In vehicle edge computing(VEC),asynchronous federated learning(AFL)is used,where the edge receives a local model and updates the global model,effectively reducing the global aggregation latency.Due to different amount...In vehicle edge computing(VEC),asynchronous federated learning(AFL)is used,where the edge receives a local model and updates the global model,effectively reducing the global aggregation latency.Due to different amounts of local data,computing capabilities and locations of the vehicles,renewing the global model with same weight is inappropriate.The above factors will affect the local calculation time and upload time of the local model,and the vehicle may also be affected by Byzantine attacks,leading to the deterioration of the vehicle data.However,based on deep reinforcement learning(DRL),we can consider these factors comprehensively to eliminate vehicles with poor performance as much as possible and exclude vehicles that have suffered Byzantine attacks before AFL.At the same time,when aggregating AFL,we can focus on those vehicles with better performance to improve the accuracy and safety of the system.In this paper,we proposed a vehicle selection scheme based on DRL in VEC.In this scheme,vehicle’s mobility,channel conditions with temporal variations,computational resources with temporal variations,different data amount,transmission channel status of vehicles as well as Byzantine attacks were taken into account.Simulation results show that the proposed scheme effectively improves the safety and accuracy of the global model.展开更多
The cache-based covert channel is one of the common vulnerabilities exploited in the Spectre attacks.Current mitigation strategies focus on blocking the eviction-based channel by using a random/encrypted mapping funct...The cache-based covert channel is one of the common vulnerabilities exploited in the Spectre attacks.Current mitigation strategies focus on blocking the eviction-based channel by using a random/encrypted mapping function to translate memory address to the cache address,while the updated-based channel is still vulnerable.In addition,some mitigation strategies are also costly as it needs software and hardware modifications.In this paper,our objective is to devise low-cost,comprehensive-protection techniques for mitigating the Spectre attacks.We proposed a novel cache structure,named EBCache,which focuses on the RISC-V processor and applies the address encryption and blacklist to resist the Spectre attacks.The addresses encryption mechanism increases the difficulty of pruning a minimal eviction set.The blacklist mechanism makes the updated cache lines loaded by the malicious updates invisible.Our experiments demonstrated that the EBCache can prevent malicious modifications.The EBCache,however,reduces the processor’s performance by about 23%but involves only a low-cost modification in the hardware.展开更多
Owing to the integration of energy digitization and artificial intelligence technology,smart energy grids can realize the stable,efficient and clean operation of power systems.However,the emergence of cyber-physical a...Owing to the integration of energy digitization and artificial intelligence technology,smart energy grids can realize the stable,efficient and clean operation of power systems.However,the emergence of cyber-physical attacks,such as dynamic load-altering attacks(DLAAs)has introduced great challenges to the security of smart energy grids.Thus,this study developed a novel cyber-physical collaborative security framework for DLAAs in smart energy grids.The proposed framework integrates attack prediction in the cyber layer with the detection and localization of attacks in the physical layer.First,a data-driven method was proposed to predict the DLAA sequence in the cyber layer.By designing a double radial basis function network,the influence of disturbances on attack prediction can be eliminated.Based on the prediction results,an unknown input observer-based detection and localization method was further developed for the physical layer.In addition,an adaptive threshold was designed to replace the traditional precomputed threshold and improve the detection performance of the DLAAs.Consequently,through the collaborative work of the cyber-physics layer,injected DLAAs were effectively detected and located.Compared with existing methodologies,the simulation results on IEEE 14-bus and 118-bus power systems verified the superiority of the proposed cyber-physical collaborative detection and localization against DLAAs.展开更多
Link flooding attack(LFA)is a type of covert distributed denial of service(DDoS)attack.The attack mechanism of LFAs is to flood critical links within the network to cut off the target area from the Internet.Recently,t...Link flooding attack(LFA)is a type of covert distributed denial of service(DDoS)attack.The attack mechanism of LFAs is to flood critical links within the network to cut off the target area from the Internet.Recently,the proliferation of Internet of Things(IoT)has increased the quantity of vulnerable devices connected to the network and has intensified the threat of LFAs.In LFAs,attackers typically utilize low-speed flows that do not reach the victims,making the attack difficult to detect.Traditional LFA defense methods mainly reroute the attack traffic around the congested link,which encounters high complexity and high computational overhead due to the aggregation of massive attack traffic.To address these challenges,we present an LFA defense framework which can mitigate the attack flows at the border switches when they are small in scale.This framework is lightweight and can be deployed at border switches of the network in a distributed manner,which ensures the scalability of our defense system.The performance of our framework is assessed in an experimental environment.The simulation results indicate that our method is effective in detecting and mitigating LFAs with low time complexity.展开更多
A critical problem in the cube attack is how to recover superpolies efficiently.As the targeting number of rounds of an iterative stream cipher increases,the scale of its superpolies becomes larger and larger.Recently...A critical problem in the cube attack is how to recover superpolies efficiently.As the targeting number of rounds of an iterative stream cipher increases,the scale of its superpolies becomes larger and larger.Recently,to recover massive superpolies,the nested monomial prediction technique,the algorithm based on the divide-and-conquer strategy,and stretching cube attacks were proposed,which have been used to recover a superpoly with over ten million monomials for the NFSR-based stream ciphers such as Trivium and Grain-128AEAD.Nevertheless,when these methods are used to recover superpolies,many invalid calculations are performed,which makes recovering superpolies more difficult.This study finds an interesting observation that can be used to improve the above methods.Based on the observation,a new method is proposed to avoid a part of invalid calculations during the process of recovering superpolies.Then,the new method is applied to the nested monomial prediction technique and an improved superpoly recovery framework is presented.To verify the effectiveness of the proposed scheme,the improved framework is applied to 844-and 846-round Trivium and the exact ANFs of the superpolies is obtained with over one hundred million monomials,showing the improved superpoly recovery technique is powerful.Besides,extensive experiments on other scaled-down variants of NFSR-based stream ciphers show that the proposed scheme indeed could be more efficient on the superpoly recovery against NFSR-based stream ciphers.展开更多
