226
Dominik Ziegler, Alexander Marsalek
We present a novel Ciphertext-Policy Attribute-Based Encryption (CP-ABE) scheme, which bridges the gap between highly dynamic (industrial) environments and resource-constrained devices. Our construction combines outsourced-decryption, hidden policies and revocation to cope with the requirements posed by such environments. In contrast to existing schemes, which typically rely on composite order bilinear groups, we present a scheme in prime order groups. The resulting scheme is more efficient as it relies on smaller group orders. We prove our scheme is secure under the Symmetric External Diffie-Hellman (SXDH) assumption. Lastly, we compare our scheme against existing schemes and provide timing results of our software implementation. Our evaluation shows that the proposed scheme is flexible enough for the targeted environment while improving performance by an order of magnitude.
{"title":"Efficient Revocable Attribute-Based Encryption with Hidden Policies","authors":"Dominik Ziegler, Alexander Marsalek","doi":"10.1109/TrustCom50675.2020.00226","DOIUrl":"https://doi.org/10.1109/TrustCom50675.2020.00226","url":null,"abstract":"We present a novel Ciphertext-Policy Attribute-Based Encryption (CP-ABE) scheme, which bridges the gap between highly dynamic (industrial) environments and resource-constrained devices. Our construction combines outsourced-decryption, hidden policies and revocation to cope with the requirements posed by such environments. In contrast to existing schemes, which typically rely on composite order bilinear groups, we present a scheme in prime order groups. The resulting scheme is more efficient as it relies on smaller group orders. We prove our scheme is secure under the Symmetric External Diffie-Hellman (SXDH) assumption. Lastly, we compare our scheme against existing schemes and provide timing results of our software implementation. Our evaluation shows that the proposed scheme is flexible enough for the targeted environment while improving performance by an order of magnitude.","PeriodicalId":221956,"journal":{"name":"2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124841472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-01DOI: 10.1109/TrustCom50675.2020.00106
Yen-Ting Lee, Tao Ban, Tzu-Ling Wan, Shin-Ming Cheng, Ryoichi Isawa, Takeshi Takahashi, D. Inoue
In this era of rapid network development, Internet of Things (IoT) security considerations receive a lot of attention from both the research and commercial sectors. With limited computation resource, unfriendly interface, and poor software implementation, legacy IoT devices are vulnerable to many infamous mal ware attacks. Moreover, the heterogeneity of IoT platforms and the diversity of IoT malware make the detection and classification of IoT malware even more challenging. In this paper, we propose to use printable strings as an easy-to-get but effective cross-platform feature to identify IoT malware on different IoT platforms. The discriminating capability of these strings are verified using a set of machine learning algorithms on malware family classification across different platforms. The proposed scheme shows a 99% accuracy on a large scale IoT malware dataset consisted of 120K executable fils in executable and linkable format when the training and test are done on the same platform. Meanwhile, it also achieves a 96% accuracy when training is carried out on a few popular IoT platforms but test is done on different platforms. Efficient malware prevention and mitigation solutions can be enabled based on the proposed method to prevent and mitigate IoT malware damages across different platforms.
{"title":"Cross Platform IoT- Malware Family Classification based on Printable Strings","authors":"Yen-Ting Lee, Tao Ban, Tzu-Ling Wan, Shin-Ming Cheng, Ryoichi Isawa, Takeshi Takahashi, D. Inoue","doi":"10.1109/TrustCom50675.2020.00106","DOIUrl":"https://doi.org/10.1109/TrustCom50675.2020.00106","url":null,"abstract":"In this era of rapid network development, Internet of Things (IoT) security considerations receive a lot of attention from both the research and commercial sectors. With limited computation resource, unfriendly interface, and poor software implementation, legacy IoT devices are vulnerable to many infamous mal ware attacks. Moreover, the heterogeneity of IoT platforms and the diversity of IoT malware make the detection and classification of IoT malware even more challenging. In this paper, we propose to use printable strings as an easy-to-get but effective cross-platform feature to identify IoT malware on different IoT platforms. The discriminating capability of these strings are verified using a set of machine learning algorithms on malware family classification across different platforms. The proposed scheme shows a 99% accuracy on a large scale IoT malware dataset consisted of 120K executable fils in executable and linkable format when the training and test are done on the same platform. Meanwhile, it also achieves a 96% accuracy when training is carried out on a few popular IoT platforms but test is done on different platforms. Efficient malware prevention and mitigation solutions can be enabled based on the proposed method to prevent and mitigate IoT malware damages across different platforms.","PeriodicalId":221956,"journal":{"name":"2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124254692","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-01DOI: 10.1109/TrustCom50675.2020.00067
Joe Frederick Samuel, Khalil Aalab, Jason Jaskolka
Over the years, a number of vulnerability scoring frameworks have been proposed to characterize the severity of known vulnerabilities in software-dependent systems. These frameworks provide security metrics to support decision-making in system development and security evaluation and assurance activities. When used in this context, it is imperative that these security metrics be sound, meaning that they can be consistently measured in a reproducible, objective, and unbiased fashion while providing contextually relevant, actionable information for decision makers. In this paper, we evaluate the soundness of the security metrics obtained via several vulnerability scoring frameworks. The evaluation is based on the Method for Designing Sound Security Metrics (MDSSM). We also present several recommendations to improve vulnerability scoring frameworks to yield more sound security metrics to support the development of secure software-dependent systems.
