Pub Date : 2020-12-01DOI: 10.1109/TrustCom50675.2020.00112
Taejun Choi, Guangdong Bai, R. Ko, Naipeng Dong, Wenlu Zhang, Shunyao Wang
Industrial control systems (ICS) of critical infrastructure are increasingly connected to the Internet for remote site management at scale. However, cyber attacks against ICS - especially at the communication channels between human-machine interface (HMIs) and programmable logic controllers (PLCs) - are increasing at a rate which outstrips the rate of mitigation. In this paper, we introduce a vendor-agnostic analytics framework which allows security researchers to analyse attacks against ICS systems, even if the researchers have zero control automation domain knowledge or are faced with a myriad of heterogenous ICS systems. Unlike existing works that require expertise in domain knowledge and specialised tool usage, our analytics framework does not require prior knowledge about ICS communication protocols, PLCs, and expertise of any network penetration testing tool. Using ‘digital twin’ scenarios comprising industry-representative HMIs, PLCs and firewalls in our test lab, our framework's steps were demonstrated to successfully implement a stealthy deception attack based on false data injection attacks (FDIA). Furthermore, our framework also demonstrated the relative ease of attack dataset collection, and the ability to leverage well-known penetration testing tools. We also introduce the concept of ‘heuristic inference attacks', a new family of attack types on ICS which is agnostic to PLC and HMI brands/models commonly deployed in ICS. Our experiments were also validated on a separate ICS dataset collected from a cyber-physical scenario of water utilities. Finally, we utilized time complexity theory to estimate the difficulty for the attacker to conduct the proposed packet analyses, and recommended countermeasures based on our findings.
{"title":"An Analytics Framework for Heuristic Inference Attacks against Industrial Control Systems","authors":"Taejun Choi, Guangdong Bai, R. Ko, Naipeng Dong, Wenlu Zhang, Shunyao Wang","doi":"10.1109/TrustCom50675.2020.00112","DOIUrl":"https://doi.org/10.1109/TrustCom50675.2020.00112","url":null,"abstract":"Industrial control systems (ICS) of critical infrastructure are increasingly connected to the Internet for remote site management at scale. However, cyber attacks against ICS - especially at the communication channels between human-machine interface (HMIs) and programmable logic controllers (PLCs) - are increasing at a rate which outstrips the rate of mitigation. In this paper, we introduce a vendor-agnostic analytics framework which allows security researchers to analyse attacks against ICS systems, even if the researchers have zero control automation domain knowledge or are faced with a myriad of heterogenous ICS systems. Unlike existing works that require expertise in domain knowledge and specialised tool usage, our analytics framework does not require prior knowledge about ICS communication protocols, PLCs, and expertise of any network penetration testing tool. Using ‘digital twin’ scenarios comprising industry-representative HMIs, PLCs and firewalls in our test lab, our framework's steps were demonstrated to successfully implement a stealthy deception attack based on false data injection attacks (FDIA). Furthermore, our framework also demonstrated the relative ease of attack dataset collection, and the ability to leverage well-known penetration testing tools. We also introduce the concept of ‘heuristic inference attacks', a new family of attack types on ICS which is agnostic to PLC and HMI brands/models commonly deployed in ICS. Our experiments were also validated on a separate ICS dataset collected from a cyber-physical scenario of water utilities. Finally, we utilized time complexity theory to estimate the difficulty for the attacker to conduct the proposed packet analyses, and recommended countermeasures based on our findings.","PeriodicalId":221956,"journal":{"name":"2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)","volume":"639 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":"123049300","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/TrustCom50675.2020.00270
Li Jian, Fei Rong, Tang Yu
In this paper, we proposed a path planning algorithm based on Q-learning model to simulate an environment model, which is suitable for the complex environment. A virtual simulation platform has been built to complete the experiments. The experimental results show that the algorithm proposed in this paper can be effectively applied to the solution of vehicle routing problems in the complex environment.