In this paper,the fixed-time time-varying formation of heterogeneous multi-agent systems(MASs) based on tracking error observer under denial-of-service(DoS) attacks is investigated.Firstly,the dynamic pinning strategy...In this paper,the fixed-time time-varying formation of heterogeneous multi-agent systems(MASs) based on tracking error observer under denial-of-service(DoS) attacks is investigated.Firstly,the dynamic pinning strategy is used to reconstruct the communication channel for the system that suffers from DoS attacks to prevent the discontinuous transmission information of the communication network from affecting MASs formation.Then,considering that the leader state is not available to each follower under DoS attacks,a fixed-time distributed observer without velocity information is constructed to estimate the tracking error between followers and the leader.Finally,adaptive radial basis function neural network(RBFNN) is used to approximate the unknown ensemble disturbances in the system,and the fixed-time time-varying formation scheme is designed with the constructed observer.The effectiveness of the proposed control algorithm is demonstrated by the numerical simulation.展开更多
Recently,several PC oracle based side-channel attacks have been proposed against Kyber.However,most of them focus on unprotected implementations and masking is considered as a counter-measure.In this study,we extend P...Recently,several PC oracle based side-channel attacks have been proposed against Kyber.However,most of them focus on unprotected implementations and masking is considered as a counter-measure.In this study,we extend PC oracle based side-channel attacks to the second-order scenario and successfully conduct key-recovery attacks on the first-order masked Kyber.Firstly,we analyze the potential joint information leakage.Inspired by the binary PC oracle based attack proposed by Qin et al.at Asiacrypt 2021,we identify the 1-bit leakage scenario in the masked Keccak implementation.Moreover,we modify the ciphertexts construction described by Tanaka et al.at CHES 2023,extending the leakage scenario from 1-bit to 32-bit.With the assistance of TVLA,we validate these leakages through experiments.Secondly,for these two scenarios,we construct a binary PC oracle based on t-test and a multiple-valued PC oracle based on neural networks.Furthermore,we conduct practical side-channel attacks on masked Kyber by utilizing our oracles,with the implementation running on an ARM Cortex-M4 microcontroller.The demonstrated attacks require a minimum of 15788 and 648 traces to fully recover the key of Kyber768 in the 1-bit leakage scenario and the 32-bit leakage scenario,respectively.Our analysis may also be extended to attack other post-quantum schemes that use the same masked hash function.Finally,we apply the shuffling strategy to the first-order masked imple-mentation of the Kyber and perform leakage tests.Experimental results show that the combination strategy of shuffling and masking can effectively resist our proposed attacks.展开更多
Given the rapid development of advanced information systems,microgrids(MGs)suffer from more potential attacks that affect their operational performance.Conventional distributed secondary control with a small,fixed sam...Given the rapid development of advanced information systems,microgrids(MGs)suffer from more potential attacks that affect their operational performance.Conventional distributed secondary control with a small,fixed sampling time period inevitably causes the wasteful use of communication resources.This paper proposes a self-triggered secondary control scheme under perturbations from false data injection(FDI)attacks.We designed a linear clock for each DG to trigger its controller at aperiodic and intermittent instants.Sub-sequently,a hash-based defense mechanism(HDM)is designed for detecting and eliminating malicious data infiltrated in the MGs.With the aid of HDM,a self-triggered control scheme achieves the secondary control objectives even in the presence of FDI attacks.Rigorous theoretical analyses and simulation results indicate that the introduced secondary control scheme significantly reduces communication costs and enhances the resilience of MGs under FDI attacks.展开更多
Searchable public key encryption is a useful cryptographic paradigm that enables an untrustworthy server to retrieve the encrypted data without revealing the contents of the data. It offers a promising solution to enc...Searchable public key encryption is a useful cryptographic paradigm that enables an untrustworthy server to retrieve the encrypted data without revealing the contents of the data. It offers a promising solution to encrypted data retrieval in cryptographic cloud storage. Certificateless public key cryptography (CLPKC) is a novel cryptographic primitive that has many merits. It overcomes the key escrow problem in identity-based cryptography (IBC) and the cumbersome certificate problem in conventional public key cryptography (PKC). Motivated by the appealing features of CLPKC, several certificateless encryption with keyword search (CLEKS) schemes have been presented in the literature. But, our cryptanalysis demonstrates that the previously proposed CLEKS frameworks suffer from the security vulnerability caused by the keyword guessing attack. To remedy the security weakness in the previous frameworks and provide resistance against both inside and outside keyword guessing attacks, we propose a new CLEKS framework. Under the new framework, we design a concrete CLEKS scheme and formally prove its security in the random oracle model. Compared with previous two CLEKS schemes, the proposed scheme has better overall performance while offering stronger security guarantee as it withstands the existing known types of keyword guessing attacks.展开更多
