检索结果-南通市图书馆

Anomaly Detection in Imbalanced Encrypted Traffic with Few Packet Metadata-Based Feature Extraction

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Computer Modeling in Engineering & Sciences 2024年第10期141卷 585-607页

作者： Min-Gyu Kim Hwankuk Kim Department of Financial information security Kookmin UniversitySeoul02707Republic of Korea Department of information security cryptography Mathematics Kookmin UniversitySeoul02707Republic of Korea

In the IoT(Internet of Things)domain,the increased use of encryption protocols such as SSL/TLS,VPN(Virtual Private Network),and Tor has led to a rise in attacks leveraging encrypted *** research on anomaly detection using AI(Artificial Intelligence)is actively progressing,the encrypted nature of the data poses challenges for labeling,resulting in data imbalance and biased feature extraction toward specific *** study proposes a reconstruction error-based anomaly detection method using an autoencoder(AE)that utilizes packet metadata excluding specific node *** proposed method omits biased packet metadata such as IP and Port and trains the detection model using only normal data,leveraging a small amount of packet *** makes it well-suited for direct application in IoT environments due to its low resource *** experiments comparing feature extraction methods for AE-based anomaly detection,we found that using flowbased features significantly improves accuracy,precision,F1 score,and AUC(Area Under the Receiver Operating Characteristic Curve)score compared to packet-based ***,for flow-based features,the proposed method showed a 30.17%increase in F1 score and improved false positive rates compared to Isolation Forest and ***,the proposedmethod demonstrated a 32.43%higherAUCwhen using packet features and a 111.39%higher AUC when using flow features,compared to previously proposed oversampling *** study highlights the impact of feature extraction methods on attack detection in imbalanced,encrypted traffic environments and emphasizes that the one-class method using AE is more effective for attack detection and reducing false positives compared to traditional oversampling methods.

关键词： One-class anomaly detection feature extraction auto-encoder encrypted traffic CICIoT2023

Improving Transferable Targeted Adversarial Attack for Object Detection Using RCEN Framework and Logit Loss Optimization

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2024年第9期80卷 4387-4412页

作者： Zhiyi Ding Lei Sun Xiuqing Mao Leyu Dai Ruiyang Ding School of cryptography Engineering Information Engineering UniversityZhengzhou450000China

Object detection finds wide application in various sectors,including autonomous driving,industry,and *** studies have highlighted the vulnerability of object detection models built using deep neural networks when confronted with carefully crafted adversarial *** not only reveals their shortcomings in defending against malicious attacks but also raises widespread concerns about the security of existing *** existing adversarial attack strategies focus primarily on image classification problems,failing to fully exploit the unique characteristics of object detectionmodels,thus resulting in widespread deficiencies in their ***,previous research has predominantly concentrated on the transferability issues of non-targeted attacks,whereas enhancing the transferability of targeted adversarial examples presents even greater *** attack techniques typically employ cross-entropy as a loss measure,iteratively adjusting adversarial examples to match target ***,their inherent limitations restrict their broad applicability and transferability across different *** address the aforementioned challenges,this study proposes a novel targeted adversarial attack method aimed at enhancing the transferability of adversarial samples across object detection *** the framework of iterative attacks,we devise a new objective function designed to mitigate consistency issues arising from cumulative noise and to enhance the separation between target and non-target categories(logit margin).Secondly,a data augmentation framework incorporating random erasing and color transformations is introduced into targeted adversarial *** enhances the diversity of gradients,preventing overfitting to white-box ***,perturbations are applied only within the specified object’s bounding box to reduce the perturbation range,enhancing attack *** were conducted on the Microsoft

关键词： Object detection model security targeted attack gradient diversity

SAT-Based Automatic Searching for Differential and Linear Trails: Applying to CRAX

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Chinese Journal of Electronics 2024年第1期33卷 72-79页

作者： Yiyi HAN Caibing WANG Zhongfeng NIU Lei HU State Key Laboratory of information security Institute of Information Engineering Chinese Academy of Sciences School of Cyber security University of Chinese Academy of Sciences

Boolean satisfiability problem(SAT) is now widely applied in differential cryptanalysis and linear cryptanalysis for various cipher *** generated many excellent results for some ciphers,for example,*** this research,we study the differential and linear propagations through the operations of addition,rotation and XOR(ARX),and construct the SAT *** apply the models to CRAX to search differential trails and linear trails *** this sense,our contnbution can be broadly divided into two *** give the bounds for differential and linear cryptanalysis of Alzette both up to 12 steps,by which we present a 3-round differential attack and a 3-round linear attack for *** construct a 4-round key-recovery attack for CRAX with time complexity289times of 4-round encryption and data complexity 225.