{"title":"A novel Q-Learning Algorithm Based on the Stochastic Environment Path Planning Problem","authors":"Li Jian, Fei Rong, Tang Yu","doi":"10.1109/TrustCom50675.2020.00270","DOIUrl":"https://doi.org/10.1109/TrustCom50675.2020.00270","url":null,"abstract":"In this paper, we proposed a path planning algorithm based on Q-learning model to simulate an environment model, which is suitable for the complex environment. A virtual simulation platform has been built to complete the experiments. The experimental results show that the algorithm proposed in this paper can be effectively applied to the solution of vehicle routing problems in the complex environment.","PeriodicalId":221956,"journal":{"name":"2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)","volume":"35 28","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120813536","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/TrustCom50675.2020.00193
K. Herberth
Instant Messaging (IM) clients are lying to you about groups and their consistency. None of the so called secure chat applications provide the same security properties for group communication you know from face-to-face meetings. In this paper we give an overview of the challenges in group communication and introduce a solution to the transcript distribution challenge. We present a new visualization for out-of-order messages and the results of a user study to show that our approach is working for every day users.
{"title":"Group Communication Needs No Consistent Transcript Distribution","authors":"K. Herberth","doi":"10.1109/TrustCom50675.2020.00193","DOIUrl":"https://doi.org/10.1109/TrustCom50675.2020.00193","url":null,"abstract":"Instant Messaging (IM) clients are lying to you about groups and their consistency. None of the so called secure chat applications provide the same security properties for group communication you know from face-to-face meetings. In this paper we give an overview of the challenges in group communication and introduce a solution to the transcript distribution challenge. We present a new visualization for out-of-order messages and the results of a user study to show that our approach is working for every day users.","PeriodicalId":221956,"journal":{"name":"2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)","volume":"4 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":"127113143","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/TrustCom50675.2020.00024
Ran Li, Jiaqi Yin, Huibiao Zhu
RabbitMQ is a very popular message middleware, which is an implementation of AMQP (Advanced Message Queuing Protocol) using the Erlang language. It supports concurrency and guarantees the sequential consistency of messages. Additionally, RabbitMQ provides the message acknowledgement mechanism to ensure that messages can be delivered reliably to the consumer from the broker. However, these crucial properties have not been verified with formal methods. In this paper, we model the architecture of RabbitMQ with timed automata. By utilizing the model checker UPPAAL, RabbitMQ is abstracted to five timed automata. Based on the formalized model, we verify whether RabbitMQ meets some essential properties, including Reachability of Data, Concurrency, Sequence Consistency and Message Acknowledgement. Consequently, it can be found that RabbitMQ can totally satisfy these properties according to the verification results via UPPAAL.
{"title":"Modeling and Analysis of RabbitMQ Using UPPAAL","authors":"Ran Li, Jiaqi Yin, Huibiao Zhu","doi":"10.1109/TrustCom50675.2020.00024","DOIUrl":"https://doi.org/10.1109/TrustCom50675.2020.00024","url":null,"abstract":"RabbitMQ is a very popular message middleware, which is an implementation of AMQP (Advanced Message Queuing Protocol) using the Erlang language. It supports concurrency and guarantees the sequential consistency of messages. Additionally, RabbitMQ provides the message acknowledgement mechanism to ensure that messages can be delivered reliably to the consumer from the broker. However, these crucial properties have not been verified with formal methods. In this paper, we model the architecture of RabbitMQ with timed automata. By utilizing the model checker UPPAAL, RabbitMQ is abstracted to five timed automata. Based on the formalized model, we verify whether RabbitMQ meets some essential properties, including Reachability of Data, Concurrency, Sequence Consistency and Message Acknowledgement. Consequently, it can be found that RabbitMQ can totally satisfy these properties according to the verification results via UPPAAL.","PeriodicalId":221956,"journal":{"name":"2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)","volume":"40 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":"124897418","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/TrustCom50675.2020.00138
Subhra Mazumdar, Prabal Banerjee, S. Ruj
Lightning Network is the most deployed Bitcoin-compatible Payment Channel Network (PCN), ensuring faster execution of transactions. However, this Layer-two solution has its fair share of problems. Topological analysis on Lightning Network reveals that Griefing Attack is a major problem whereby an adversary intentionally exhausts the channel capacity of the network. Though the attack does not always result in a direct monetary gain of the attacker, blocking of channel capacity for several days prevents several nodes from processing any future transaction request, leading to substantial collateral damage. If the attacker is able to lock funds in multiple paths simultaneously, then a major portion of the network may get stalled, reducing the throughput. Mitigating Griefing Attack still remains an open problem. In this paper, we propose an efficient countermeasure for the attack, known as Griefing-Penalty. To realize it, we propose a new payment protocol HTLC-GP or Hashed Timelock Contract with Griefing-Penalty. It not only preserves privacy but also ensures that an attacker cannot ascribe blame on any honest party present in the path relaying the payment. We evaluate the effectiveness of griefing-penalty using different attack strategies and test it on several snapshots of Lightning Network. Our evaluation results show that loss incurred is substantially high for HTLC-GP compared to HTLC.
