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Hoque, Enamul.  2016.  Visual Text Analytics for Online Conversations: Design, Evaluation, and Applications. Companion Publication of the 21st International Conference on Intelligent User Interfaces. :122–125.

Analyzing and gaining insights from a large amount of textual conversations can be quite challenging for a user, especially when the discussions become very long. During my doctoral research, I have focused on integrating Information Visualization (InfoVis) with Natural Language Processing (NLP) techniques to better support the user's task of exploring and analyzing conversations. For this purpose, I have designed a visual text analytics system that supports the user exploration, starting from a possibly large set of conversations, then narrowing down to a subset of conversations, and eventually drilling-down to a set of comments of one conversation. While so far our approach is evaluated mainly based on lab studies, in my on-going and future work I plan to evaluate our approach via online longitudinal studies.

El-Assady, Mennatallah.  2018.  Visual Text Analytics: Techniques for Linguistic Information Visualization. Proceedings of the ACM Symposium on Document Engineering 2018. :2:1-2:2.
Visual Text Analytics has been an active area of interdisciplinary research (http://textvis.lnu.se/). This interactive tutorial is designed to give attendees an introduction to the area of information visualization, with a focus on linguistic visualization. After an introduction to the basic principles of information visualization and visual analytics, this tutorial will give an overview of the broad spectrum of linguistic and text visualization techniques, as well as their application areas [3]. This will be followed by a hands-on session that will allow participants to design their own visualizations using tools (e.g., Tableau), libraries (e.g., d3.js), or applying sketching techniques [4]. Some sample datasets will be provided by the instructor. Besides general techniques, special access will be provided to use the VisArgue framework [1] for the analysis of selected datasets.
W. Huang, J. Gu, X. Ma.  2015.  "Visual tracking based on compressive sensing and particle filter". 2015 IEEE 28th Canadian Conference on Electrical and Computer Engineering (CCECE). :1435-1440.

A robust appearance model is usually required in visual tracking, which can handle pose variation, illumination variation, occlusion and many other interferences occurring in video. So far, a number of tracking algorithms make use of image samples in previous frames to update appearance models. There are many limitations of that approach: 1) At the beginning of tracking, there exists no sufficient amount of data for online update because these adaptive models are data-dependent and 2) in many challenging situations, robustly updating the appearance models is difficult, which often results in drift problems. In this paper, we proposed a tracking algorithm based on compressive sensing theory and particle filter framework. Features are extracted by random projection with data-independent basis. Particle filter is employed to make a more accurate estimation of the target location and make much of the updated classifier. The robustness and the effectiveness of our tracker have been demonstrated in several experiments.

Kotenko, I., Novikova, E..  2014.  Visualization of Security Metrics for Cyber Situation Awareness. Availability, Reliability and Security (ARES), 2014 Ninth International Conference on. :506-513.

One of the important direction of research in situational awareness is implementation of visual analytics techniques which can be efficiently applied when working with big security data in critical operational domains. The paper considers a visual analytics technique for displaying a set of security metrics used to assess overall network security status and evaluate the efficiency of protection mechanisms. The technique can assist in solving such security tasks which are important for security information and event management (SIEM) systems. The approach suggested is suitable for displaying security metrics of large networks and support historical analysis of the data. To demonstrate and evaluate the usefulness of the proposed technique we implemented a use case corresponding to the Olympic Games scenario.
 

Riveiro, M., Lebram, M., Warston, H..  2014.  On visualizing threat evaluation configuration processes: A design proposal. Information Fusion (FUSION), 2014 17th International Conference on. :1-8.

Threat evaluation is concerned with estimating the intent, capability and opportunity of detected objects in relation to our own assets in an area of interest. To infer whether a target is threatening and to which degree is far from a trivial task. Expert operators have normally to their aid different support systems that analyze the incoming data and provide recommendations for actions. Since the ultimate responsibility lies in the operators, it is crucial that they trust and know how to configure and use these systems, as well as have a good understanding of their inner workings, strengths and limitations. To limit the negative effects of inadequate cooperation between the operators and their support systems, this paper presents a design proposal that aims at making the threat evaluation process more transparent. We focus on the initialization, configuration and preparation phases of the threat evaluation process, supporting the user in the analysis of the behavior of the system considering the relevant parameters involved in the threat estimations. For doing so, we follow a known design process model and we implement our suggestions in a proof-of-concept prototype that we evaluate with military expert system designers.