{"title":"Evaluating the Soundness of Security Metrics from Vulnerability Scoring Frameworks","authors":"Joe Frederick Samuel, Khalil Aalab, Jason Jaskolka","doi":"10.1109/TrustCom50675.2020.00067","DOIUrl":"https://doi.org/10.1109/TrustCom50675.2020.00067","url":null,"abstract":"Over the years, a number of vulnerability scoring frameworks have been proposed to characterize the severity of known vulnerabilities in software-dependent systems. These frameworks provide security metrics to support decision-making in system development and security evaluation and assurance activities. When used in this context, it is imperative that these security metrics be sound, meaning that they can be consistently measured in a reproducible, objective, and unbiased fashion while providing contextually relevant, actionable information for decision makers. In this paper, we evaluate the soundness of the security metrics obtained via several vulnerability scoring frameworks. The evaluation is based on the Method for Designing Sound Security Metrics (MDSSM). We also present several recommendations to improve vulnerability scoring frameworks to yield more sound security metrics to support the development of secure software-dependent systems.","PeriodicalId":221956,"journal":{"name":"2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125015811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-01DOI: 10.1109/TrustCom50675.2020.00016
Xin Tang, Linna Zhou, Dan Liu, Boyu Liu, Xin-yi Lü
Rhombus predictor is an effective technique to achieve prediction error expansion based reversible data hiding. Considering the correlation of adjacent pixels, it achieves high performance prediction of the central pixel with the help of its surrounding four pixels in a rhombus cell. However, for cells with large fluctuation, such correlation is rather weak, leading to poor accuracy of prediction. In this paper, we propose a reversible data hiding scheme based on improved rhombus predictor, which takes the lead to consider consistencies along horizontal, vertical and diagonal directions of the rhombus cell simultaneously so that pixels with higher consistency are employed together to make up the predictor. To reduce the prediction error once watermark bits are not fully embedded, we further present a corresponding fluctuation based sorting strategy. The experimental results show that, with the same amount of watermark bits embedded, the proposed scheme is able to achieve better performance comparing with the classic scheme and the state-of-the art.
{"title":"Reversible data hiding based on improved rhombus predictor and prediction error expansion","authors":"Xin Tang, Linna Zhou, Dan Liu, Boyu Liu, Xin-yi Lü","doi":"10.1109/TrustCom50675.2020.00016","DOIUrl":"https://doi.org/10.1109/TrustCom50675.2020.00016","url":null,"abstract":"Rhombus predictor is an effective technique to achieve prediction error expansion based reversible data hiding. Considering the correlation of adjacent pixels, it achieves high performance prediction of the central pixel with the help of its surrounding four pixels in a rhombus cell. However, for cells with large fluctuation, such correlation is rather weak, leading to poor accuracy of prediction. In this paper, we propose a reversible data hiding scheme based on improved rhombus predictor, which takes the lead to consider consistencies along horizontal, vertical and diagonal directions of the rhombus cell simultaneously so that pixels with higher consistency are employed together to make up the predictor. To reduce the prediction error once watermark bits are not fully embedded, we further present a corresponding fluctuation based sorting strategy. The experimental results show that, with the same amount of watermark bits embedded, the proposed scheme is able to achieve better performance comparing with the classic scheme and the state-of-the art.","PeriodicalId":221956,"journal":{"name":"2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125301896","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-01DOI: 10.1109/TrustCom50675.2020.00062
Meng Li, Qi Zhong, L. Zhang, Yajuan Du, Jinchao Zhang, Yong Xiangt
Similar to other digital assets, deep neural network (DNN) models could suffer from piracy threat initiated by insider and/or outsider adversaries due to their inherent commercial value. DNN watermarking is a promising technique to mitigate this threat to intellectual property. This work focuses on black-box DNN watermarking, with which an owner can only verify his ownership by issuing special trigger queries to a remote suspicious model. However, informed attackers, who are aware of the watermark and somehow obtain the triggers, could forge fake triggers to claim their ownerships since the poor robustness of triggers and the lack of correlation between the model and the owner identity. This consideration calls for new watermarking methods that can achieve better trade-off for addressing the discrepancy. In this paper, we exploit frequency domain image watermarking to generate triggers and build our DNN watermarking algorithm accordingly. Since watermarking in the frequency domain is high concealment and robust to signal processing operation, the proposed algorithm is superior to existing schemes in resisting fraudulent claim attack. Besides, extensive experimental results on 3 datasets and 8 neural networks demonstrate that the proposed DNN watermarking algorithm achieves similar performance on functionality metrics and better performance on security metrics when compared with existing algorithms.
