Security problem is an important issue for Wireless Sensor Network.The paper focuses on the privacy protection of WSN applications.An anonymity enhancement tactic based on pseudonym mechanism is presented for clustere...Security problem is an important issue for Wireless Sensor Network.The paper focuses on the privacy protection of WSN applications.An anonymity enhancement tactic based on pseudonym mechanism is presented for clustered Wireless Sensor Network,which provides anonymity for both the sensors within a cluster and the cluster head nodes.Simulation experiments are launched through NS2 platform to validate the anonymity performance.The theoretical analysis and empirical study imply that the proposed scheme based on pseudonym can protect the privacies of both the sensor nodes and the cluster head nodes.The work is valuable and the experimental results are convincible.展开更多
In this paper, we proposed an anonymity scheme based on pseudonym where peers are motivated not to share their identity. Compared with precious scheme such as RuP （Reputation using Pseudonyms）, our scheme can reduce...In this paper, we proposed an anonymity scheme based on pseudonym where peers are motivated not to share their identity. Compared with precious scheme such as RuP （Reputation using Pseudonyms）, our scheme can reduce its overhead and minimize the trusted center＇s involvement.展开更多
As technology develops,the amount of information being used has increased a lot.Every company learns big data to provide customized services with its customers.Accordingly,collecting and analyzing data of the data sub...As technology develops,the amount of information being used has increased a lot.Every company learns big data to provide customized services with its customers.Accordingly,collecting and analyzing data of the data subject has become one of the core competencies of the companies.However,when collecting and using it,the authority of the data subject may be violated.The data often identifies its subject by itself,and even if it is not a personal information that infringes on an individual’s authority,the moment it is connected,it becomes important and sensitive personal information that we have never thought of.Therefore,recent privacy regulations such as GDPR(GeneralData ProtectionRegulation)are changing to guarantee more rights of the data subjects.To use data effectively without infringing on the rights of the data subject,the concept of de-identification has been created.Researchers and companies can make personal information less identifiable through appropriate de-identification/pseudonymization and use the data for the purpose of statistical research.De-identification/pseudonymization techniques have been studied a lot,but it is difficult for companies and researchers to know how to de-identify/pseudonymize data.It is difficult to clearly understand how and to what extent each organization should take deidentification measures.Currently,each organization does not systematically analyze and conduct the situation but only takes minimal action while looking at the guidelines distributed by each country.We solved this problem from the perspective of risk management.Several steps are required to secure the dataset starting from pre-processing to releasing the dataset.We can analyze the dataset,analyze the risk,evaluate the risk,and treat the risk appropriately.The outcomes of each step can then be used to take appropriate action on the dataset to eliminate or reduce its risk.Then,we can release the dataset under its own purpose.These series of processes were reconstructed to fit the current situation by analyzing various standards such as ISO/IEC(International Organization for Standardization/International Electrotechnical Commission)20889,NIST IR(National Institute of Standards and Technology Interagency Reports)8053,NIST SP(National Institute of Standards and Technology Special Publications)800-188,and ITU-T(International Telecommunications Union-Telecommunication)X.1148.We propose an integrated framework based on situational awareness model and risk management model.We found that this framework can be specialized for multiple domains,and it is useful because it is based on a variety of case and utility-based ROI calculations.展开更多
As Vehicular ad hoc networks (VANETs) become more sophisticated, the importance of integrating data protection and cybersecurity is increasingly evident. This paper offers a comprehensive investigation into the challe...As Vehicular ad hoc networks (VANETs) become more sophisticated, the importance of integrating data protection and cybersecurity is increasingly evident. This paper offers a comprehensive investigation into the challenges and solutions associated with the privacy implications within VANETs, rooted in an intricate landscape of cross-jurisdictional data protection regulations. Our examination underscores the unique nature of VANETs, which, unlike other ad-hoc networks, demand heightened security and privacy considerations due to their exposure to sensitive data such as vehicle identifiers, routes, and more. Through a rigorous exploration of pseudonymization schemes, with a notable emphasis on the Density-based Location Privacy (DLP) method, we elucidate the potential to mitigate and sometimes sidestep the heavy compliance burdens associated with data protection laws. Furthermore, this paper illuminates the cybersecurity vulnerabilities inherent to VANETs, proposing robust countermeasures, including secure data transmission protocols. In synthesizing our findings, we advocate for the proactive adoption of protective mechanisms to facilitate the broader acceptance of VANET technology while concurrently addressing regulatory and cybersecurity hurdles.展开更多
基金the National Natural Science Foundation of China (NSFC) under grant No.61309024,the National Key Basic Research Program of China (973) under Grant No.2013CB834204,the Fundamental Research Funds for the Central Universities under grant No.14CX06009A at China University of Petroleum
文摘Security problem is an important issue for Wireless Sensor Network.The paper focuses on the privacy protection of WSN applications.An anonymity enhancement tactic based on pseudonym mechanism is presented for clustered Wireless Sensor Network,which provides anonymity for both the sensors within a cluster and the cluster head nodes.Simulation experiments are launched through NS2 platform to validate the anonymity performance.The theoretical analysis and empirical study imply that the proposed scheme based on pseudonym can protect the privacies of both the sensor nodes and the cluster head nodes.The work is valuable and the experimental results are convincible.
