Biblio

As cyber-physical systems are becoming more wide spread, it is imperative to secure these systems. In the real world these systems produce large amounts of data. However, it is generally impractical to test security techniques on operational cyber-physical systems. Thus, there exists a need to have realistic systems and data for testing security of cyber-physical systems [1]. This is often done in testbeds and cyber ranges. Most cyber ranges and testbeds focus on traditional network systems and few incorporate cyber-physical components. When they do, the cyber-physical components are often simulated. In the systems that incorporate cyber-physical components, generally only the network data is analyzed for attack detection and diagnosis. While there is some study in using physical signals to detect and diagnosis attacks, this data is not incorporated into current testbeds and cyber ranges. This study surveys currents testbeds and cyber ranges and demonstrates a prototype testbed that includes cyber-physical components and sensor data in addition to traditional cyber data monitoring.

Since its inception, the Internet has experienced tremendous speed and functionality improvements. Among these developments are innovative approaches such as the design and deployment of Internet Protocol version six (IPv6) and the continuous modification of TCP. New transport protocols like Stream Communication Transport Protocol (SCTP) and Multipath TCP (MPTCP), which can use multiple data paths, have been developed to overcome the IP-coupled challenge in TCP. However, given the difficulties of packet modifiers over the Internet that prevent the deployment of newly proposed protocols, e.g., SCTP, a UDP innovative approach with QUIC (Quick UDP Internet Connection) has been put forward as an alternative. QUIC reduces the connection establishment complexity in TCP and its variants, high security, stream multiplexing, and pluggable congestion control. Motivated by the gains and acceptability of MPTCP, Multipath QUIC has been developed to enable multipath transmission in QUIC. While several researchers have reviewed the progress of improvement and application of MPTCP, the review on MPQUIC improvement is limited. To breach the gap, this paper provides a brief survey on the practical application and progress of MPQUIC in data communication. We first review the fundamentals of multipath transport protocols. We then provide details on the design of QUIC and MPQUIC. Based on the articles reviewed, we looked at the various applications of MPQUIC, identifying the application domain, tools used, and evaluation parameters. Finally, we highlighted the open research issues and directions for further investigations.

Covert channels are data transmission methods that bypass the detection of security mechanisms and pose a serious threat to critical infrastructure. Meanwhile, it is also an effective way to ensure the secure transmission of private data. Therefore, research on covert channels helps us to quickly detect attacks and protect the security of data transmission. This paper proposes covert channels based on the timestamp of the Internet Control Message Protocol echo reply packet in the Linux system. By considering the concealment, we improve our proposed covert channels, ensuring that changing trends in the timestamp of modified consecutive packets are consistent with consecutive regular packets. Besides, we design an Iptables rule based on the current system time to analyze the performance of the proposed covert channels. Finally, it is shown through experiments that the channels complete the private data transmission in the industrial control network. Furthermore, the results demonstrate that the improved covert channels offer better performance in concealment, time cost, and the firewall test.

As the IPv6 protocol has been rapidly developed and applied, the security of IPv6 networks has become the focus of academic and industrial attention. Despite the fact that the IPv6 protocol is designed with security in mind, due to insufficient defense measures of current firewalls and intrusion detection systems for IPv6 networks, the construction of covert channels using fields not defined or reserved in IPv6 protocols may compromise the information systems. By discussing the possibility of constructing storage covert channels within IPv6 protocol fields, 10 types of IPv6 covert channels are constructed with undefined and reserved fields, including the flow label field, the traffic class field of IPv6 header, the reserved fields of IPv6 extension headers and the code field of ICMPv6 header. An IPv6 covert channel detection method based on field matching (CC-Guard) is proposed, and a typical IPv6 network environment is built for testing. In comparison with existing detection tools, the experimental results show that the CC-Guard not only can detect more covert channels consisting of IPv6 extension headers and ICMPv6 headers, but also achieves real-time detection with a lower detection overhead.

In this paper, a novel method is proposed to assess the power system resilience considering the impacts of hurricanes. Firstly, the transmission line outage model correlated to wind speed is developed. Then, Probability Load Flow (PLF) considering the random outage of lines and the variation of loads is designed, and Latin Hypercube Sampling (LHS) is used to improve the efficiency of Monte Carlo Simulation (MCS) in solving PLF. Moreover, risk indices, including line overloading, node voltage exceeding limit, load shedding and system collapse, are established to assess the resilience of power systems during hurricanes. The method is tested with a modified IEEE 14-bus system, and simulation results indicate the effectiveness of the proposed approach.