A new 5-round distinguisher of AES with key whitening is presented by using the properties of its round transformation. Based on this distinguisher,we present new meet-in-the-middle attacks on reduced AES considering ...A new 5-round distinguisher of AES with key whitening is presented by using the properties of its round transformation. Based on this distinguisher,we present new meet-in-the-middle attacks on reduced AES considering the key schedule and the time-memory tradeoff approach. New attacks improve the best known meet-in-the-middle attacks on reduced AES presented at FSE2008.We reduce the time complexity of attacks on 7-round AES-192 and 8-round AES-256 by a factor of at least 28. Moreover,the distinguisher can be exploited to develop the attack on 8-round AES-192.展开更多
Co-residency of virtual machines(VMs) of different tenants on the same physical platform would possibly lead to cross-VM side-channel attacks in the cloud. While most of current countermeasures fail for real or immedi...Co-residency of virtual machines(VMs) of different tenants on the same physical platform would possibly lead to cross-VM side-channel attacks in the cloud. While most of current countermeasures fail for real or immediate deployment due to their requirement for modification of virtualization structure, we adopt dynamic migration, an inherent mechanism of the cloud platform, as a general defense against this kind of threats. To this end, we first set up a unified practical information leakage model which shows the factors affecting side channels and describes the way they influence the damage due to side-channel attacks. Since migration is adopted to limit the time duration of co-residency, we envision this defense as an optimization problem by setting up an Integer Linear Programming(ILP) to calculate optimal migration strategy, which is intractable due to high computational complexity. Therefore, we approximate the ILP with a baseline genetic algorithm, which is further improved for its optimality and scalability. Experimental results show that our migration-based defense can not only provide excellent security guarantees and affordable performance cost in both theoretical simulation and practical cloud environment, but also achieve better optimality and scalability than previous countermeasures.展开更多
Faced with the evolving attacks in recommender systems, many detection features have been proposed by human engineering and used in supervised or unsupervised detection methods. However, the detection features extract...Faced with the evolving attacks in recommender systems, many detection features have been proposed by human engineering and used in supervised or unsupervised detection methods. However, the detection features extracted by human engineering are usually aimed at some specific types of attacks. To further detect other new types of attacks, the traditional methods have to re-extract detection features with high knowledge cost. To address these limitations, the method for automatic extraction of robust features is proposed and then an Adaboost-based detection method is presented. Firstly, to obtain robust representation with prior knowledge, unlike uniform corruption rate in traditional mLDA(marginalized Linear Denoising Autoencoder), different corruption rates for items are calculated according to the ratings’ distribution. Secondly, the ratings sparsity is used to weight the mapping matrix to extract low-dimensional representation. Moreover, the uniform corruption rate is also set to the next layer in mSLDA(marginalized Stacked Linear Denoising Autoencoder) to extract the stable and robust user features. Finally, under the robust feature space, an Adaboost-based detection method is proposed to alleviate the imbalanced classification problem. Experimental results on the Netflix and Amazon review datasets indicate that the proposed method can effectively detect various attacks.展开更多
With the increasing deployment of wireless sensordevices and networks,security becomes a criticalchallenge for sensor networks.In this paper,a schemeusing data mining is proposed for routing anomalydetection in wirele...With the increasing deployment of wireless sensordevices and networks,security becomes a criticalchallenge for sensor networks.In this paper,a schemeusing data mining is proposed for routing anomalydetection in wireless sensor networks.The schemeuses the Apriori algorithm to extract traffic patternsfrom both routing table and network traffic packetsand subsequently the K-means cluster algorithmadaptively generates a detection model.Through thecombination of these two algorithms,routing attackscan be detected effectively and automatically.Themain advantage of the proposed approach is that it isable to detect new attacks that have not previouslybeen seen.Moreover,the proposed detection schemeis based on no priori knowledge and then can beapplied to a wide range of different sensor networksfor a variety of routing attacks.展开更多
Software Defined Networking(SDN) is a revolutionary networking paradigm towards the future network,experiencing rapid development nowadays.However,its main characteristic,the separation of control plane and data plane...Software Defined Networking(SDN) is a revolutionary networking paradigm towards the future network,experiencing rapid development nowadays.However,its main characteristic,the separation of control plane and data plane,also brings about new security challenges,i.e.,Denial-of-Service(DoS) attacks specific to Open Flow SDN networks to exhaust the control plane bandwidth and overload the buffer memory of Open Flow switch.To mitigate the DoS attacks in the Open Flow networks,we design and implement SGuard,a security application on top of the NOX controller that mainly contains two modules:Access control module and Classification module.We employ novel six-tuple as feature vector to classify traffic flows,meanwhile optimizing classification by feature ranking and selecting algorithms.All the modules will cooperate with each other to complete a series of tasks such as authorization,classification and so on.At the end of this paper,we experimentally use Mininet to evaluate SGuard in a software environment.The results show that SGuard works efficiently and accurately without adding more overhead to the SDN networks.展开更多
Nowadays the modular multiplications in many kinds of smartcards are utilized Montgomery's algorithm modular multiplier, so traditional SPA to RSA becomes invalid. An improved attack method is proposed based on SP...Nowadays the modular multiplications in many kinds of smartcards are utilized Montgomery's algorithm modular multiplier, so traditional SPA to RSA becomes invalid. An improved attack method is proposed based on SPA which just depends on the fact that there exist some subtle differences in each loop during the operation of cd mod n. At same time, compared with the traditional SPA, it doesn't need to select the clear text or some known message. Using this method, attacks can easy to discover the mode of RSA implementation and extract the bits of decryption key just based on a few collected traces. From the real attack test on several main kinds of smartcard, the private keys of RSA stored inside can be analyzed successfully.展开更多