{"title":"Time is Money: Countering Griefing Attack in Lightning Network","authors":"Subhra Mazumdar, Prabal Banerjee, S. Ruj","doi":"10.1109/TrustCom50675.2020.00138","DOIUrl":"https://doi.org/10.1109/TrustCom50675.2020.00138","url":null,"abstract":"Lightning Network is the most deployed Bitcoin-compatible Payment Channel Network (PCN), ensuring faster execution of transactions. However, this Layer-two solution has its fair share of problems. Topological analysis on Lightning Network reveals that Griefing Attack is a major problem whereby an adversary intentionally exhausts the channel capacity of the network. Though the attack does not always result in a direct monetary gain of the attacker, blocking of channel capacity for several days prevents several nodes from processing any future transaction request, leading to substantial collateral damage. If the attacker is able to lock funds in multiple paths simultaneously, then a major portion of the network may get stalled, reducing the throughput. Mitigating Griefing Attack still remains an open problem. In this paper, we propose an efficient countermeasure for the attack, known as Griefing-Penalty. To realize it, we propose a new payment protocol HTLC-GP or Hashed Timelock Contract with Griefing-Penalty. It not only preserves privacy but also ensures that an attacker cannot ascribe blame on any honest party present in the path relaying the payment. We evaluate the effectiveness of griefing-penalty using different attack strategies and test it on several snapshots of Lightning Network. Our evaluation results show that loss incurred is substantially high for HTLC-GP compared to HTLC.","PeriodicalId":221956,"journal":{"name":"2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)","volume":"40 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":"116539433","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}
In order to help researchers quickly understand the connection between new threat events and previous threat events, threat intelligence document-level relation extraction plays a very important role in threat intelligence text analysis and processing. Because there is no public document-level threat intelligence dataset, we create APTERC-DOC, an APT intelligence entities, relations and coreference dataset. We treat the relation extraction as a multi-classification task. Treating the coreference relation as a kind of predefined relations, we develop a joint learning framework called TIRECO, a model which can simultaneously complete threat intelligence relation extraction and coreference resolution. In order to solve the problem of document-level text being too long to extract feature, we propose the concept of sentence set, which transforms document-level relation extraction into inter-sentence relation extraction. To incorporate relevant information with maximally removing irrelevant content in sentence set, we further apply a novel pruning strategy (SDP-VP-SET) to the input trees considering that verbs are crucial in determining the relation between entities in sentence set. With retaining the shortest path and nodes that are K hops away from the shortest path, we give the edge connected to the verb nodes a weight of w times. Experimental results show that our model not only performs well in the extraction of inter-sentence relations, it is also effective in intra-sentence relations, and the F1 value has increased by 15.694%.
