Visible to the public Biblio

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2019-10-02
Wang, S., Zhu, S., Zhang, Y..  2018.  Blockchain-Based Mutual Authentication Security Protocol for Distributed RFID Systems. 2018 IEEE Symposium on Computers and Communications (ISCC). :00074–00077.

Since radio frequency identification (RFID) technology has been used in various scenarios such as supply chain, access control system and credit card, tremendous efforts have been made to improve the authentication between tags and readers to prevent potential attacks. Though effective in certain circumstances, these existing methods usually require a server to maintain a database of identity related information for every tag, which makes the system vulnerable to the SQL injection attack and not suitable for distributed environment. To address these problems, we now propose a novel blockchain-based mutual authentication security protocol. In this new scheme, there is no need for the trusted third parties to provide security and privacy for the system. Authentication is executed as an unmodifiable transaction based on blockchain rather than database, which applies to distributed RFID systems with high security demand and relatively low real-time requirement. Analysis shows that our protocol is logically correct and can prevent multiple attacks.

Zhang, Y., Eisele, S., Dubey, A., Laszka, A., Srivastava, A. K..  2019.  Cyber-Physical Simulation Platform for Security Assessment of Transactive Energy Systems. 2019 7th Workshop on Modeling and Simulation of Cyber-Physical Energy Systems (MSCPES). :1–6.
Transactive energy systems (TES) are emerging as a transformative solution for the problems that distribution system operators face due to an increase in the use of distributed energy resources and rapid growth in scalability of managing active distribution system (ADS). On the one hand, these changes pose a decentralized power system control problem, requiring strategic control to maintain reliability and resiliency for the community and for the utility. On the other hand, they require robust financial markets while allowing participation from diverse prosumers. To support the computing and flexibility requirements of TES while preserving privacy and security, distributed software platforms are required. In this paper, we enable the study and analysis of security concerns by developing Transactive Energy Security Simulation Testbed (TESST), a TES testbed for simulating various cyber attacks. In this work, the testbed is used for TES simulation with centralized clearing market, highlighting weaknesses in a centralized system. Additionally, we present a blockchain enabled decentralized market solution supported by distributed computing for TES, which on one hand can alleviate some of the problems that we identify, but on the other hand, may introduce newer issues. Future study of these differing paradigms is necessary and will continue as we develop our security simulation testbed.
2019-08-26
Zhang, Y., Ya\u gan, O..  2018.  Modeling and Analysis of Cascading Failures in Interdependent Cyber-Physical Systems. 2018 IEEE Conference on Decision and Control (CDC). :4731-4738.

Integrated cyber-physical systems (CPSs), such as the smart grid, are becoming the underpinning technology for major industries. A major concern regarding such systems are the seemingly unexpected large scale failures, which are often attributed to a small initial shock getting escalated due to intricate dependencies within and across the individual counterparts of the system. In this paper, we develop a novel interdependent system model to capture this phenomenon, also known as cascading failures. Our framework consists of two networks that have inherently different characteristics governing their intra-dependency: i) a cyber-network where a node is deemed to be functional as long as it belongs to the largest connected (i.e., giant) component; and ii) a physical network where nodes are given an initial flow and a capacity, and failure of a node results with redistribution of its flow to the remaining nodes, upon which further failures might take place due to overloading. Furthermore, it is assumed that these two networks are inter-dependent. For simplicity, we consider a one-to-one interdependency model where every node in the cyber-network is dependent upon and supports a single node in the physical network, and vice versa. We provide a thorough analysis of the dynamics of cascading failures in this interdependent system initiated with a random attack. The system robustness is quantified as the surviving fraction of nodes at the end of cascading failures, and is derived in terms of all network parameters involved. Analytic results are supported through an extensive numerical study. Among other things, these results demonstrate the ability of our model to capture the unexpected nature of large-scale failures, and provide insights on improving system robustness.