This study aims to explore the security issues and computational intelligence of drone information system based on deep learning. Targeting at the security issues of the drone system when it is attacked, this study adopts the improved long short-term memory (LSTM) network to analyze the cyber physical system (CPS) data for prediction from the perspective of predicting the control signal data of the system before the attack occurs. At the same time, the differential privacy frequent subgraph (DPFS) is introduced to keep data privacy confidential, and the digital twins technology is used to map the operating environment of the drone in the physical space, and an attack prediction model for drone digital twins CPS is constructed based on differential privacy-improved LSTM. Finally, the tennessee eastman (TE) process is undertaken as a simulation platform to simulate the constructed model so as to verify its performance. In addition, the proposed model is compared with the Bidirectional LSTM (BiLSTM) and Attention-BiLSTM models proposed by other scholars. It was found that the root mean square error (RMSE) of the proposed model is the smallest (0.20) when the number of hidden layer nodes is 26. Comparison with the actual flow value shows that the proposed algorithm is more accurate with better fitting. Therefore, the constructed drone attack prediction model can achieve higher prediction accuracy and obvious better robustness under the premise of ensuring errors, which can provide experimental basis for the later security and intelligent development of drone system.

Cyber-Physical Systems (CPS) are complex systems of computational, physical, and human components integrated to achieve some function over one or more networks. The use of distributed simulation, or co-simulation, is one method often used to analyze the behavior and properties of these systems. High-Level Architecture (HLA) is an IEEE co-simulation standard that supports the development and orchestration of distributed simulations. However, a simple HLA federation constructed with the component simulations (i.e., federates) does not satisfy several requirements that arise in real-world use cases such as the shared use of limited physical and computational resources, the need to selectively hide information from participating federates, the creation of reusable federates and federations for supporting configurable shared services, achieving performant distributed simulations, organizing federations across different model types or application concerns, and coordinating federations across organizations with different information technology policies. This paper describes these core requirements that necessitate the use of multiple HLA federations and presents various mechanisms for constructing such integrated HLA federations. An example use case is implemented using a model-based rapid simulation integration framework called the Universal CPS Environment for Federation (UCEF) to illustrate these requirements and demonstrate techniques for integrating multiple HLA federations.

The traditional ciphertext-policy attribute-based encryption (CP-ABE) has the problems of poor security of key distribution by a single attribute authorization center and too much calculation on the client in the process of encryption and decryption. A CP-ABE scheme that can outsource encryption and decryption and support multi-authorization centers is introduced to solve the above two problems. In the key generation stage, the user's private key is generated by the attribute authorization center and the key generation center jointly executing the two-party secure computing protocol; In the encryption and decryption stage, the cloud encryption server and cloud storage server are used to handle most of the computing work. Security proof and performance analysis show that the scheme not only can effectively make up for the defect of all key leakage when the attribute authorization center is broken, but also can enhance the security of the system; Moreover, after using the cloud server to process data, users only need to perform a simple calculation on the client to complete encryption or decryption, thus reducing the user's computing workload.

The security and reliability of power grid dispatching system is the basis of the stable development of the whole social economy. With the development of information, computer science and technology, communication technology, and network technology, using more advanced intelligent technology to improve the performance of security and reliability of power grid dispatching system has important research value and practical significance. In order to provide valuable references for relevant researchers and for the construction of future power system related applications. This paper summarizes the latest technical status of attribute encryption and hierarchical identity encryption methods, and introduces the access control method based on attribute and hierarchical identity encryption, the construction method of attribute encryption scheme, revocable CP-ABE scheme and its application in power grid data security access control. Combined with multi authorization center encryption, third-party trusted entity and optimized encryption algorithm, the parallel access control algorithm of hierarchical identity and attribute encryption and its application in power grid data security access control are introduced.

At present, the ciphertext-policy attribute based encryption (CP-ABE) has been widely used in different fields of data sharing such as cross-border paperless trade, digital government and etc. However, there still exist some challenges including single point of failure, key abuse and key unaccountable issues in CP-ABE. To address these problems. We propose an accountable CP-ABE mechanism based on block chain system. First, we establish two authorization agencies MskCA and AttrVN(Attribute verify Network),where the MskCA can realize master key escrow, and the AttrVN manages and validates users' attributes. In this way, our system can avoid the single point of failure and improve the privacy of user attributes and security of keys. Moreover, in order to realize auditability of CP-ABE key parameter transfer, we introduce the did and record parameter transfer process on the block chain. Finally, we theoretically prove the security of our CP-ABE. Through comprehensive comparison, the superiority of CP-ABE is verified. At the same time, our proposed schemes have some properties such as fast decryption and so on.