{"title":"Joint Learning for Document-Level Threat Intelligence Relation Extraction and Coreference Resolution Based on GCN","authors":"Xuren Wang, Mengbo Xiong, Yali Luo, Ning Li, Zhengwei Jiang, Zihan Xiong","doi":"10.1109/TrustCom50675.2020.00083","DOIUrl":"https://doi.org/10.1109/TrustCom50675.2020.00083","url":null,"abstract":"In order to help researchers quickly understand the connection between new threat events and previous threat events, threat intelligence document-level relation extraction plays a very important role in threat intelligence text analysis and processing. Because there is no public document-level threat intelligence dataset, we create APTERC-DOC, an APT intelligence entities, relations and coreference dataset. We treat the relation extraction as a multi-classification task. Treating the coreference relation as a kind of predefined relations, we develop a joint learning framework called TIRECO, a model which can simultaneously complete threat intelligence relation extraction and coreference resolution. In order to solve the problem of document-level text being too long to extract feature, we propose the concept of sentence set, which transforms document-level relation extraction into inter-sentence relation extraction. To incorporate relevant information with maximally removing irrelevant content in sentence set, we further apply a novel pruning strategy (SDP-VP-SET) to the input trees considering that verbs are crucial in determining the relation between entities in sentence set. With retaining the shortest path and nodes that are K hops away from the shortest path, we give the edge connected to the verb nodes a weight of w times. Experimental results show that our model not only performs well in the extraction of inter-sentence relations, it is also effective in intra-sentence relations, and the F1 value has increased by 15.694%.","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":"122629284","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/TrustCom50675.2020.00265
Tao Peng, Jierong Liu, Jianer Chen, Guojun Wang
Mobile crowdsensing system has become a new paradigm application with popularity and development of smart mobile devices. It provides a costless and efficient model to collect sensory data. However, most of mobile crowdsensing systems are based on the centralized structure, which will lead to serious privacy disclosure. In this paper, we combine k-anonymity and blockchain to build a mobile corwdsensing system, in which the users can upload their sensory data and receive corresponding rewards without privacy disclosure concern. With the distributed structure system and encryption algorithm, the system achieves enhanced privacy preservation through breaking the link between data and rewards and their owners.
{"title":"A Privacy-Preserving Crowdsensing System with Muti-Blockchain","authors":"Tao Peng, Jierong Liu, Jianer Chen, Guojun Wang","doi":"10.1109/TrustCom50675.2020.00265","DOIUrl":"https://doi.org/10.1109/TrustCom50675.2020.00265","url":null,"abstract":"Mobile crowdsensing system has become a new paradigm application with popularity and development of smart mobile devices. It provides a costless and efficient model to collect sensory data. However, most of mobile crowdsensing systems are based on the centralized structure, which will lead to serious privacy disclosure. In this paper, we combine k-anonymity and blockchain to build a mobile corwdsensing system, in which the users can upload their sensory data and receive corresponding rewards without privacy disclosure concern. With the distributed structure system and encryption algorithm, the system achieves enhanced privacy preservation through breaking the link between data and rewards and their owners.","PeriodicalId":221956,"journal":{"name":"2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)","volume":"262 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":"122929794","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/trustcom50675.2020.00010
{"title":"PASS4IoT 2020 Organizing and Program Committees","authors":"","doi":"10.1109/trustcom50675.2020.00010","DOIUrl":"https://doi.org/10.1109/trustcom50675.2020.00010","url":null,"abstract":"","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":"128497817","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/TrustCom50675.2020.00082
Tianyi Zhang, Jian Wang
As one of the most expensive computations in public-key cryptosystems, modular exponentiation is typically out-sourced to the cloud servers. Traditional cloud-based outsourcing algorithms depend on multiple untrusted servers to guarantee the security, which may lead to vulnerability to the collusion attack. Although recent single-server multiple-requests outsourcing algorithms are more secure, they have to perform multiple requests to the single untrusted server to guarantee the security and checkability of the data, which will incur unacceptable latency and local computational costs. In comparison, the edge computing paradigm enhances security since it has multiple computational nodes, including some highly secure local computational nodes. In this paper, we propose the secure outsourcing algorithm of modular exponentiation for the edge computing paradigm. To address the dilemma that the computational resources of different nodes vary significantly, we design two lightweight algorithms to adaptively separate the modular exponentiation to the nodes based on the computational resources. To guarantee the outsourcing checkability, we propose a protocol verify the result returned from each node. We formally prove the security and checkability of our algorithm and validate the efficiency of our algorithm based on experiments and case studies.