2019-03-28
He, F., Zhang, Y., Liu, H., Zhou, W..  2018.  SCPN-Based Game Model for Security Situational Awareness in the Intenet of Things. 2018 IEEE Conference on Communications and Network Security (CNS). :1-5.
Internet of Things (IoT) is characterized by various of heterogeneous devices that facing numerous threats, which makes modeling security situation of IoT still a certain challenge. This paper defines a Stochastic Colored Petri Net (SCPN) for IoT-based smart environment and then proposes a Game model for security situational awareness. All possible attack paths are computed by the SCPN, and antagonistic behavior of both attackers and defenders are taken into consideration dynamically according to Game Theory (GT). Experiments on two typical attack scenarios in smart home environment demonstrate the effectiveness of the proposed model. The proposed model can form a macroscopic trend curve of the security situation. Analysis of the results shows the capabilities of the proposed model in finding vulnerable devices and potential attack paths, and even facilitating the choice of defense strategy. To the best of our knowledge, this is the first attempt to use Game Theory in the IoT-based SCPN to establish a security situational awareness model for a complex smart environment.
2019-03-06
Lin, Y., Liu, H., Xie, G., Zhang, Y..  2018.  Time Series Forecasting by Evolving Deep Belief Network with Negative Correlation Search. 2018 Chinese Automation Congress (CAC). :3839-3843.

The recently developed deep belief network (DBN) has been shown to be an effective methodology for solving time series forecasting problems. However, the performance of DBN is seriously depended on the reasonable setting of hyperparameters. At present, random search, grid search and Bayesian optimization are the most common methods of hyperparameters optimization. As an alternative, a state-of-the-art derivative-free optimizer-negative correlation search (NCS) is adopted in this paper to decide the sizes of DBN and learning rates during the training processes. A comparative analysis is performed between the proposed method and other popular techniques in the time series forecasting experiment based on two types of time series datasets. Experiment results statistically affirm the efficiency of the proposed model to obtain better prediction results compared with conventional neural network models.

2019-03-04
Berscheid, A., Makarov, Y., Hou, Z., Diao, R., Zhang, Y., Samaan, N., Yuan, Y., Zhou, H..  2018.  An Open-Source Tool for Automated Power Grid Stress Level Prediction at Balancing Authorities. 2018 IEEE/PES Transmission and Distribution Conference and Exposition (T D). :1–5.
The behavior of modern power systems is becoming more stochastic and dynamic, due to the increased penetration of variable generation, demand response, new power market structure, extreme weather conditions, contingencies, and unexpected events. It is critically important to predict potential system operational issues so that grid planners and operators can take preventive actions to mitigate the impact, e.g., lack of operational reserves. In this paper, an innovative software tool is presented to assist power grid operators in a balancing authority in predicting the grid stress level over the next operating day. It periodically collects necessary information from public domain such as weather forecasts, electricity demand, and automatically estimates the stress levels on a daily basis. Advanced Neural Network and regression tree algorithms are developed as the prediction engines to achieve this goal. The tool has been tested on a few key balancing authorities and successfully predicted the growing system peak load and increased stress levels under extreme heat waves.
2019-02-14
Zhang, F., Dong, X., Zhao, X., Wang, Y., Qureshi, S., Zhang, Y., Lou, X., Tang, Y..  2018.  Theoretical Round Modification Fault Analysis on AEGIS-128 with Algebraic Techniques. 2018 IEEE 15th International Conference on Mobile Ad Hoc and Sensor Systems (MASS). :335-343.
This paper proposed an advanced round modification fault analysis (RMFA) at the theoretical level on AEGIS-128, which is one of seven finalists in CAESAR competition. First, we clarify our assumptions and simplifications on the attack model, focusing on the encryption security. Then, we emphasize the difficulty of applying vanilla RMFA to AEGIS-128 in the practical case. Finally we demonstrate our advanced fault analysis on AEGIS-128 using machine-solver based algebraic techniques. Our enhancement can be used to conquer the practical scenario which is difficult for vanilla RMFA. Simulation results show that when the fault is injected to the initialization phase and the number of rounds is reduced to one, two samples of injections can extract the whole 128 key bits within less than two hours. This work can also be extended to other versions such as AEGIS-256.
2019-02-08
Yang, B., Xu, G., Zeng, X., Liu, J., Zhang, Y..  2018.  A Lightweight Anonymous Mobile User Authentication Scheme for Smart Grid. 2018 IEEE SmartWorld, Ubiquitous Intelligence Computing, Advanced Trusted Computing, Scalable Computing Communications, Cloud Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI). :821-827.