AEZ is an AES-based authenticated encryption submitted to the ongoing CAESAR competition and was presented at Eurocrypt2015 with AEZ v3. There are three models for AEZ, AEZ-core, AEZ-tiny and AEZ-prf. In this paper, w...AEZ is an AES-based authenticated encryption submitted to the ongoing CAESAR competition and was presented at Eurocrypt2015 with AEZ v3. There are three models for AEZ, AEZ-core, AEZ-tiny and AEZ-prf. In this paper, we consider the security of AEZprf for AEZ v4.2, the latest version of AEZ.Our major finding is a collision of any 256-bit associated data for AES-prf. Then we launch collision attacks in a quantum setting and a classical setting respectively under different assumptions. In the quantum setting, by Simon's quantum algorithm, we amount a forgery with O(n) quantum superposition queries and an overwhelming probability close to 1.In the classical setting, one with the key of AEZ-prf can also construct the forgeries. Our results show that the AEZ-prf models of AEZ v4.2 is not secure in both the quantum setting and classical world. Furthermore, our results can also be applied to AEZ v3, which has been published on Eurocrypt 2015. As far as we know, no cryptanalysis of AEZ v4.2 has been published so far.展开更多
The spectrum sensing model based on deep learning has achieved satisfying detection per-formence,but its robustness has not been verified.In this paper,we propose primary user adversarial attack(PUAA)to verify the rob...The spectrum sensing model based on deep learning has achieved satisfying detection per-formence,but its robustness has not been verified.In this paper,we propose primary user adversarial attack(PUAA)to verify the robustness of the deep learning based spectrum sensing model.PUAA adds a care-fully manufactured perturbation to the benign primary user signal,which greatly reduces the probability of detection of the spectrum sensing model.We design three PUAA methods in black box scenario.In or-der to defend against PUAA,we propose a defense method based on autoencoder named DeepFilter.We apply the long short-term memory network and the convolutional neural network together to DeepFilter,so that it can extract the temporal and local features of the input signal at the same time to achieve effective defense.Extensive experiments are conducted to eval-uate the attack effect of the designed PUAA method and the defense effect of DeepFilter.Results show that the three PUAA methods designed can greatly reduce the probability of detection of the deep learning-based spectrum sensing model.In addition,the experimen-tal results of the defense effect of DeepFilter show that DeepFilter can effectively defend against PUAA with-out affecting the detection performance of the model.展开更多
Similar to device-independent quantum key distribution （DI-QKD）, semi-device-independent quantum key distribu- tion （SDI-QKD） provides secure key distribution without any assumptions about the internal workings of...Similar to device-independent quantum key distribution （DI-QKD）, semi-device-independent quantum key distribu- tion （SDI-QKD） provides secure key distribution without any assumptions about the internal workings of the QKD devices. The only assumption is that the dimension of the Hilbert space is bounded. But SDI-QKD can be implemented in a one- way prepare-and-measure configuration without entanglement compared with DI-QKD. We propose a practical SDI-QKD protocol with four preparation states and three measurement bases by considering the maximal violation of dimension witnesses and specific processes of a QKD protocol. Moreover, we prove the security of the SDI-QKD protocol against collective attacks based on the min-entropy and dimension witnesses. We also show a comparison of the secret key rate between the SDI-QKD protocol and the standard QKD.展开更多
Objective To determine the safety and efficacy of fresh frozen plasma （FFP） iniusion for the treat- ment of hereditary angioedema （FIAE）. Methods The medical records of patients with HAE admitted to Peking Union ...Objective To determine the safety and efficacy of fresh frozen plasma （FFP） iniusion for the treat- ment of hereditary angioedema （FIAE）. Methods The medical records of patients with HAE admitted to Peking Union Medical College Fiospital who had received FFP infusion during 2004 and 2010 were reviewed and PubMed database iFom 1966 to the present were searched using the following key words： hereditary angioedema and fresh frozen plasma. The patient＇s age, sex, body location of HAE attacks, the dose of FFP infusion, time of beginning to improvenaent, time to complete remission, complication, C 1 inhibitor activity, and outcome were analyzed. Results A total of 13 enrolled patients （7 male and 6 female） received 16 times of FFP infusion, in- cluding 2 patients undergoing FFP infusion in Peking Union Medical College Hospital and 11 patients re- ported in the literature. The mean dosage of FFP infusion was 586±337 mL. Two cases suffered from wors- ening abdominal pain and one case experienced skin rash. Only I patient had no improvement in symptom owing to transfusion related reaction. There was a definite improvement in symptom 49± 19 minutes after beginning FFP infusion. The remission time decreased from 61.7±27.0 hours to 3.3 （2.0, 12.0） hours after FFP infusion. FFP infusion was effective for both type I and type Ⅱ HAE. Conclusion FFP seems to be safe and effective for acute attacks of HAE.展开更多
To protect the copyright of the image as well as the image quality, a kind of image zero-watermark method based on the Krawtchouk moment invariants and timestamp is proposed. A method is used to protect the image, in ...To protect the copyright of the image as well as the image quality, a kind of image zero-watermark method based on the Krawtchouk moment invariants and timestamp is proposed. A method is used to protect the image, in which features are drawn out from the image as the watermarking. The main steps of the method are presented. Firstly, some low-order moment invariants of the image are extracted. Secondly, the moment invariants and the key are registered to a fair third party to gain the timestamp. Finally, the timestamp can be used to prove who the real owner is. The processing method is simple, only with a few low-order moment invariants to be computed. Experimental results are obtained and compared with those of the method based on geometric moment invariants. Results show that the scheme can well withstand such geometrical attacks as rotating, scaling, cropping, combined attack, translating, removing lines, filtering, and JPEG lossy compression.展开更多
基金supported in part by the National Natural Science Foundation of China(No.61701197)in part by the National Key Research and Development Program of China(No.2021YFA1000500(4))in part by the 111 Project(No.B23008).