R. Saravanan, V. Saminadan, V. Thirunavukkarasu.  2015.  "VLSI implementation of BER measurement for wireless communication system". 2015 International Conference on Innovations in Information, Embedded and Communication Systems (ICIIECS). :1-5.

This paper presents the Bit Error Rate (BER) performance of the wireless communication system. The complexity of modern wireless communication system are increasing at fast pace. It becomes challenging to design the hardware of wireless system. The proposed system consists of MIMO transmitter and MIMO receiver along with the along with a realistic fading channel. To make the data transmission more secure when the data are passed into channel Crypto-System with Embedded Error Control (CSEEC) is used. The system supports data security and reliability using forward error correction codes (FEC). Security is provided through the use of a new symmetric encryption algorithm, and reliability is provided by the use of FEC codes. The system aims at speeding up the encryption and encoding operations and reduces the hardware dedicated to each of these operations. The proposed system allows users to achieve more security and reliable communication. The proposed BER measurement communication system consumes low power compared to existing systems. Advantage of VLSI based BER measurement it that they can be used in the Real time applications and it provides single chip solution.

Thakre, P. P., Sahare, V. N..  2017.  VM live migration time reduction using NAS based algorithm during VM live migration. 2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS). :242–246.

Live migration is the process used in virtualization environment of datacenters in order to take the benefit of zero downtime during system maintenance. But during migrating live virtual machines along with system files and storage data, network traffic gets increases across network bandwidth and delays in migration time. There is need to reduce the migration time in order to maintain the system performance by analyzing and optimizing the storage overheads which mainly creates due to unnecessary duplicated data transferred during live migration. So there is need of such storage device which will keep the duplicated data residing in both the source as well as target physical host i.e. NAS. The proposed hash map based algorithm maps all I/O operations in order to track the duplicated data by assigning hash value to both NAS and RAM data. Only the unique data then will be sent data to the target host without affecting service level agreement (SLA), without affecting VM migration time, application downtime, SLA violations, VM pre-migration and downtime post migration overheads during pre and post migration of virtual machines.

Nemati, H., Dagenais, M. R..  2018.  VM processes state detection by hypervisor tracing. 2018 Annual IEEE International Systems Conference (SysCon). :1–8.

The diagnosis of performance issues in cloud environments is a challenging problem, due to the different levels of virtualization, the diversity of applications and their interactions on the same physical host. Moreover, because of privacy, security, ease of deployment and execution overhead, an agent-less method, which limits its data collection to the physical host level, is often the only acceptable solution. In this paper, a precise host-based method, to recover wait state for the processes inside a given Virtual Machine (VM), is proposed. The virtual Process State Detection (vPSD) algorithm computes the state of processes through host kernel tracing. The state of a virtual Process (vProcess) is displayed in an interactive trace viewer (Trace Compass) for further inspection. Our proposed VM trace analysis algorithm has been open-sourced for further enhancements and for the benefit of other developers. Experimental evaluations were conducted using a mix of workload types (CPU, Disk, and Network), with different applications like Hadoop, MySQL, and Apache. vPSD, being based on host hypervisor tracing, brings a lower overhead (around 0.03%) as compared to other approaches.

Liu, D., Li, Y., Tang, Y., Wang, B., Xie, W..  2018.  VMPBL: Identifying Vulnerable Functions Based on Machine Learning Combining Patched Information and Binary Comparison Technique by LCS. 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). :800-807.

Nowadays, most vendors apply the same open source code to their products, which is dangerous. In addition, when manufacturers release patches, they generally hide the exact location of the vulnerabilities. So, identifying vulnerabilities in binaries is crucial. However, just searching source program has a lower identifying accuracy of vulnerability, which requires operators further to differentiate searched results. Under this context, we propose VMPBL to enhance identifying the accuracy of vulnerability with the help of patch files. VMPBL, compared with other proposed schemes, uses patched functions according to its vulnerable functions in patch file to further distinguish results. We establish a prototype of VMPBL, which can effectively identify vulnerable function types and get rid of safe functions from results. Firstly, we get the potential vulnerable-patched functions by binary comparison technique based on K-Trace algorithm. Then we combine the functions with vulnerability and patch knowledge database to classify these function pairs and identify the possible vulnerable functions and the vulnerability types. Finally, we test some programs containing real-world CWE vulnerabilities, and one of the experimental results about CWE415 shows that the results returned from only searching source program are about twice as much as the results from VMPBL. We can see that using VMPBL can significantly reduce the false positive rate of discovering vulnerabilities compared with analyzing source files alone.