Smart Grid (SG) technology has been developing for years, which facilitates users with portable access to power through being applied in numerous application scenarios, one of which is the electric vehicle charging. In order to ensure the security of the charging process, users need authenticating with the smart meter for the subsequent communication. Although there are many researches in this field, few of which have endeavored to protect the anonymity and the untraceability of users during the authentication. Further, some studies consider the problem of user anonymity, but they are non-light-weight protocols, even some can not assure any fairness in key agreement. In this paper, we first points out that existing authentication schemes for Smart Grid are neither lack of critical security nor short of important property such as untraceability, then we propose a new two-factor lightweight user authentication scheme based on password and biometric. The authentication process of the proposed scheme includes four message exchanges among the user mobile, smart meter and the cloud server, and then a security one-time session key is generated for the followed communication process. Moreover, the scheme has some new features, such as the protection of the user's anonymity and untraceability. Security analysis shows that our proposed scheme can resist various well-known attacks and the performance analysis shows that compared to other three schemes, our scheme is more lightweight, secure and efficient.

Yousefi, M., Mtetwa, N., Zhang, Y., Tianfield, H..  2018.  A Reinforcement Learning Approach for Attack Graph Analysis. 2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE). :212-217.

Attack graph approach is a common tool for the analysis of network security. However, analysis of attack graphs could be complicated and difficult depending on the attack graph size. This paper presents an approximate analysis approach for attack graphs based on Q-learning. First, we employ multi-host multi-stage vulnerability analysis (MulVAL) to generate an attack graph for a given network topology. Then we refine the attack graph and generate a simplified graph called a transition graph. Next, we use a Q-learning model to find possible attack routes that an attacker could use to compromise the security of the network. Finally, we evaluate the approach by applying it to a typical IT network scenario with specific services, network configurations, and vulnerabilities.

2019-01-31
Lyu, C., Pande, A., Zhang, Y., Gu, D., Mohapatra, P..  2018.  FastTrust: Fast and Anonymous Spatial-Temporal Trust for Connected Cars on Expressways. 2018 15th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON). :1–9.

Connected cars have received massive attention in Intelligent Transportation System. Many potential services, especially safety-related ones, rely on spatial-temporal messages periodically broadcast by cars. Without a secure authentication algorithm, malicious cars may send out invalid spatial-temporal messages and then deny creating them. Meanwhile, a lot of private information may be disclosed from these spatial-temporal messages. Since cars move on expressways at high speed, any authentication must be performed in real-time to prevent crashes. In this paper, we propose a Fast and Anonymous Spatial-Temporal Trust (FastTrust) mechanism to ensure these properties. In contrast to most authentication protocols which rely on fixed infrastructures, FastTrust is distributed and mostly designed on symmetric-key cryptography and an entropy-based commitment, and is able to fast authenticate spatial-temporal messages. FastTrust also ensures the anonymity and unlinkability of spatial-temporal messages by developing a pseudonym-varying scheduling scheme on cars. We provide both analytical and simulation evaluations to show that FastTrust achieves the security and privacy properties. FastTrust is low-cost in terms of communication and computational resources, authenticating 20 times faster than existing Elliptic Curve Digital Signature Algorithm.

2018-11-14
Teoh, T. T., Zhang, Y., Nguwi, Y. Y., Elovici, Y., Ng, W. L..  2017.  Analyst Intuition Inspired High Velocity Big Data Analysis Using PCA Ranked Fuzzy K-Means Clustering with Multi-Layer Perceptron (MLP) to Obviate Cyber Security Risk. 2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD). :1790–1793.
The growing prevalence of cyber threats in the world are affecting every network user. Numerous security monitoring systems are being employed to protect computer networks and resources from falling victim to cyber-attacks. There is a pressing need to have an efficient security monitoring system to monitor the large network datasets generated in this process. A large network datasets representing Malware attacks have been used in this work to establish an expert system. The characteristics of attacker's IP addresses can be extracted from our integrated datasets to generate statistical data. The cyber security expert provides to the weight of each attribute and forms a scoring system by annotating the log history. We adopted a special semi supervise method to classify cyber security log into attack, unsure and no attack by first breaking the data into 3 cluster using Fuzzy K mean (FKM), then manually label a small data (Analyst Intuition) and finally train the neural network classifier multilayer perceptron (MLP) base on the manually labelled data. By doing so, our results is very encouraging as compare to finding anomaly in a cyber security log, which generally results in creating huge amount of false detection. The method of including Artificial Intelligence (AI) and Analyst Intuition (AI) is also known as AI2. The classification results are encouraging in segregating the types of attacks.
2018-08-23
Xia, D., Zhang, Y..  2017.  The fuzzy control of trust establishment. 2017 4th International Conference on Systems and Informatics (ICSAI). :655–659.

