Visible to the public Biblio

Found 12297 results

2020
Lu, Xiao, Jing, Jiangping, Wu, Yi.  2020.  False Data Injection Attack Location Detection Based on Classification Method in Smart Grid. 2020 2nd International Conference on Artificial Intelligence and Advanced Manufacture (AIAM). :133—136.
The state estimation technology is utilized to estimate the grid state based on the data of the meter and grid topology structure. The false data injection attack (FDIA) is an information attack method to disturb the security of the power system based on the meter measurement. Current FDIA detection researches pay attention on detecting its presence. The location information of FDIA is also important for power system security. In this paper, locating the FDIA of the meter is regarded as a multi-label classification problem. Each label represents the state of the corresponding meter. The ensemble model, the multi-label decision tree algorithm, is utilized as the classifier to detect the exact location of the FDIA. This method does not need the information of the power topology and statistical knowledge assumption. The numerical experiments based on the IEEE-14 bus system validates the performance of the proposed method.
Đuranec, A., Gruičić, S., Žagar, M..  2020.  Forensic analysis of Windows 10 Sandbox. 2020 43rd International Convention on Information, Communication and Electronic Technology (MIPRO). :1224—1229.

With each Windows operating system Microsoft introduces new features to its users. Newly added features present a challenge to digital forensics examiners as they are not analyzed or tested enough. One of the latest features, introduced in Windows 10 version 1909 is Windows Sandbox; a lightweight, temporary, environment for running untrusted applications. Because of the temporary nature of the Sandbox and insufficient documentation, digital forensic examiners are facing new challenges when examining this newly added feature which can be used to hide different illegal activities. Throughout this paper, the focus will be on analyzing different Windows artifacts and event logs, with various tools, left behind as a result of the user interaction with the Sandbox feature on a clear virtual environment. Additionally, the setup of testing environment will be explained, the results of testing and interpretation of the findings will be presented, as well as open-source tools used for the analysis.

Samriya, Jitendra Kumar, Kumar, Narander.  2020.  Fuzzy Ant Bee Colony For Security And Resource Optimization In Cloud Computing. 2020 5th International Conference on Computing, Communication and Security (ICCCS). :1—5.

Cloud computing (CC) systems prevail to be the widespread computational paradigms for offering immense scalable and elastic services. Computing resources in cloud environment should be scheduled to facilitate the providers to utilize the resources moreover the users could get low cost applications. The most prominent need in job scheduling is to ensure Quality of service (QoS) to the user. In the boundary of the third party the scheduling takes place hence it is a significant condition for assuring its security. The main objective of our work is to offer QoS i.e. cost, makespan, minimized migration of task with security enforcement moreover the proposed algorithm guarantees that the admitted requests are executed without violating service level agreement (SLA). These objectives are attained by the proposed Fuzzy Ant Bee Colony algorithm. The experimental outcome confirms that secured job scheduling objective with assured QoS is attained by the proposed algorithm.

Quincozes, S. E., Passos, D., Albuquerque, C., Ochi, L. S., Mossé, D..  2020.  GRASP-based Feature Selection for Intrusion Detection in CPS Perception Layer. 2020 4th Conference on Cloud and Internet of Things (CIoT). :41—48.

Cyber-Physical Systems (CPS) will form the basis for the world's critical infrastructure and, thus, have the potential to significantly impact human lives in the near future. In recent years, there has been an increasing demand for connectivity in CPS, which has brought to attention the issue of cyber security. Aside from traditional information systems threats, CPS faces new challenges due to the heterogeneity of devices and protocols. In this paper, we investigate how Feature Selection may improve intrusion detection accuracy. In particular, we propose an adapted Greedy Randomized Adaptive Search Procedure (GRASP) metaheuristic to improve the classification performance in CPS perception layer. Our numerical results reveal that GRASP metaheuristic overcomes traditional filter-based feature selection methods for detecting four attack classes in CPSs.

Salib, E. H., Aboutabl, M. S..  2020.  Hands-on Undergraduate Labs on Anonymity Cryptographic Algorithms. 2020 IEEE Frontiers in Education Conference (FIE). :1—9.

This is an innovative practice full paper. In past projects, we have successfully used a private TOR (anonymity network) platform that enabled our students to explore the end-to-end inner workings of the TOR anonymity network through a number of controlled hands-on lab assignments. These have saisfied the needs of curriculum focusing on networking functions and algorithms. To be able to extend the use and application of the private TOR platform into cryptography courses, there is a desperate need to enhance the platform to allow the development of hands-on lab assignments on the cryptographic algorithms and methods utilized in the creation of TOR secure connections and end-to-end circuits for anonymity.In tackling this challenge, and since TOR is open source software, we identify the cryptographic functions called by the TOR algorithms in the process of establishing TLS connections and creating end-to-end TOR circuits as well tearing them down. We instrumented these functions with the appropriate code to log the cryptographic keys dynamically created at all nodes involved in the creation of the end to end circuit between the Client and the exit relay (connected to the target server).We implemented a set of pedagogical lab assignments on a private TOR platform and present them in this paper. Using these assignments, students are able to investigate and validate the cryptographic procedures applied in the establishment of the initial TLS connection, the creation of the first leg of a TOR circuit, as well as extending the circuit through additional relays (at least two relays). More advanced assignments are created to challenge the students to unwrap the traffic sent from the Client to the exit relay at all onion skin layers and compare it with the actual traffic delivered to the target server.