{"title":"Secure Outsourcing Algorithms of Modular Exponentiations in Edge Computing","authors":"Tianyi Zhang, Jian Wang","doi":"10.1109/TrustCom50675.2020.00082","DOIUrl":"https://doi.org/10.1109/TrustCom50675.2020.00082","url":null,"abstract":"As one of the most expensive computations in public-key cryptosystems, modular exponentiation is typically out-sourced to the cloud servers. Traditional cloud-based outsourcing algorithms depend on multiple untrusted servers to guarantee the security, which may lead to vulnerability to the collusion attack. Although recent single-server multiple-requests outsourcing algorithms are more secure, they have to perform multiple requests to the single untrusted server to guarantee the security and checkability of the data, which will incur unacceptable latency and local computational costs. In comparison, the edge computing paradigm enhances security since it has multiple computational nodes, including some highly secure local computational nodes. In this paper, we propose the secure outsourcing algorithm of modular exponentiation for the edge computing paradigm. To address the dilemma that the computational resources of different nodes vary significantly, we design two lightweight algorithms to adaptively separate the modular exponentiation to the nodes based on the computational resources. To guarantee the outsourcing checkability, we propose a protocol verify the result returned from each node. We formally prove the security and checkability of our algorithm and validate the efficiency of our algorithm based on experiments and case studies.","PeriodicalId":221956,"journal":{"name":"2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)","volume":"51 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":"116566394","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/TrustCom50675.2020.00017
Dapeng Qu, Jiankun Zhang, Zhenhuan Hou, M. Wan, B. Dong
Mobile peer-to-peer network (MP2P) attracts increasing attentions due to the ubiquitous use of mobile communication and huge success of peer-to-peer (P2P) mode. However, open p2p mode makes nodes tend to be selfish, and the scarcity of resources in mobile nodes aggravates this problem, thus the nodes easily express a non-complete cooperative (NCC) attitude. Therefore, an identification of non-complete cooperative nodes and a corresponding trust routing scheme are proposed for MP2P in this paper. The concept of octant is firstly introduced to build a trust model which analyzes nodes from three dimensions, namely direct trust, internal state and recommendation reliability, and then the individual non-complete cooperative (INCC) nodes can be identified by the division of different octants. The direct trust monitors nodes' external behaviors, and the consideration of internal state and recommendation reliability contributes to differentiate the subjective and objective non-cooperation, and mitigate the attacks about direct trust values respectively. Thus, the trust model can identify various INCC nodes accurately. On the basis of identification of INCC nodes, cosine similarity method is applied to identify collusive non-complete cooperate (CNCC) nodes. Moreover, a trust routing scheme based on the identification of NCC nodes is presented to reasonably deal with different kinds of NCC nodes. Results from extensive simulation experiments demonstrate that this proposed identification and routing scheme have better performances, in terms of identification precision and packet delivery fraction than current schemes respectively.
{"title":"A Trust Routing Scheme based on Identification of Non-complete Cooperative Nodes in Mobile Peer-to-Peer Networks","authors":"Dapeng Qu, Jiankun Zhang, Zhenhuan Hou, M. Wan, B. Dong","doi":"10.1109/TrustCom50675.2020.00017","DOIUrl":"https://doi.org/10.1109/TrustCom50675.2020.00017","url":null,"abstract":"Mobile peer-to-peer network (MP2P) attracts increasing attentions due to the ubiquitous use of mobile communication and huge success of peer-to-peer (P2P) mode. However, open p2p mode makes nodes tend to be selfish, and the scarcity of resources in mobile nodes aggravates this problem, thus the nodes easily express a non-complete cooperative (NCC) attitude. Therefore, an identification of non-complete cooperative nodes and a corresponding trust routing scheme are proposed for MP2P in this paper. The concept of octant is firstly introduced to build a trust model which analyzes nodes from three dimensions, namely direct trust, internal state and recommendation reliability, and then the individual non-complete cooperative (INCC) nodes can be identified by the division of different octants. The direct trust monitors nodes' external behaviors, and the consideration of internal state and recommendation reliability contributes to differentiate the subjective and objective non-cooperation, and mitigate the attacks about direct trust values respectively. Thus, the trust model can identify various INCC nodes accurately. On the basis of identification of INCC nodes, cosine similarity method is applied to identify collusive non-complete cooperate (CNCC) nodes. Moreover, a trust routing scheme based on the identification of NCC nodes is presented to reasonably deal with different kinds of NCC nodes. Results from extensive simulation experiments demonstrate that this proposed identification and routing scheme have better performances, in terms of identification precision and packet delivery fraction than current schemes respectively.","PeriodicalId":221956,"journal":{"name":"2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)","volume":"196 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":"124379632","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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