关键词： Ciphers Encryption Complexity theory Time complexity

A HEVC Video Steganalysis Method Using the Optimality of Motion Vector Prediction

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2024年第5期79卷 2085-2103页

作者： Jun Li Minqing Zhang Ke Niu Yingnan Zhang Xiaoyuan Yang College of cryptography Engineering Engineering University of the Chinese People’s Armed Police ForceXi’an710086China Key Laboratory of Network and information security of the Chinese People’s Armed Police Force Xi’an710086China

Among steganalysis techniques,detection against MV(motion vector)domain-based video steganography in the HEVC(High Efficiency Video Coding)standard remains a challenging *** the purpose of improving the detection performance,this paper proposes a steganalysis method that can perfectly detectMV-based steganography in ***,we define the local optimality of MVP(Motion Vector Prediction)based on the technology of AMVP(Advanced Motion Vector Prediction).Secondly,we analyze that in HEVC video,message embedding either usingMVP index orMVD(Motion Vector Difference)may destroy the above optimality of *** then,we define the optimal rate of MVP as a steganalysis ***,we conduct steganalysis detection experiments on two general datasets for three popular steganographymethods and compare the performance with four state-ofthe-art steganalysis *** experimental results demonstrate the effectiveness of the proposed feature ***,our method stands out for its practical applicability,requiring no model training and exhibiting low computational complexity,making it a viable solution for real-world scenarios.

关键词： Video steganography video steganalysis motion vector prediction motion vector difference advanced motion vector prediction local optimality

An Efficient and Secure Privacy-Preserving Federated Learning Framework Based on Multiplicative Double Privacy Masking

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2024年第9期80卷 4729-4748页

作者： Cong Shen Wei Zhang Tanping Zhou Yiming Zhang Lingling Zhang College of cryptography Engineering Engineering University of PAPXi’an710086China Key Laboratory of People’s Armed Police for Cryptology and information security Xi’an710086China College of information Engineering Engineering University of PAPXi’an710086China

With the increasing awareness of privacy protection and the improvement of relevant laws,federal learning has gradually become a new choice for cross-agency and cross-device machine *** order to solve the problems of privacy leakage,high computational overhead and high traffic in some federated learning schemes,this paper proposes amultiplicative double privacymask algorithm which is convenient for homomorphic addition *** combination of homomorphic encryption and secret sharing ensures that the server cannot compromise user privacy from the private gradient uploaded by the *** the same time,the proposed TQRR(Top-Q-Random-R)gradient selection algorithm is used to filter the gradient of encryption and upload efficiently,which reduces the computing overhead of 51.78%and the traffic of 64.87%on the premise of ensuring the accuracy of themodel,whichmakes the framework of privacy protection federated learning lighter to adapt to more miniaturized federated learning terminals.

关键词： Federated learning privacy protection homomorphic encryption double mask secret sharing gradient selection

General Method of Combining Grover and Simon for Attacking Block Ciphers

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

China Communications 2024年第6期21卷 237-245页

作者： Fu Xiangqun Bao Wansu Shi Jianhong Li Tan Henan Key Laboratory of Quantum information and cryptography PLA SSF IEUZhengzhou 450001China Synergetic Innovation center of Quantum information and Quantum Physics University of Science and Technology of ChinaHefei 230026China

The compatibility of different quantum algorithms should be considered when these algorithms are *** this paper,the method of combining Grover and Simon is studied for the first time,under some preconditions or ***,we give two preconditions of applying Grover’s algorithm,which ensure that the success probability of finding the marked element is close to ***,based on these two preconditions,it is found out that the success probability of the quantum algorithm for FXconstruction is far less than ***,we give the design method of the Oracle function,and then present the general method of combining Grover and Simon algorithm for attacking block ciphers,with success probability close to 1.