Fietz, Jonas, Whitlock, Sam, Ioannidis, George, Argyraki, Katerina, Bugnion, Edouard.  2016.  VNToR: Network Virtualization at the Top-of-Rack Switch. Proceedings of the Seventh ACM Symposium on Cloud Computing. :428–441.

Cloud providers typically implement abstractions for network virtualization on the server, within the operating system that hosts the tenant virtual machines or containers. Despite being flexible and convenient, this approach has fundamental problems: incompatibility with bare-metal support, unnecessary performance overhead, and susceptibility to hypervisor breakouts. To solve these, we propose to offload the implementation of network-virtualization abstractions to the top-of-rack switch (ToR). To show that this is feasible and beneficial, we present VNToR, a ToR that takes over the implementation of the security-group abstraction. Our prototype combines commodity switching hardware with a custom software stack and is integrated in OpenStack Neutron. We show that VNToR can store tens of thousands of access rules, adapts to traffic-pattern changes in less than a millisecond, and significantly outperforms the state of the art.

Yao, Y., Xiao, B., Wu, G., Liu, X., Yu, Z., Zhang, K., Zhou, X..  2017.  Voiceprint: A Novel Sybil Attack Detection Method Based on RSSI for VANETs. 2017 47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN). :591–602.

Vehicular Ad Hoc Networks (VANETs) enable vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications that bring many benefits and conveniences to improve the road safety and drive comfort in future transportation systems. Sybil attack is considered one of the most risky threats in VANETs since a Sybil attacker can generate multiple fake identities with false messages to severely impair the normal functions of safety-related applications. In this paper, we propose a novel Sybil attack detection method based on Received Signal Strength Indicator (RSSI), Voiceprint, to conduct a widely applicable, lightweight and full-distributed detection for VANETs. To avoid the inaccurate position estimation according to predefined radio propagation models in previous RSSI-based detection methods, Voiceprint adopts the RSSI time series as the vehicular speech and compares the similarity among all received time series. Voiceprint does not rely on any predefined radio propagation model, and conducts independent detection without the support of the centralized infrastructure. It has more accurate detection rate in different dynamic environments. Extensive simulations and real-world experiments demonstrate that the proposed Voiceprint is an effective method considering the cost, complexity and performance.

Xu, Tangwei, Lu, Xiaozhen, Xiao, Liang, Tang, Yuliang, Dai, Huaiyu.  2019.  Voltage Based Authentication for Controller Area Networks with Reinforcement Learning. ICC 2019 - 2019 IEEE International Conference on Communications (ICC). :1–5.
Controller area networks (CANs) are vulnerable to spoofing attacks such as frame falsifying attacks, as electronic control units (ECUs) send and receive messages without any authentication and encryption. In this paper, we propose a physical authentication scheme that exploits the voltage features of the ECU signals on the CAN bus and applies reinforcement learning to choose the authentication mode such as the protection level and test threshold. This scheme enables a monitor node to optimize the authentication mode via trial-and-error without knowing the CAN bus signal model and spoofing model. Experimental results show that the proposed authentication scheme can significantly improve the authentication accuracy and response compared with a benchmark scheme.
Boykov, Y., Isack, H., Olsson, C., Ayed, I. B..  2015.  Volumetric Bias in Segmentation and Reconstruction: Secrets and Solutions. 2015 IEEE International Conference on Computer Vision (ICCV). :1769–1777.