{"title":"Protecting the Intellectual Property of Deep Neural Networks with Watermarking: The Frequency Domain Approach","authors":"Meng Li, Qi Zhong, L. Zhang, Yajuan Du, Jinchao Zhang, Yong Xiangt","doi":"10.1109/TrustCom50675.2020.00062","DOIUrl":"https://doi.org/10.1109/TrustCom50675.2020.00062","url":null,"abstract":"Similar to other digital assets, deep neural network (DNN) models could suffer from piracy threat initiated by insider and/or outsider adversaries due to their inherent commercial value. DNN watermarking is a promising technique to mitigate this threat to intellectual property. This work focuses on black-box DNN watermarking, with which an owner can only verify his ownership by issuing special trigger queries to a remote suspicious model. However, informed attackers, who are aware of the watermark and somehow obtain the triggers, could forge fake triggers to claim their ownerships since the poor robustness of triggers and the lack of correlation between the model and the owner identity. This consideration calls for new watermarking methods that can achieve better trade-off for addressing the discrepancy. In this paper, we exploit frequency domain image watermarking to generate triggers and build our DNN watermarking algorithm accordingly. Since watermarking in the frequency domain is high concealment and robust to signal processing operation, the proposed algorithm is superior to existing schemes in resisting fraudulent claim attack. Besides, extensive experimental results on 3 datasets and 8 neural networks demonstrate that the proposed DNN watermarking algorithm achieves similar performance on functionality metrics and better performance on security metrics when compared with existing algorithms.","PeriodicalId":221956,"journal":{"name":"2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128378209","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-01DOI: 10.1109/TrustCom50675.2020.00194
Zhicheng Song, Pushpendu Kar
Named Data Networking (NDN) is a content-centric networking, where the publisher of the packet signs and encapsulates the data packet with a name-content-signature encryption to verify the authenticity and integrity of itself. This scheme can solve many of the security issues inherently compared to IP networking. NDN also support mobility since it hides the point-to-point connection details. However, an extreme attack takes place when an NDN consumer newly connects to a network. A Man-in-the-middle (MITM) malicious node can block the consumer and keep intercepting the interest packets sent out so as to fake the corresponding data packets signed with its own private key. Without knowledge and trust to the network, the NDN consumer can by no means perceive the attack and thus exposed to severe security and privacy hazard. In this paper, the N ame-Signature Lookup System (NSLS) and corresponding Name-Signature Lookup Protocol (NSLP) is introduced to verify packets with their registered genuine publisher even in an untrusted network with the help of embedded keys inside Network Interface Controller (NIC), by which attacks like MITM is eliminated. A theoretical analysis of comparing NSLS with existing security model is provided. Digest algorithm SHA-256 and signature algorithm RSA are used in the NSLP model without specific preference.
命名数据网络(Named Data Networking, NDN)是一种以内容为中心的网络，数据包的发布者使用名称-内容-签名加密对数据包进行签名和封装，以验证自身的真实性和完整性。与IP网络相比，该方案可以解决许多固有的安全问题。NDN还支持移动性，因为它隐藏了点对点连接的细节。但是，当NDN使用者新连接到网络时，就会发生极端攻击。中间人(Man-in-the-middle, MITM)恶意节点可以阻断消费者并不断拦截发送出去的兴趣包，从而伪造出用自己的私钥签名的相应数据包。没有对网络的了解和信任，NDN消费者根本无法感知攻击，从而面临严重的安全和隐私风险。本文引入N名称签名查找系统(NSLS)和相应的名称签名查找协议(NSLP)，利用网络接口控制器(NIC)内的嵌入式密钥，在不可信网络中与注册的正版发布者验证数据包，从而消除了MITM等攻击。对NSLS与现有安全模型进行了比较分析。NSLP模型使用摘要算法SHA-256和签名算法RSA，没有特定的优先级。
{"title":"Name-Signature Lookup System: A Security Enhancement to Named Data Networking","authors":"Zhicheng Song, Pushpendu Kar","doi":"10.1109/TrustCom50675.2020.00194","DOIUrl":"https://doi.org/10.1109/TrustCom50675.2020.00194","url":null,"abstract":"Named Data Networking (NDN) is a content-centric networking, where the publisher of the packet signs and encapsulates the data packet with a name-content-signature encryption to verify the authenticity and integrity of itself. This scheme can solve many of the security issues inherently compared to IP networking. NDN also support mobility since it hides the point-to-point connection details. However, an extreme attack takes place when an NDN consumer newly connects to a network. A Man-in-the-middle (MITM) malicious node can block the consumer and keep intercepting the interest packets sent out so as to fake the corresponding data packets signed with its own private key. Without knowledge and trust to the network, the NDN consumer can by no means perceive the attack and thus exposed to severe security and privacy hazard. In this paper, the N ame-Signature Lookup System (NSLS) and corresponding Name-Signature Lookup Protocol (NSLP) is introduced to verify packets with their registered genuine publisher even in an untrusted network with the help of embedded keys inside Network Interface Controller (NIC), by which attacks like MITM is eliminated. A theoretical analysis of comparing NSLS with existing security model is provided. Digest algorithm SHA-256 and signature algorithm RSA are used in the NSLP model without specific preference.","PeriodicalId":221956,"journal":{"name":"2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)","volume":"302 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122235994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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