文摘In vehicle edge computing(VEC),asynchronous federated learning(AFL)is used,where the edge receives a local model and updates the global model,effectively reducing the global aggregation latency.Due to different amounts of local data,computing capabilities and locations of the vehicles,renewing the global model with same weight is inappropriate.The above factors will affect the local calculation time and upload time of the local model,and the vehicle may also be affected by Byzantine attacks,leading to the deterioration of the vehicle data.However,based on deep reinforcement learning(DRL),we can consider these factors comprehensively to eliminate vehicles with poor performance as much as possible and exclude vehicles that have suffered Byzantine attacks before AFL.At the same time,when aggregating AFL,we can focus on those vehicles with better performance to improve the accuracy and safety of the system.In this paper,we proposed a vehicle selection scheme based on DRL in VEC.In this scheme,vehicle’s mobility,channel conditions with temporal variations,computational resources with temporal variations,different data amount,transmission channel status of vehicles as well as Byzantine attacks were taken into account.Simulation results show that the proposed scheme effectively improves the safety and accuracy of the global model.
基金This work was supported in part by the China Ministry of Science and Technology under Grant 2015GA600002。
文摘The cache-based covert channel is one of the common vulnerabilities exploited in the Spectre attacks.Current mitigation strategies focus on blocking the eviction-based channel by using a random/encrypted mapping function to translate memory address to the cache address,while the updated-based channel is still vulnerable.In addition,some mitigation strategies are also costly as it needs software and hardware modifications.In this paper,our objective is to devise low-cost,comprehensive-protection techniques for mitigating the Spectre attacks.We proposed a novel cache structure,named EBCache,which focuses on the RISC-V processor and applies the address encryption and blacklist to resist the Spectre attacks.The addresses encryption mechanism increases the difficulty of pruning a minimal eviction set.The blacklist mechanism makes the updated cache lines loaded by the malicious updates invisible.Our experiments demonstrated that the EBCache can prevent malicious modifications.The EBCache,however,reduces the processor’s performance by about 23%but involves only a low-cost modification in the hardware.
基金supported by the National Nature Science Foundation of China under 62203376the Science and Technology Plan of Hebei Education Department under QN2021139+1 种基金the Nature Science Foundation of Hebei Province under F2021203043the Open Research Fund of Jiangsu Collaborative Innovation Center for Smart Distribution Network,Nanjing Institute of Technology under No.XTCX202203.
文摘Owing to the integration of energy digitization and artificial intelligence technology,smart energy grids can realize the stable,efficient and clean operation of power systems.However,the emergence of cyber-physical attacks,such as dynamic load-altering attacks(DLAAs)has introduced great challenges to the security of smart energy grids.Thus,this study developed a novel cyber-physical collaborative security framework for DLAAs in smart energy grids.The proposed framework integrates attack prediction in the cyber layer with the detection and localization of attacks in the physical layer.First,a data-driven method was proposed to predict the DLAA sequence in the cyber layer.By designing a double radial basis function network,the influence of disturbances on attack prediction can be eliminated.Based on the prediction results,an unknown input observer-based detection and localization method was further developed for the physical layer.In addition,an adaptive threshold was designed to replace the traditional precomputed threshold and improve the detection performance of the DLAAs.Consequently,through the collaborative work of the cyber-physics layer,injected DLAAs were effectively detected and located.Compared with existing methodologies,the simulation results on IEEE 14-bus and 118-bus power systems verified the superiority of the proposed cyber-physical collaborative detection and localization against DLAAs.
基金supported in part by the National Key R&D Program of China under Grant 2018YFA0701601in part by the National Natural Science Foundation of China(Grant No.62201605,62341110,U22A2002)in part by Tsinghua University-China Mobile Communications Group Co.,Ltd.Joint Institute。
文摘Link flooding attack(LFA)is a type of covert distributed denial of service(DDoS)attack.The attack mechanism of LFAs is to flood critical links within the network to cut off the target area from the Internet.Recently,the proliferation of Internet of Things(IoT)has increased the quantity of vulnerable devices connected to the network and has intensified the threat of LFAs.In LFAs,attackers typically utilize low-speed flows that do not reach the victims,making the attack difficult to detect.Traditional LFA defense methods mainly reroute the attack traffic around the congested link,which encounters high complexity and high computational overhead due to the aggregation of massive attack traffic.To address these challenges,we present an LFA defense framework which can mitigate the attack flows at the border switches when they are small in scale.This framework is lightweight and can be deployed at border switches of the network in a distributed manner,which ensures the scalability of our defense system.The performance of our framework is assessed in an experimental environment.The simulation results indicate that our method is effective in detecting and mitigating LFAs with low time complexity.