Many standard optimization methods for segmentation and reconstruction compute ML model estimates for appearance or geometry of segments, e.g. Zhu-Yuille [23], Torr [20], Chan-Vese [6], GrabCut [18], Delong et al. [8]. We observe that the standard likelihood term in these formu-lations corresponds to a generalized probabilistic K-means energy. In learning it is well known that this energy has a strong bias to clusters of equal size [11], which we express as a penalty for KL divergence from a uniform distribution of cardinalities. However, this volumetric bias has been mostly ignored in computer vision. We demonstrate signif- icant artifacts in standard segmentation and reconstruction methods due to this bias. Moreover, we propose binary and multi-label optimization techniques that either (a) remove this bias or (b) replace it by a KL divergence term for any given target volume distribution. Our general ideas apply to continuous or discrete energy formulations in segmenta- tion, stereo, and other reconstruction problems.

Noroozi, Hamid, Khodaei, Mohammad, Papadimitratos, Panos.  2018.  VPKIaaS: A Highly-Available and Dynamically-Scalable Vehicular Public-Key Infrastructure. Proceedings of the 11th ACM Conference on Security & Privacy in Wireless and Mobile Networks. :302–304.
The central building block of secure and privacy-preserving Vehicular Communication (VC) systems is a Vehicular Public-Key Infrastructure (VPKI), which provides vehicles with multiple anonymized credentials, termed pseudonyms. These pseudonyms are used to ensure message authenticity and integrity while preserving vehicle (and thus passenger) privacy. In the light of emerging large-scale multi-domain VC environments, the efficiency of the VPKI and, more broadly, its scalability are paramount. In this extended abstract, we leverage the state-of-the-art VPKI system and enhance its functionality towards a highly-available and dynamically-scalable design; this ensures that the system remains operational in the presence of benign failures or any resource depletion attack, and that it dynamically scales out, or possibly scales in, according to the requests' arrival rate. Our full-blown implementation on the Google Cloud Platform shows that deploying a VPKI for a large-scale scenario can be cost-effective, while efficiently issuing pseudonyms for the requesters.
Vincur, J., Navrat, P., Polasek, I..  2017.  VR City: Software Analysis in Virtual Reality Environment. 2017 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C). :509–516.
This paper presents software visualization tool that utilizes the modified city metaphor to represent software system and related analysis data in virtual reality environment. To better address all three kinds of software aspects we propose a new layouting algorithm that provides a higher level of detail and position the buildings according to the coupling between classes that they represent. Resulting layout allows us to visualize software metrics and source code modifications at the granularity of methods, visualize method invocations involved in program execution and to support the remodularization analysis. To further reduce the cognitive load and increase efficiency of 3D visualization we allow users to observe and interact with our city in immersive virtual reality environment that also provides a source code browsing feature. We demonstrate the use of our approach on two open-source systems.
Falk, E., Repcek, S., Fiz, B., Hommes, S., State, R., Sasnauskas, R..  2017.  VSOC - A Virtual Security Operating Center. GLOBECOM 2017 - 2017 IEEE Global Communications Conference. :1–6.

Security in virtualised environments is becoming increasingly important for institutions, not only for a firm's own on-site servers and network but also for data and sites that are hosted in the cloud. Today, security is either handled globally by the cloud provider, or each customer needs to invest in its own security infrastructure. This paper proposes a Virtual Security Operation Center (VSOC) that allows to collect, analyse and visualize security related data from multiple sources. For instance, a user can forward log data from its firewalls, applications and routers in order to check for anomalies and other suspicious activities. The security analytics provided by the VSOC are comparable to those of commercial security incident and event management (SIEM) solutions, but are deployed as a cloud-based solution with the additional benefit of using big data processing tools to handle large volumes of data. This allows us to detect more complex attacks that cannot be detected with todays signature-based (i.e. rules) SIEM solutions.

Pointcheval, David, Wang, Guilin.  2017.  VTBPEKE: Verifier-Based Two-Basis Password Exponential Key Exchange. Proceedings of the 2017 ACM on Asia Conference on Computer and Communications Security. :301–312.