SWIM (System Wide Information Management) has become the development direction of A TM (Air Traffic Management) system by providing interoperable services to promote the exchange and sharing of data among various stakeholders. The premise of data sharing is security, and the access control has become the key guarantee for the secure sharing and exchange. The CP-ABE scheme (Ciphertext Policy Attribute-Based Encryption) can realize one-to-many access control, which is suitable for the characteristics of SWIM environment. However, the combination of the existing CP-ABE access control and SWIM has following constraints. 1. The traditional single authority CP-ABE scheme requires unconditional trust in the authority center. Once the authority center is corrupted, the excessive authority of the center may lead to the complete destruction of system security. So, SWIM with a large user group and data volume requires multiple authorities CP-ABE when performing access control. 2. There is no unified management of users' data access records. Lack of supervision on user behavior make it impossible to effectively deter malicious users. 3. There are a certain proportion of lightweight data users in SWIM, such as aircraft, users with handheld devices, etc. And their computing capacity becomes the bottleneck of data sharing. Aiming at these issues above, this paper based on cloud-chain fusion basically proposes a multi-authority CP-ABE scheme, called the MOV ATM scheme, which has three advantages. 1. Based on a multi-cloud and multi-authority CP-ABE, this solution conforms to the distributed nature of SWIM; 2. This scheme provides outsourced computing and verification functions for lightweight users; 3. Based on blockchain technology, a blockchain that is maintained by all stakeholders of SWIM is designed. It takes user's access records as transactions to ensure that access records are well documented and cannot be tampered with. Compared with other schemes, this scheme adds the functions of multi-authority, outsourcing, verifiability and auditability, but do not increase the decryption cost of users.

Deadlock is one of the critical problems in the message passing interface. At present, most techniques for detecting the MPI deadlock issue rely on exhausting all execution paths of a program, which is extremely inefficient. In addition, with the increasing number of wildcards that receive events and processes, the number of execution paths raises exponentially, further worsening the situation. To alleviate the problem, we propose a deadlock detection approach called SAMPI based on match-sets to avoid exploring execution paths. In this approach, a match detection rule is employed to form the rough match-sets based on Lazy Lamport Clocks Protocol. Then we design three refining algorithms based on the non-overtaking rule and MPI communication mechanism to refine the match-sets. Finally, deadlocks are detected by analyzing the refined match-sets. We performed the experimental evaluation on 15 various programs, and the experimental results show that SAMPI is really efficient in detecting deadlocks in MPI programs, especially in handling programs with many interleavings.

Given the COVID-19 pandemic, this paper aims at providing a full-process information system to support the detection of pathogens for a large range of populations, satisfying the requirements of light weight, low cost, high concurrency, high reliability, quick response, and high security. The project includes functional modules such as sample collection, sample transfer, sample reception, laboratory testing, test result inquiry, pandemic analysis, and monitoring. The progress and efficiency of each collection point as well as the status of sample transfer, reception, and laboratory testing are all monitored in real time, in order to support the comprehensive surveillance of the pandemic situation and support the dynamic deployment of pandemic prevention resources in a timely and effective manner. Deployed on a cloud platform, this system can satisfy ultra-high concurrent data collection requirements with 20 million collections per day and a maximum of 5 million collections per hour, due to its advantages of high concurrency, elasticity, security, and manageability. This system has also been widely used in Jiangsu, Shaanxi provinces, for the prevention and control of COVID-19 pandemic. Over 100 million NAT data have been collected nationwide, providing strong informational support for scientific and reasonable formulation and execution of COVID-19 prevention plans.

In the process of crowdsourced testing service, the intellectual property of crowdsourced testing has been faced with problems such as code plagiarism, difficulties in confirming rights and unreliability of data. Blockchain is a decentralized, tamper-proof distributed ledger, which can help solve current problems. This paper proposes an intellectual property right confirmation system oriented to crowdsourced testing services, combined with blockchain, IPFS (Interplanetary file system), digital signature, code similarity detection to realize the confirmation of crowdsourced testing intellectual property. The performance test shows that the system can meet the requirements of normal crowdsourcing business as well as high concurrency situations.