基金National Natural Science Foundation of China(62372464)。
文摘A critical problem in the cube attack is how to recover superpolies efficiently.As the targeting number of rounds of an iterative stream cipher increases,the scale of its superpolies becomes larger and larger.Recently,to recover massive superpolies,the nested monomial prediction technique,the algorithm based on the divide-and-conquer strategy,and stretching cube attacks were proposed,which have been used to recover a superpoly with over ten million monomials for the NFSR-based stream ciphers such as Trivium and Grain-128AEAD.Nevertheless,when these methods are used to recover superpolies,many invalid calculations are performed,which makes recovering superpolies more difficult.This study finds an interesting observation that can be used to improve the above methods.Based on the observation,a new method is proposed to avoid a part of invalid calculations during the process of recovering superpolies.Then,the new method is applied to the nested monomial prediction technique and an improved superpoly recovery framework is presented.To verify the effectiveness of the proposed scheme,the improved framework is applied to 844-and 846-round Trivium and the exact ANFs of the superpolies is obtained with over one hundred million monomials,showing the improved superpoly recovery technique is powerful.Besides,extensive experiments on other scaled-down variants of NFSR-based stream ciphers show that the proposed scheme indeed could be more efficient on the superpoly recovery against NFSR-based stream ciphers.
文摘In this paper,the fixed-time time-varying formation of heterogeneous multi-agent systems(MASs) based on tracking error observer under denial-of-service(DoS) attacks is investigated.Firstly,the dynamic pinning strategy is used to reconstruct the communication channel for the system that suffers from DoS attacks to prevent the discontinuous transmission information of the communication network from affecting MASs formation.Then,considering that the leader state is not available to each follower under DoS attacks,a fixed-time distributed observer without velocity information is constructed to estimate the tracking error between followers and the leader.Finally,adaptive radial basis function neural network(RBFNN) is used to approximate the unknown ensemble disturbances in the system,and the fixed-time time-varying formation scheme is designed with the constructed observer.The effectiveness of the proposed control algorithm is demonstrated by the numerical simulation.
基金National Natural Science Foundation of China(62472397)Innovation Program for Quantum Science and Technology(2021ZD0302902)。
文摘Recently,several PC oracle based side-channel attacks have been proposed against Kyber.However,most of them focus on unprotected implementations and masking is considered as a counter-measure.In this study,we extend PC oracle based side-channel attacks to the second-order scenario and successfully conduct key-recovery attacks on the first-order masked Kyber.Firstly,we analyze the potential joint information leakage.Inspired by the binary PC oracle based attack proposed by Qin et al.at Asiacrypt 2021,we identify the 1-bit leakage scenario in the masked Keccak implementation.Moreover,we modify the ciphertexts construction described by Tanaka et al.at CHES 2023,extending the leakage scenario from 1-bit to 32-bit.With the assistance of TVLA,we validate these leakages through experiments.Secondly,for these two scenarios,we construct a binary PC oracle based on t-test and a multiple-valued PC oracle based on neural networks.Furthermore,we conduct practical side-channel attacks on masked Kyber by utilizing our oracles,with the implementation running on an ARM Cortex-M4 microcontroller.The demonstrated attacks require a minimum of 15788 and 648 traces to fully recover the key of Kyber768 in the 1-bit leakage scenario and the 32-bit leakage scenario,respectively.Our analysis may also be extended to attack other post-quantum schemes that use the same masked hash function.Finally,we apply the shuffling strategy to the first-order masked imple-mentation of the Kyber and perform leakage tests.Experimental results show that the combination strategy of shuffling and masking can effectively resist our proposed attacks.
基金supported by Hainan Provincial Natural Science Foundation of China(No.524RC532)Research Startup Funding from Hainan Institute of Zhejiang University(No.0210-6602-A12202)Project of Sanya Yazhou Bay Science and Technology City(No.SKJC-2022-PTDX-009/010/011).
文摘Given the rapid development of advanced information systems,microgrids(MGs)suffer from more potential attacks that affect their operational performance.Conventional distributed secondary control with a small,fixed sampling time period inevitably causes the wasteful use of communication resources.This paper proposes a self-triggered secondary control scheme under perturbations from false data injection(FDI)attacks.We designed a linear clock for each DG to trigger its controller at aperiodic and intermittent instants.Sub-sequently,a hash-based defense mechanism(HDM)is designed for detecting and eliminating malicious data infiltrated in the MGs.With the aid of HDM,a self-triggered control scheme achieves the secondary control objectives even in the presence of FDI attacks.Rigorous theoretical analyses and simulation results indicate that the introduced secondary control scheme significantly reduces communication costs and enhances the resilience of MGs under FDI attacks.
基金supported by the National Natural Science Foundation of China under Grant Nos. 61772009 and U1736112the Natural Science Foundation of Jiangsu Province under Grant Nos. BK20161511 and BK20181304
文摘Searchable public key encryption is a useful cryptographic paradigm that enables an untrustworthy server to retrieve the encrypted data without revealing the contents of the data. It offers a promising solution to encrypted data retrieval in cryptographic cloud storage. Certificateless public key cryptography (CLPKC) is a novel cryptographic primitive that has many merits. It overcomes the key escrow problem in identity-based cryptography (IBC) and the cumbersome certificate problem in conventional public key cryptography (PKC). Motivated by the appealing features of CLPKC, several certificateless encryption with keyword search (CLEKS) schemes have been presented in the literature. But, our cryptanalysis demonstrates that the previously proposed CLEKS frameworks suffer from the security vulnerability caused by the keyword guessing attack. To remedy the security weakness in the previous frameworks and provide resistance against both inside and outside keyword guessing attacks, we propose a new CLEKS framework. Under the new framework, we design a concrete CLEKS scheme and formally prove its security in the random oracle model. Compared with previous two CLEKS schemes, the proposed scheme has better overall performance while offering stronger security guarantee as it withstands the existing known types of keyword guessing attacks.
