As modern communication technology advances apace,the digital communication signals identification plays an important role in cognitive radio networks,the communication monitoring and management systems.AI has become ...As modern communication technology advances apace,the digital communication signals identification plays an important role in cognitive radio networks,the communication monitoring and management systems.AI has become a promising solution to this problem due to its powerful modeling capability,which has become a consensus in academia and industry.However,because of the data-dependence and inexplicability of AI models and the openness of electromagnetic space,the physical layer digital communication signals identification model is threatened by adversarial attacks.Adversarial examples pose a common threat to AI models,where well-designed and slight perturbations added to input data can cause wrong results.Therefore,the security of AI models for the digital communication signals identification is the premise of its efficient and credible applications.In this paper,we first launch adversarial attacks on the end-to-end AI model for automatic modulation classifi-cation,and then we explain and present three defense mechanisms based on the adversarial principle.Next we present more detailed adversarial indicators to evaluate attack and defense behavior.Finally,a demonstration verification system is developed to show that the adversarial attack is a real threat to the digital communication signals identification model,which should be paid more attention in future research.展开更多
With the increasing popularity of fingerprint identification technology, its security and privacy have been paid much attention. Only the security and privacy of biological information are insured, the biological tech...With the increasing popularity of fingerprint identification technology, its security and privacy have been paid much attention. Only the security and privacy of biological information are insured, the biological technology can be better accepted and used by the public. In this paper, we propose a novel quantum bit（qbit）-based scheme to solve the security and privacy problem existing in the traditional fingerprint identification system. By exploiting the properties of quantum mechanics, our proposed scheme, cancelable remote quantum fingerprint templates protection scheme, can achieve the unconditional security guaranteed in an information-theoretical sense. Moreover, this novel quantum scheme can invalidate most of the attacks aimed at the fingerprint identification system. In addition, the proposed scheme is applicable to the requirement of remote communication with no need to worry about its security and privacy during the transmission. This is an absolute advantage when comparing with other traditional methods. Security analysis shows that the proposed scheme can effectively ensure the communication security and the privacy of users＇ information for the fingerprint identification.展开更多
基金supported by the National Natural Science Foundation of China(61771154)the Fundamental Research Funds for the Central Universities(3072022CF0601)supported by Key Laboratory of Advanced Marine Communication and Information Technology,Ministry of Industry and Information Technology,Harbin Engineering University,Harbin,China.
文摘As modern communication technology advances apace,the digital communication signals identification plays an important role in cognitive radio networks,the communication monitoring and management systems.AI has become a promising solution to this problem due to its powerful modeling capability,which has become a consensus in academia and industry.However,because of the data-dependence and inexplicability of AI models and the openness of electromagnetic space,the physical layer digital communication signals identification model is threatened by adversarial attacks.Adversarial examples pose a common threat to AI models,where well-designed and slight perturbations added to input data can cause wrong results.Therefore,the security of AI models for the digital communication signals identification is the premise of its efficient and credible applications.In this paper,we first launch adversarial attacks on the end-to-end AI model for automatic modulation classifi-cation,and then we explain and present three defense mechanisms based on the adversarial principle.Next we present more detailed adversarial indicators to evaluate attack and defense behavior.Finally,a demonstration verification system is developed to show that the adversarial attack is a real threat to the digital communication signals identification model,which should be paid more attention in future research.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.61379153 and 61572529)
文摘With the increasing popularity of fingerprint identification technology, its security and privacy have been paid much attention. Only the security and privacy of biological information are insured, the biological technology can be better accepted and used by the public. In this paper, we propose a novel quantum bit（qbit）-based scheme to solve the security and privacy problem existing in the traditional fingerprint identification system. By exploiting the properties of quantum mechanics, our proposed scheme, cancelable remote quantum fingerprint templates protection scheme, can achieve the unconditional security guaranteed in an information-theoretical sense. Moreover, this novel quantum scheme can invalidate most of the attacks aimed at the fingerprint identification system. In addition, the proposed scheme is applicable to the requirement of remote communication with no need to worry about its security and privacy during the transmission. This is an absolute advantage when comparing with other traditional methods. Security analysis shows that the proposed scheme can effectively ensure the communication security and the privacy of users＇ information for the fingerprint identification.