In the open network environment, the strange entities can establish the mutual trust through Automated Trust Negotiation (ATN) that is based on exchanging digital credentials. In traditional ATN, the attribute certificate required to either satisfied or not, and in the strategy, the importance of the certificate is same, it may cause some unnecessary negotiation failure. And in the actual situation, the properties is not just 0 or 1, it is likely to between 0 and 1, so the satisfaction degree is different, and the negotiation strategy need to be quantified. This paper analyzes the fuzzy negotiation process, in order to improve the trust establishment in high efficiency and accuracy further.

2018-06-11
Wu, D., Xu, Z., Chen, B., Zhang, Y..  2017.  Towards Access Control for Network Coding-Based Named Data Networking. GLOBECOM 2017 - 2017 IEEE Global Communications Conference. :1–6.

Named Data Networking (NDN) is a content-oriented future Internet architecture, which well suits the increasingly mobile and information-intensive applications that dominate today's Internet. NDN relies on in-network caching to facilitate content delivery. This makes it challenging to enforce access control since the content has been cached in the routers and the content producer has lost the control over it. Due to its salient advantages in content delivery, network coding has been introduced into NDN to improve content delivery effectiveness. In this paper, we design ACNC, the first Access Control solution specifically for Network Coding-based NDN. By combining a novel linear AONT (All Or Nothing Transform) and encryption, we can ensure that only the legitimate user who possesses the authorization key can successfully recover the encoding matrix for network coding, and hence can recover the content being transmitted. In addition, our design has two salient merits: 1) the linear AONT well suits the linear nature of network coding; 2) only one vector of the encoding matrix needs to be encrypted/decrypted, which only incurs small computational overhead. Security analysis and experimental evaluation in ndnSIM show that our design can successfully enforce access control on network coding-based NDN with an acceptable overhead.

2018-04-02
Yousefi, M., Mtetwa, N., Zhang, Y., Tianfield, H..  2017.  A Novel Approach for Analysis of Attack Graph. 2017 IEEE International Conference on Intelligence and Security Informatics (ISI). :7–12.

Attack graph technique is a common tool for the evaluation of network security. However, attack graphs are generally too large and complex to be understood and interpreted by security administrators. This paper proposes an analysis framework for security attack graphs for a given IT infrastructure system. First, in order to facilitate the discovery of interconnectivities among vulnerabilities in a network, multi-host multi-stage vulnerability analysis (MulVAL) is employed to generate an attack graph for a given network topology. Then a novel algorithm is applied to refine the attack graph and generate a simplified graph called a transition graph. Next, a Markov model is used to project the future security posture of the system. Finally, the framework is evaluated by applying it on a typical IT network scenario with specific services, network configurations, and vulnerabilities.

Wu, D., Zhang, Y., Liu, Y..  2017.  Dummy Location Selection Scheme for K-Anonymity in Location Based Services. 2017 IEEE Trustcom/BigDataSE/ICESS. :441–448.

Location-Based Service (LBS) becomes increasingly important for our daily life. However, the localization information in the air is vulnerable to various attacks, which result in serious privacy concerns. To overcome this problem, we formulate a multi-objective optimization problem with considering both the query probability and the practical dummy location region. A low complexity dummy location selection scheme is proposed. We first find several candidate dummy locations with similar query probabilities. Among these selected candidates, a cloaking area based algorithm is then offered to find K - 1 dummy locations to achieve K-anonymity. The intersected area between two dummy locations is also derived to assist to determine the total cloaking area. Security analysis verifies the effectiveness of our scheme against the passive and active adversaries. Compared with other methods, simulation results show that the proposed dummy location scheme can improve the privacy level and enlarge the cloaking area simultaneously.

2018-03-19
Ge, H., Yue, D., p Xie, X., Deng, S., Zhang, Y..  2017.  Analysis of Cyber Physical Systems Security via Networked Attacks. 2017 36th Chinese Control Conference (CCC). :4266–4272.