基金supported by the Nature Science Foundation of China under grant 60970119, 60833008the National Basic Research Program of China(973) under grant 2007CB311201the Fundamental Research Funds for the Central Universities under grant K50510010018
文摘A new 5-round distinguisher of AES with key whitening is presented by using the properties of its round transformation. Based on this distinguisher,we present new meet-in-the-middle attacks on reduced AES considering the key schedule and the time-memory tradeoff approach. New attacks improve the best known meet-in-the-middle attacks on reduced AES presented at FSE2008.We reduce the time complexity of attacks on 7-round AES-192 and 8-round AES-256 by a factor of at least 28. Moreover,the distinguisher can be exploited to develop the attack on 8-round AES-192.
基金supported by the National Key Research and Development Program of China (2018YFB0804004)the Foundation of the National Natural Science Foundation of China (61602509)+1 种基金the Foundation for Innovative Research Groups of the National Natural Science Foundation of China (61521003)the Key Technologies Research and Development Program of Henan Province of China (172102210615)
文摘Co-residency of virtual machines(VMs) of different tenants on the same physical platform would possibly lead to cross-VM side-channel attacks in the cloud. While most of current countermeasures fail for real or immediate deployment due to their requirement for modification of virtualization structure, we adopt dynamic migration, an inherent mechanism of the cloud platform, as a general defense against this kind of threats. To this end, we first set up a unified practical information leakage model which shows the factors affecting side channels and describes the way they influence the damage due to side-channel attacks. Since migration is adopted to limit the time duration of co-residency, we envision this defense as an optimization problem by setting up an Integer Linear Programming(ILP) to calculate optimal migration strategy, which is intractable due to high computational complexity. Therefore, we approximate the ILP with a baseline genetic algorithm, which is further improved for its optimality and scalability. Experimental results show that our migration-based defense can not only provide excellent security guarantees and affordable performance cost in both theoretical simulation and practical cloud environment, but also achieve better optimality and scalability than previous countermeasures.
基金supported by the National Natural Science Foundation of China [Nos. 61772452, 61379116]the Scientific and Technological Innovation Programs of Higher Education Institutions in Shanxi [No.2019L0847]the Natural Science Foundation of Hebei Province, China [No. F2015203046]
文摘Faced with the evolving attacks in recommender systems, many detection features have been proposed by human engineering and used in supervised or unsupervised detection methods. However, the detection features extracted by human engineering are usually aimed at some specific types of attacks. To further detect other new types of attacks, the traditional methods have to re-extract detection features with high knowledge cost. To address these limitations, the method for automatic extraction of robust features is proposed and then an Adaboost-based detection method is presented. Firstly, to obtain robust representation with prior knowledge, unlike uniform corruption rate in traditional mLDA(marginalized Linear Denoising Autoencoder), different corruption rates for items are calculated according to the ratings’ distribution. Secondly, the ratings sparsity is used to weight the mapping matrix to extract low-dimensional representation. Moreover, the uniform corruption rate is also set to the next layer in mSLDA(marginalized Stacked Linear Denoising Autoencoder) to extract the stable and robust user features. Finally, under the robust feature space, an Adaboost-based detection method is proposed to alleviate the imbalanced classification problem. Experimental results on the Netflix and Amazon review datasets indicate that the proposed method can effectively detect various attacks.
基金the supports of the National Natural Science Foundation of China (60403027) the projects of science and research plan of Hubei provincial department of education (2003A011)the Natural Science Foundation Of Hubei Province of China (2005ABA243).
文摘With the increasing deployment of wireless sensordevices and networks,security becomes a criticalchallenge for sensor networks.In this paper,a schemeusing data mining is proposed for routing anomalydetection in wireless sensor networks.The schemeuses the Apriori algorithm to extract traffic patternsfrom both routing table and network traffic packetsand subsequently the K-means cluster algorithmadaptively generates a detection model.Through thecombination of these two algorithms,routing attackscan be detected effectively and automatically.Themain advantage of the proposed approach is that it isable to detect new attacks that have not previouslybeen seen.Moreover,the proposed detection schemeis based on no priori knowledge and then can beapplied to a wide range of different sensor networksfor a variety of routing attacks.
基金supported by the National key Research and Development Program of China(No.2016YFB0800100,2016YFB0800101)the National Natural Science Fund for Creative Research Groups Project(No.61521003)the National Natural Science Fund for Youth Found Project(No.61602509)
文摘Software Defined Networking(SDN) is a revolutionary networking paradigm towards the future network,experiencing rapid development nowadays.However,its main characteristic,the separation of control plane and data plane,also brings about new security challenges,i.e.,Denial-of-Service(DoS) attacks specific to Open Flow SDN networks to exhaust the control plane bandwidth and overload the buffer memory of Open Flow switch.To mitigate the DoS attacks in the Open Flow networks,we design and implement SGuard,a security application on top of the NOX controller that mainly contains two modules:Access control module and Classification module.We employ novel six-tuple as feature vector to classify traffic flows,meanwhile optimizing classification by feature ranking and selecting algorithms.All the modules will cooperate with each other to complete a series of tasks such as authorization,classification and so on.At the end of this paper,we experimentally use Mininet to evaluate SGuard in a software environment.The results show that SGuard works efficiently and accurately without adding more overhead to the SDN networks.
基金supported by the fundamental Research Funds for the Central University under Grant 2013JBM006
文摘Nowadays the modular multiplications in many kinds of smartcards are utilized Montgomery's algorithm modular multiplier, so traditional SPA to RSA becomes invalid. An improved attack method is proposed based on SPA which just depends on the fact that there exist some subtle differences in each loop during the operation of cd mod n. At same time, compared with the traditional SPA, it doesn't need to select the clear text or some known message. Using this method, attacks can easy to discover the mode of RSA implementation and extract the bits of decryption key just based on a few collected traces. From the real attack test on several main kinds of smartcard, the private keys of RSA stored inside can be analyzed successfully.