PAKE protocols, for Password-Authenticated Key Exchange, enable two parties to establish a shared cryptographically strong key over an insecure network using a short common secret as authentication means. After the seminal work by Bellovin and Merritt, with the famous EKE, for Encrypted Key Exchange, various settings and security notions have been defined, and many protocols have been proposed. In this paper, we revisit the promising SPEKE, for Simple Password Exponential Key Exchange, proposed by Jablon. The only known security analysis works in the random oracle model under the CDH assumption, but in the multiplicative groups of finite fields only (subgroups of Zp*), which means the use of large elements and so huge communications and computations. Our new instantiation (TBPEKE, for Two-Basis Password Exponential Key Exchange) applies to any group, and our security analysis requires a DLIN-like assumption to hold. In particular, one can use elliptic curves, which leads to a better efficiency, at both the communication and computation levels. We additionally consider server corruptions, which immediately leak all the passwords to the adversary with symmetric PAKE. We thus study an asymmetric variant, also known as VPAKE, for Verifier-based Password Authenticated Key Exchange. We then propose a verifier-based variant of TBPEKE, the so-called VTBPEKE, which is also quite efficient, and resistant to server-compromise.

He, Lu, Xu, Chen, Luo, Yan.  2016.  vTC: Machine Learning Based Traffic Classification As a Virtual Network Function. Proceedings of the 2016 ACM International Workshop on Security in Software Defined Networks & Network Function Virtualization. :53–56.

Network flow classification is fundamental to network management and network security. However, it is challenging to classify network flows at very high line rates while simultaneously preserving user privacy. Machine learning based classification techniques utilize only meta-information of a flow and have been shown to be effective in identifying network flows. We analyze a group of widely used machine learning classifiers, and observe that the effectiveness of different classification models depends highly upon the protocol types as well as the flow features collected from network data.We propose vTC, a design of virtual network functions to flexibly select and apply the best suitable machine learning classifiers at run time. The experimental results show that the proposed NFV for flow classification can improve the accuracy of classification by up to 13%.

Jiaqi Yan, Illinois Institute of Technology, Dong Jin, Illinois Institute of Technology.  2015.  VT-Miniet: Virtual-time-enabled Mininet for Scalable and Accurate Software-Define Network Emulation. ACM SIGCOMM Symposium on SDN Research.

The advancement of software-defined networking (SDN) technology is highly dependent on the successful transformations from in-house research ideas to real-life products. To enable such transformations, a testbed offering scalable and high fidelity networking environment for testing and evaluating new/existing designs is extremely valuable. Mininet, the most popular SDN emulator by far, is designed to achieve both accuracy and scalability by running unmodified code of network applications in lightweight Linux Containers. How- ever, Mininet cannot guarantee performance fidelity under high workloads, in particular when the number of concurrent active events is more than the number of parallel cores. In this project, we develop a lightweight virtual time system in Linux container and integrate the system with Mininet, so that all the containers have their own virtual clocks rather than using the physical system clock which reflects the se- rialized execution of multiple containers. With the notion of virtual time, all the containers perceive virtual time as if they run independently and concurrently. As a result, inter- actions between the containers and the physical system are artificially scaled, making a network appear to be ten times faster from the viewpoint of applications within the contain- ers than it actually is. We also design an adaptive virtual time scheduling subsystem in Mininet, which is responsible to balance the experiment speed and fidelity. Experimen- tal results demonstrate that embedding virtual time into Mininet significantly enhances its performance fidelity, and therefore, results in a useful platform for the SDN community to conduct scalable experiments with high fidelity.

Biswas, S., Sarwat, A..  2016.  Vulnerabilities in two-area Automatic Generation Control systems under cyberattack. 2016 Resilience Week (RWS). :40–45.

The power grid is a prime target of cyber criminals and warrants special attention as it forms the backbone of major infrastructures that drive the nation's defense and economy. Developing security measures for the power grid is challenging since it is physically dispersed and interacts dynamically with associated cyber infrastructures that control its operation. This paper presents a mathematical framework to investigate stability of two area systems due to data attacks on Automatic Generation Control (AGC) system. Analytical and simulation results are presented to identify attack levels that could drive the AGC system to potentially become unstable.