With the rapid development of Internet Technology in recent years, the demand for security support for complex applications is becoming stronger and stronger. Intel Software Guard Extensions (Intel SGX) is created as an extension of Intel Systems to enhance software security. Intel SGX allows application developers to create so-called enclave. Sensitive application code and data are encapsulated in Trusted Execution Environment (TEE) by enclave. TEE is completely isolated from other applications, operating systems, and administrative programs. Enclave is the core structure of Intel SGX Technology. Enclave supports multi-threading. Thread Control Structure (TCS) stores special information for restoring enclave threads when entering or exiting enclave. Each execution thread in enclave is associated with a TCS. This paper analyzes and verifies the possible security risks of enclave under concurrent conditions. It is found that in the case of multithread concurrency, a single enclave cannot resist flooding attacks, and related threads also throw TCS exception codes.

Concurrency vulnerabilities caused by synchronization problems will occur in the execution of multi-threaded programs, and the emergence of concurrency vulnerabilities often cause great threats to the system. Once the concurrency vulnerabilities are exploited, the system will suffer various attacks, seriously affecting its availability, confidentiality and security. In this paper, we extract 839 concurrency vulnerabilities from Common Vulnerabilities and Exposures (CVE), and conduct a comprehensive analysis of the trend, classifications, causes, severity, and impact. Finally, we obtained some findings: 1) From 1999 to 2021, the number of concurrency vulnerabilities disclosures show an overall upward trend. 2) In the distribution of concurrency vulnerability, race condition accounts for the largest proportion. 3) The overall severity of concurrency vulnerabilities is medium risk. 4) The number of concurrency vulnerabilities that can be exploited for local access and network access is almost equal, and nearly half of the concurrency vulnerabilities (377/839) can be accessed remotely. 5) The access complexity of 571 concurrency vulnerabilities is medium, and the number of concurrency vulnerabilities with high or low access complexity is almost equal. The results obtained through the empirical study can provide more support and guidance for research in the field of concurrency vulnerabilities.

The humidity in the air parameters has an impact on the characteristics of corona discharge, and the magnetic field also affects the electron movement of corona discharge. We build a constant humidity chamber and use a wire-mesh electrode device to study the effects of humidity and magnetic field on the discharge. The enhancement of the discharge by humidity is caused by the combination of water vapor molecules and ions generated by the discharge into hydrated ions. By building a “water flow channel” between the high voltage wire electrode and the ground mesh electrode, the ions can pass more smoothly, thereby enhanced discharge. The ions are subjected to the Lorentz force in the electromagnetic field environment, the motion state of the ions changes, and the larmor motion in the electromagnetic field increases the movement path, the collision between the gas molecules increases, and more charged particles are generated, which increases the discharge current. During the period, the electrons and ions generated by the ionization of the wire electrode leave the ionization zone faster, which reduces the inhibitory effect of the ion aggregation on the discharge and promotes the discharge.

In order to investigate the effect of island divertor on the peak heat load reduction in a tokamak, a new island divertor was developed and installed in J-TEXT tokamak. The engineering design takes into account the complexity of the device based on the physical design, and also needs to ensure the insulation performance of the coil. Before installing the coil, electromagnetic forces on conductors and thermal conditions were simulated, the electromagnetic force on the magnetic island divertor coil will not cause damage to the coil, and there will be no thermal failure behavior.

Social networks are considered to be heterogeneous graph neural networks (HGNNs) with deep learning technological advances. HGNNs, compared to homogeneous data, absorb various aspects of information about individuals in the training stage. That means more information has been covered in the learning result, especially sensitive information. However, the privacy-preserving methods on homogeneous graphs only preserve the same type of node attributes or relationships, which cannot effectively work on heterogeneous graphs due to the complexity. To address this issue, we propose a novel heterogeneous graph neural network privacy-preserving method based on a differential privacy mechanism named HeteDP, which provides a double guarantee on graph features and topology. In particular, we first define a new attack scheme to reveal privacy leakage in the heterogeneous graphs. Specifically, we design a two-stage pipeline framework, which includes the privacy-preserving feature encoder and the heterogeneous link reconstructor with gradients perturbation based on differential privacy to tolerate data diversity and against the attack. To better control the noise and promote model performance, we utilize a bi-level optimization pattern to allocate a suitable privacy budget for the above two modules. Our experiments on four public benchmarks show that the HeteDP method is equipped to resist heterogeneous graph privacy leakage with admirable model generalization.