In this paper, cyber physical system is analyzed from security perspective. A double closed-loop security control structure and algorithm with defense functions is proposed. From this structure, the features of several cyber attacks are considered respectively. By this structure, the models of information disclosure, denial-of-service (DoS) and Man-in-the-Middle Attack (MITM) are proposed. According to each kind attack, different models are obtained and analyzed, then reduce to the unified models. Based on this, system security conditions are obtained, and a defense scenario with detail algorithm is design to illustrate the implementation of this program.

2018-02-06
Zhang, Y., Mao, W., Zeng, D..  2017.  Topic Evolution Modeling in Social Media Short Texts Based on Recurrent Semantic Dependent CRP. 2017 IEEE International Conference on Intelligence and Security Informatics (ISI). :119–124.

Social media has become an important platform for people to express opinions, share information and communicate with others. Detecting and tracking topics from social media can help people grasp essential information and facilitate many security-related applications. As social media texts are usually short, traditional topic evolution models built based on LDA or HDP often suffer from the data sparsity problem. Recently proposed topic evolution models are more suitable for short texts, but they need to manually specify topic number which is fixed during different time period. To address these issues, in this paper, we propose a nonparametric topic evolution model for social media short texts. We first propose the recurrent semantic dependent Chinese restaurant process (rsdCRP), which is a nonparametric process incorporating word embeddings to capture semantic similarity information. Then we combine rsdCRP with word co-occurrence modeling and build our short-text oriented topic evolution model sdTEM. We carry out experimental studies on Twitter dataset. The results demonstrate the effectiveness of our method to monitor social media topic evolution compared to the baseline methods.

2018-01-10
Zhang, Y., Wang, L., You, Y., Yi, L..  2017.  A Remote-Attestation-Based Extended Hash Algorithm for Privacy Protection. 2017 International Conference on Computer Network, Electronic and Automation (ICCNEA). :254–257.

Compared to other remote attestation methods, the binary-based approach is the most direct and complete one, but privacy protection has become an important problem. In this paper, we presented an Extended Hash Algorithm (EHA) for privacy protection based on remote attestation method. Based on the traditional Merkle Hash Tree, EHA altered the algorithm of node connection. The new algorithm could ensure the same result in any measure order. The security key is added when the node connection calculation is performed, which ensures the security of the value calculated by the Merkle node. By the final analysis, we can see that the remote attestation using EHA has better privacy protection and execution performance compared to other methods.

Zhang, Y., Duan, L., Sun, C. A., Cheng, B., Chen, J..  2017.  A Cross-Layer Security Solution for Publish/Subscribe-Based IoT Services Communication Infrastructure. 2017 IEEE International Conference on Web Services (ICWS). :580–587.

The publish/subscribe paradigm can be used to build IoT service communication infrastructure owing to its loose coupling and scalability. Its features of decoupling among event producers and event consumers make IoT services collaborations more real-time and flexible, and allow indirect, anonymous and multicast IoT service interactions. However, in this environment, the IoT service cannot directly control the access to the events. This paper proposes a cross-layer security solution to address the above issues. The design principle of our security solution is to embed security policies into events as well as allow the network to route events according to publishers' policies and requirements. This solution helps to improve the system's performance, while keeping features of IoT service interactions and minimizing the event visibility at the same time. Experimental results show that our approach is effective.

2017-12-12
Zhang, M., Chen, Q., Zhang, Y., Liu, X., Dong, S..  2017.  Requirement analysis and descriptive specification for exploratory evaluation of information system security protection capability. 2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC). :1874–1878.

Exploratory evaluation is an effective way to analyze and improve the security of information system. The information system structure model for security protection capability is set up in view of the exploratory evaluation requirements of security protection capability, and the requirements of agility, traceability and interpretation for exploratory evaluation are obtained by analyzing the relationship between information system, protective equipment and protection policy. Aimed at the exploratory evaluation description problem of security protection capability, the exploratory evaluation problem and exploratory evaluation process are described based on the Granular Computing theory, and a general mathematical description is established. Analysis shows that the standardized description established meets the exploratory evaluation requirements, and it can provide an analysis basis and description specification for exploratory evaluation of information system security protection capability.