Liang, J., Sankar, L., Kosut, O..  2017.  Vulnerability analysis and consequences of false data injection attack on power system state estimation. 2017 IEEE Power Energy Society General Meeting. :1–1.
An unobservable false data injection (FDI) attack on AC state estimation (SE) is introduced and its consequences on the physical system are studied. With a focus on understanding the physical consequences of FDI attacks, a bi-level optimization problem is introduced whose objective is to maximize the physical line flows subsequent to an FDI attack on DC SE. The maximization is subject to constraints on both attacker resources (size of attack) and attack detection (limiting load shifts) as well as those required by DC optimal power flow (OPF) following SE. The resulting attacks are tested on a more realistic non-linear system model using AC state estimation and ACOPF, and it is shown that, with an appropriately chosen sub-network, the attacker can overload transmission lines with moderate shifts of load.
Paul, S., Ni, Z..  2017.  Vulnerability Analysis for Simultaneous Attack in Smart Grid Security. 2017 IEEE Power Energy Society Innovative Smart Grid Technologies Conference (ISGT). :1–5.

Power grid infrastructures have been exposed to several terrorists and cyber attacks from different perspectives and have resulted in critical system failures. Among different attack strategies, simultaneous attack is feasible for the attacker if enough resources are available at the moment. In this paper, vulnerability analysis for simultaneous attack is investigated, using a modified cascading failure simulator with reduced calculation time than the existing methods. A new damage measurement matrix is proposed with the loss of generation power and time to reach the steady-state condition. The combination of attacks that can result in a total blackout in the shortest time are considered as the strongest simultaneous attack for the system from attacker's viewpoint. The proposed approach can be used for general power system test cases. In this paper, we conducted the experiments on W&W 6 bus system and IEEE 30 bus system for demonstration of the result. The modified simulator can automatically find the strongest attack combinations for reaching maximum damage in terms of generation power loss and time to reach black-out.

Astaburuaga, Ignacio, Lombardi, Amee, La Torre, Brian, Hughes, Carolyn, Sengupta, Shamik.  2019.  Vulnerability Analysis of AR.Drone 2.0, an Embedded Linux System. 2019 IEEE 9th Annual Computing and Communication Workshop and Conference (CCWC). :0666–0672.
The goal of this work was to identify and try to solve some of the vulnerabilities present in the AR Drone 2.0 by Parrot. The approach was to identify how the system worked, find and analyze vulnerabilities and flaws in the system as a whole and in the software, and find solutions to those problems. Analyzing the results of some tests showed that the system has an open WiFi network and the communication between the controller and the drone are unencrypted. Analyzing the Linux operating system that the drone uses, we see that "Pairing Mode" is the only way the system protects itself from unauthorized control. This is a feature that can be easily bypassed. Port scans reveal that the system has all the ports for its services open and exposed. This makes it susceptible to attacks like DoS and takeover. This research also focuses on some of the software vulnerabilities, such as Busybox that the drone runs. Lastly, this paper discuses some of the possible methods that can be used to secure the drone. These methods include securing the messages via SSH Tunnel, closing unused ports, and re-implementing the software used by the drone and the controller.
Ojagbule, O., Wimmer, H., Haddad, R. J..  2018.  Vulnerability Analysis of Content Management Systems to SQL Injection Using SQLMAP. SoutheastCon 2018. :1–7.

There are over 1 billion websites today, and most of them are designed using content management systems. Cybersecurity is one of the most discussed topics when it comes to a web application and protecting the confidentiality, integrity of data has become paramount. SQLi is one of the most commonly used techniques that hackers use to exploit a security vulnerability in a web application. In this paper, we compared SQLi vulnerabilities found on the three most commonly used content management systems using a vulnerability scanner called Nikto, then SQLMAP for penetration testing. This was carried on default WordPress, Drupal and Joomla website pages installed on a LAMP server (Iocalhost). Results showed that each of the content management systems was not susceptible to SQLi attacks but gave warnings about other vulnerabilities that could be exploited. Also, we suggested practices that could be implemented to prevent SQL injections.

Huang, P., Wang, Y., Yan, G..  2017.  Vulnerability Analysis of Electrical Cyber Physical Systems Using a Simulation Platform. IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society. :489–494.

This paper considers a framework of electrical cyber-physical systems (ECPSs) in which each bus and branch in a power grid is equipped with a controller and a sensor. By means of measuring the damages of cyber attacks in terms of cutting off transmission lines, three solution approaches are proposed to assess and deal with the damages caused by faults or cyber attacks. Splitting incident is treated as a special situation in cascading failure propagation. A new simulation platform is built for simulating the protection procedure of ECPSs under faults. The vulnerability of ECPSs under faults is analyzed by experimental results based on IEEE 39-bus system.