With the increasing complexity of the driving environment, more and more attention has been paid to the research on improving the intelligentization of traffic control. Among them, the digital twin-based internet of vehicle can establish a mirror system on the cloud to improve the efficiency of communication between vehicles, provide warning and safety instructions for drivers, avoid driving potential dangers. To ensure the security and effectiveness of data sharing in traffic control, this paper proposes a secure and privacy-preserving scheme for digital twin-based traffic control. Specifically, in the data uploading phase, we employ a group signature with a time-bound keys technique to realize data source authentication with efficient members revocation and privacy protection, which can ensure that data can be securely stored on cloud service providers after it synchronizes to its twin. In the data sharing stage, we employ the secure and efficient attribute-based access control technique to provide flexible and efficient data sharing, in which the parameters of a specific sub-policy can be stored during the first decryption and reused in subsequent data access containing the same sub-policy, thus reducing the computing complexity. Finally, we analyze the security and efficiency of the scheme theoretically.

Public transportation is an important system of urban passenger transport. The purpose of this article is to explore the impact of network resilience when each station of urban rail transit network was attacked by large passenger flow. Based on the capacity load model, we propose a load redistribution mechanism to simulate the passenger flow propagation after being attacked by large passenger flow. Then, taking Xi'an's rail network as an example, we study the resilience variety of the network after a node is attacked by large passenger flow. Through some attack experiments, the feasibility of the model for studying the resilience of the rail transit system is finally verified.

The resilience assessment of electric and gas networks gains importance due to increasing interdependencies caused by the coupling of gas-fired units. However, the gradually increasing scale of the integrated electricity and gas system (IEGS) poses a significant challenge to current assessment methods. The numerical analysis method is accurate but time-consuming, which may incur a significant computational cost in large-scale IEGS. Therefore, this paper proposes a resilience assessment method based on hetero-functional graph theory for IEGS to balance the accuracy with the computational complexity. In contrast to traditional graph theory, HFGT can effectively depict the coupled systems with inherent heterogeneity and can represent the structure of heterogeneous functional systems in a clear and unambiguous way. In addition, due to the advantages of modelling the system functionality, the effect of line-pack in the gas network on the system resilience is depicted more precisely in this paper. Simulation results on an IEGS with the IEEE 9-bus system and a 7-node gas system verify the effectiveness of the proposed method.

National cultural security has existed since ancient times, but it has become a focal proposition in the context of the times and real needs. From the perspective of national security, national cultural security is an important part of national security, and it has become a strategic task that cannot be ignored in defending national security. Cultural diversity and imbalance are the fundamental prerequisites for the existence of national cultural security. Finally, the artificial intelligence algorithm is used as the theoretical basis for this article, the connotation and characteristics of China's national cultural security theory; Xi Jinping's "network view"; network ideological security view. The fourth part is the analysis of the current cultural security problems, hazards and their root causes in our country.

Access control is a widely used technology to protect information security. The implementation of access control depends on the response generated by access control policies to users’ access requests. Therefore, ensuring the correctness of access control policies is an important step to ensure the smooth implementation of access control mechanisms. To solve this problem, this paper proposes a constraint based access control policy security analysis framework (CACPSAF) to perform security analysis on access control policies. The framework transforms the problem of security analysis of access control policy into the satisfiability of security principle constraints. The analysis and calculation of access control policy can be divided into formal transformation of access control policy, SMT coding of policy model, generation of security principle constraints, policy detection and evaluation. The security analysis of policies is divided into mandatory security principle constraints, optional security principle constraints and user-defined security principle constraints. The multi-dimensional security analysis of access control policies is realized and the semantic expression of policy analysis is stronger. Finally, the effectiveness of this framework is analyzed by performance evaluation, which proves that this framework can provide strong support for fine-grained security analysis of policies, and help to correctly model and conFigure policies during policy modeling, implementation and verification.

With the high-speed development of UHV power grid, the characteristics of power grid changed significantly, which puts forward new requirements for the safe operation of power grid and depend on Security and Stability Control System (SSCS) greatly. Based on the practical cases, this paper analyzes the principle of the abnormal criteria of the SSCS and its influence on the strategy of the SSCS, points out the necessity of the research on the locking strategy of the SSCS under the abnormal state. Taking the large-scale SSCS for an example, this paper analysis different control strategies of the stations in the different layered, and puts forward effective solutions to adapt different system functions. It greatly improved the effectiveness and reliability of the strategy of SSCS, and ensure the integrity of the system function. Comparing the different schemes, the principles of making the lock-strategy are proposed. It has reference significance for the design, development and implementation of large-scale SSCS.