文摘In this paper, we proposed an anonymity scheme based on pseudonym where peers are motivated not to share their identity. Compared with precious scheme such as RuP （Reputation using Pseudonyms）, our scheme can reduce its overhead and minimize the trusted center＇s involvement.
文摘As technology develops,the amount of information being used has increased a lot.Every company learns big data to provide customized services with its customers.Accordingly,collecting and analyzing data of the data subject has become one of the core competencies of the companies.However,when collecting and using it,the authority of the data subject may be violated.The data often identifies its subject by itself,and even if it is not a personal information that infringes on an individual’s authority,the moment it is connected,it becomes important and sensitive personal information that we have never thought of.Therefore,recent privacy regulations such as GDPR(GeneralData ProtectionRegulation)are changing to guarantee more rights of the data subjects.To use data effectively without infringing on the rights of the data subject,the concept of de-identification has been created.Researchers and companies can make personal information less identifiable through appropriate de-identification/pseudonymization and use the data for the purpose of statistical research.De-identification/pseudonymization techniques have been studied a lot,but it is difficult for companies and researchers to know how to de-identify/pseudonymize data.It is difficult to clearly understand how and to what extent each organization should take deidentification measures.Currently,each organization does not systematically analyze and conduct the situation but only takes minimal action while looking at the guidelines distributed by each country.We solved this problem from the perspective of risk management.Several steps are required to secure the dataset starting from pre-processing to releasing the dataset.We can analyze the dataset,analyze the risk,evaluate the risk,and treat the risk appropriately.The outcomes of each step can then be used to take appropriate action on the dataset to eliminate or reduce its risk.Then,we can release the dataset under its own purpose.These series of processes were reconstructed to fit the current situation by analyzing various standards such as ISO/IEC(International Organization for Standardization/International Electrotechnical Commission)20889,NIST IR(National Institute of Standards and Technology Interagency Reports)8053,NIST SP(National Institute of Standards and Technology Special Publications)800-188,and ITU-T(International Telecommunications Union-Telecommunication)X.1148.We propose an integrated framework based on situational awareness model and risk management model.We found that this framework can be specialized for multiple domains,and it is useful because it is based on a variety of case and utility-based ROI calculations.
文摘As Vehicular ad hoc networks (VANETs) become more sophisticated, the importance of integrating data protection and cybersecurity is increasingly evident. This paper offers a comprehensive investigation into the challenges and solutions associated with the privacy implications within VANETs, rooted in an intricate landscape of cross-jurisdictional data protection regulations. Our examination underscores the unique nature of VANETs, which, unlike other ad-hoc networks, demand heightened security and privacy considerations due to their exposure to sensitive data such as vehicle identifiers, routes, and more. Through a rigorous exploration of pseudonymization schemes, with a notable emphasis on the Density-based Location Privacy (DLP) method, we elucidate the potential to mitigate and sometimes sidestep the heavy compliance burdens associated with data protection laws. Furthermore, this paper illuminates the cybersecurity vulnerabilities inherent to VANETs, proposing robust countermeasures, including secure data transmission protocols. In synthesizing our findings, we advocate for the proactive adoption of protective mechanisms to facilitate the broader acceptance of VANET technology while concurrently addressing regulatory and cybersecurity hurdles.