关键词： block ciphers post-quantum crypto quantum algorithms

维普期刊数据库

Automatically identifying imperfections and attacks in practical quantum key distribution systems via machine learning

在线全文

学校读者我要写书评

暂无评论

Science China(information Sciences) 2024年第10期67卷 359-372页

作者： Jiaxin XU Xiao MA Jingyang LIU Chunhui ZHANG Hongwei LI Xingyu ZHOU Qin WANG Institute of Quantum information and Technology Nanjing University of Posts and Telecommunications Telecommunication and Networks National Engineering Research CenterNanjing University of Posts and Telecommunications Henan Key Laboratory of Quantum information and cryptography Strategic Support Force Information Engineering University

The realistic security of quantum key distribution(QKD) systems is currently a hot research topic in the field of quantum communications. There are always defects in practical devices, and eavesdroppers can make use of the security risk points of various devices to obtain key information. To date, current types of security analysis tend to analyze each security risk point individually, thereby posing great challenges for the overall security evaluation of QKD systems. In this paper, for the first time, we employ machine learning algorithms to identify the defects of different devices and certain attacks in real time, with an accuracy of 98%. It provides a novel solution for the practical security evaluation of QKD systems, thereby addressing the bottleneck problem of multiple risk points being difficult to address simultaneously in QKD systems,thus paving the way for the future large-scale application of quantum communication networks.

关键词： quantum key distribution device imperfections eavasdropping attacks real-time detection machine learning algorithms

同方期刊数据库

A New Solution to Intrusion Detection Systems Based on Improved Federated-Learning Chain

在线全文

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2024年第6期79卷 4491-4512页

作者： Chunhui Li Hua Jiang School of Computer and Electronic information Guangxi UniversityNanning530000China Cyber security and information center Guangxi UniversityNanning530000China

In the context of enterprise systems,intrusion detection(ID)emerges as a critical element driving the digital transformation of *** systems spanning various sectors of enterprises geographically dispersed,the necessity for seamless information exchange has surged *** existing cross-domain solutions are challenged by such issues as insufficient security,high communication overhead,and a lack of effective update mechanisms,rendering them less feasible for prolonged application on resource-limited *** study proposes a new cross-domain collaboration scheme based on federated chains to streamline the server-side *** this framework,individual nodes solely engage in training local data and subsequently amalgamate the final model employing a federated learning algorithm to uphold enterprise systems with efficiency and *** curtail the resource utilization of blockchains and deter malicious nodes,a node administration module predicated on the workload paradigm is introduced,enabling the release of surplus resources in response to variations in a node’s contribution *** encountering an intrusion,the system triggers an alert and logs the characteristics of the breach,facilitating a comprehensive global update across all nodes for collective *** results across multiple scenarios have verified the security and effectiveness of the proposed solution,with no loss of its recognition accuracy.

关键词： Cross-domain collaboration blockchain federated learning contribution value node management release slack resources

Fault-tolerant identity-based encryption from SM9

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Science China(information Sciences) 2024年第2期67卷 104-117页

作者： Xiaohong LIU Xinyi HUANG Zhaohui CHENG Wei WU Fujian Provincial Key Laboratory of Network security and Cryptology College of Computer and Cyber SecurityFujian Normal University Artificial Intelligence Thrust Information HubThe Hong Kong University of Science and Technology (Guangzhou) Olym information security Technology Ltd. center for Applied Mathematics of Fujian Province School of Mathematics and StatisticsFujian Normal University

This paper initiates the formal study of attribute-based encryption within the framework of SM9,the Chinese National cryptography Standard for Identity-Based cryptography, by presenting two new faulttolerant identity-based encryption(FIBE) schemes. Our first scheme uses the same private-key/ciphertext structure as the original SM9 algorithm and operates in a small attribute universe. As a result, it can be effectively and smoothly integrated into the information systems using SM9. In the random oracle model,we prove that our scheme is ciphertext-indistinguishable against fuzzy selective-identity and chosen-plaintext attacks under the(k + 3)-DBDHI assumption. Our second design is a large universe FIBE scheme based on SM9 that is ciphertext-indistinguishable against chosen-plaintext attacks in the random oracle model under the(f, g)-GDDHE assumption. Finally, we compare the communication and computing costs of our schemes to those of other classical ones. The comparison shows that our schemes have comparable performance as others. We believe that our findings will accelerate the applications of SM9 in modern information systems such as cloud computing and blockchain.

关键词： attribute-based encryption identity-based encryption fault-tolerant SM9