基金supported by the National Natural Science Foundation of China (Grant No.61572516, No.61272041 and No.61272488)
文摘AEZ is an AES-based authenticated encryption submitted to the ongoing CAESAR competition and was presented at Eurocrypt2015 with AEZ v3. There are three models for AEZ, AEZ-core, AEZ-tiny and AEZ-prf. In this paper, we consider the security of AEZprf for AEZ v4.2, the latest version of AEZ.Our major finding is a collision of any 256-bit associated data for AES-prf. Then we launch collision attacks in a quantum setting and a classical setting respectively under different assumptions. In the quantum setting, by Simon's quantum algorithm, we amount a forgery with O(n) quantum superposition queries and an overwhelming probability close to 1.In the classical setting, one with the key of AEZ-prf can also construct the forgeries. Our results show that the AEZ-prf models of AEZ v4.2 is not secure in both the quantum setting and classical world. Furthermore, our results can also be applied to AEZ v3, which has been published on Eurocrypt 2015. As far as we know, no cryptanalysis of AEZ v4.2 has been published so far.
基金the National Nat-ural Science Foundation of China under Grant No.62072406,No.U19B2016,No.U20B2038 and No.61871398the Natural Science Foundation of Zhejiang Province under Grant No.LY19F020025the Major Special Funding for“Science and Tech-nology Innovation 2025”in Ningbo under Grant No.2018B10063.
文摘The spectrum sensing model based on deep learning has achieved satisfying detection per-formence,but its robustness has not been verified.In this paper,we propose primary user adversarial attack(PUAA)to verify the robustness of the deep learning based spectrum sensing model.PUAA adds a care-fully manufactured perturbation to the benign primary user signal,which greatly reduces the probability of detection of the spectrum sensing model.We design three PUAA methods in black box scenario.In or-der to defend against PUAA,we propose a defense method based on autoencoder named DeepFilter.We apply the long short-term memory network and the convolutional neural network together to DeepFilter,so that it can extract the temporal and local features of the input signal at the same time to achieve effective defense.Extensive experiments are conducted to eval-uate the attack effect of the designed PUAA method and the defense effect of DeepFilter.Results show that the three PUAA methods designed can greatly reduce the probability of detection of the deep learning-based spectrum sensing model.In addition,the experimen-tal results of the defense effect of DeepFilter show that DeepFilter can effectively defend against PUAA with-out affecting the detection performance of the model.
基金Project supported by the National Basic Research Program of China(Grant No.2013CB338002)the National Natural Science Foundation of China(Grant Nos.11304397 and 11204379)
文摘Similar to device-independent quantum key distribution （DI-QKD）, semi-device-independent quantum key distribu- tion （SDI-QKD） provides secure key distribution without any assumptions about the internal workings of the QKD devices. The only assumption is that the dimension of the Hilbert space is bounded. But SDI-QKD can be implemented in a one- way prepare-and-measure configuration without entanglement compared with DI-QKD. We propose a practical SDI-QKD protocol with four preparation states and three measurement bases by considering the maximal violation of dimension witnesses and specific processes of a QKD protocol. Moreover, we prove the security of the SDI-QKD protocol against collective attacks based on the min-entropy and dimension witnesses. We also show a comparison of the secret key rate between the SDI-QKD protocol and the standard QKD.
文摘Objective To determine the safety and efficacy of fresh frozen plasma （FFP） iniusion for the treat- ment of hereditary angioedema （FIAE）. Methods The medical records of patients with HAE admitted to Peking Union Medical College Fiospital who had received FFP infusion during 2004 and 2010 were reviewed and PubMed database iFom 1966 to the present were searched using the following key words： hereditary angioedema and fresh frozen plasma. The patient＇s age, sex, body location of HAE attacks, the dose of FFP infusion, time of beginning to improvenaent, time to complete remission, complication, C 1 inhibitor activity, and outcome were analyzed. Results A total of 13 enrolled patients （7 male and 6 female） received 16 times of FFP infusion, in- cluding 2 patients undergoing FFP infusion in Peking Union Medical College Hospital and 11 patients re- ported in the literature. The mean dosage of FFP infusion was 586±337 mL. Two cases suffered from wors- ening abdominal pain and one case experienced skin rash. Only I patient had no improvement in symptom owing to transfusion related reaction. There was a definite improvement in symptom 49± 19 minutes after beginning FFP infusion. The remission time decreased from 61.7±27.0 hours to 3.3 （2.0, 12.0） hours after FFP infusion. FFP infusion was effective for both type I and type Ⅱ HAE. Conclusion FFP seems to be safe and effective for acute attacks of HAE.
文摘To protect the copyright of the image as well as the image quality, a kind of image zero-watermark method based on the Krawtchouk moment invariants and timestamp is proposed. A method is used to protect the image, in which features are drawn out from the image as the watermarking. The main steps of the method are presented. Firstly, some low-order moment invariants of the image are extracted. Secondly, the moment invariants and the key are registered to a fair third party to gain the timestamp. Finally, the timestamp can be used to prove who the real owner is. The processing method is simple, only with a few low-order moment invariants to be computed. Experimental results are obtained and compared with those of the method based on geometric moment invariants. Results show that the scheme can well withstand such geometrical attacks as rotating, scaling, cropping, combined attack, translating, removing lines, filtering, and JPEG lossy compression.