Bulle, Bruno B., Santin, Altair O., Viegas, Eduardo K., dos Santos, Roger R..  2020.  A Host-based Intrusion Detection Model Based on OS Diversity for SCADA. IECON 2020 The 46th Annual Conference of the IEEE Industrial Electronics Society. :691—696.

Supervisory Control and Data Acquisition (SCADA) systems have been a frequent target of cyberattacks in Industrial Control Systems (ICS). As such systems are a frequent target of highly motivated attackers, researchers often resort to intrusion detection through machine learning techniques to detect new kinds of threats. However, current research initiatives, in general, pursue higher detection accuracies, neglecting the detection of new kind of threats and their proposal detection scope. This paper proposes a novel, reliable host-based intrusion detection for SCADA systems through the Operating System (OS) diversity. Our proposal evaluates, at the OS level, the SCADA communication over time and, opportunistically, detects, and chooses the most appropriate OS to be used in intrusion detection for reliability purposes. Experiments, performed through a variety of SCADA OSs front-end, shows that OS diversity provides higher intrusion detection scope, improving detection accuracy by up to 8 new attack categories. Besides, our proposal can opportunistically detect the most reliable OS that should be used for the current environment behavior, improving by up to 8%, on average, the system accuracy when compared to a single OS approach, in the best case.

Xu, J., Howard, A..  2020.  How much do you Trust your Self-Driving Car? Exploring Human-Robot Trust in High-Risk Scenarios 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC). :4273—4280.

Trust is an important characteristic of successful interactions between humans and agents in many scenarios. Self-driving scenarios are of particular relevance when discussing the issue of trust due to the high-risk nature of erroneous decisions being made. The present study aims to investigate decision-making and aspects of trust in a realistic driving scenario in which an autonomous agent provides guidance to humans. To this end, a simulated driving environment based on a college campus was developed and presented. An online and an in-person experiment were conducted to examine the impacts of mistakes made by the self-driving AI agent on participants’ decisions and trust. During the experiments, participants were asked to complete a series of driving tasks and make a sequence of decisions in a time-limited situation. Behavior analysis indicated a similar relative trend in the decisions across these two experiments. Survey results revealed that a mistake made by the self-driving AI agent at the beginning had a significant impact on participants’ trust. In addition, similar overall experience and feelings across the two experimental conditions were reported. The findings in this study add to our understanding of trust in human-robot interaction scenarios and provide valuable insights for future research work in the field of human-robot trust.

Fatehi, Nina, Shahhoseini, HadiShahriar.  2020.  A Hybrid Algorithm for Evaluating Trust in Online Social Networks. 2020 10th International Conference on Computer and Knowledge Engineering (ICCKE). :158—162.
The acceleration of extending popularity of Online Social Networks (OSNs) thanks to various services with which they provide people, is inevitable. This is why in OSNs security as a way to protect private data of users to be abused by unauthoritative people has a vital role to play. Trust evaluation is the security approach that has been utilized since the advent of OSNs. Graph-based approaches are among the most popular methods for trust evaluation. However, graph-based models need to employ limitations in the search process of finding trusted paths. This contributes to a reduction in trust accuracy. In this investigation, a learning-based model which with no limitation is able to find reliable users of any target user, is proposed. Experimental results depict 12% improvement in trust accuracy compares to models based on the graph-based approach.
Jin, Ya, Chen, Yin Fang, Xu, Chang Da, Qi, Yi Chao, Chen, Shao Kang, Chen, Wei, Zhu, Ning Hua.  2020.  A hybrid optical frequency-hopping scheme based on OAM multiplexing for secure optical communications. 2020 Asia Communications and Photonics Conference (ACP) and International Conference on Information Photonics and Optical Communications (IPOC). :1—3.
In this paper, a hybrid optical frequency hopping system based on OAM multiplexing is proposed, which is mainly applied to the security of free space optical communication. In the proposed scheme, the segmented users' data goes through two stages of hopping successively to realize data hiding. And the security performance is also analyzed in this paper. © 2020 The Author(s).
Jeong, J. H., Choi, S. G..  2020.  Hybrid System to Minimize Damage by Zero-Day Attack based on NIDPS and HoneyPot. 2020 International Conference on Information and Communication Technology Convergence (ICTC). :1650—1652.

This paper presents hybrid system to minimize damage by zero-day attack. Proposed system consists of signature-based NIDPS, honeypot and temporary queue. When proposed system receives packet from external network, packet which is known for attack packet is dropped by signature-based NIDPS. Passed packets are redirected to honeypot, because proposed system assumes that all packets which pass NIDPS have possibility of zero-day attack. Redirected packet is stored in temporary queue and if the packet has possibility of zero-day attack, honeypot extracts signature of the packet. Proposed system creates rule that match rule format of NIDPS based on extracted signatures and updates the rule. After the rule update is completed, temporary queue sends stored packet to NIDPS then packet with risk of attack can be dropped. Proposed system can reduce time to create and apply rule which can respond to unknown attack packets. Also, it can drop packets that have risk of zero-day attack in real time.

Fei, Wanghao, Moses, Paul, Davis, Chad.  2020.  Identification of Smart Grid Attacks via State Vector Estimator and Support Vector Machine Methods. 2020 Intermountain Engineering, Technology and Computing (IETC). :1—6.

In recent times, an increasing amount of intelligent electronic devices (IEDs) are being deployed to make power systems more reliable and economical. While these technologies are necessary for realizing a cyber-physical infrastructure for future smart power grids, they also introduce new vulnerabilities in the grid to different cyber-attacks. Traditional methods such as state vector estimation (SVE) are not capable of identifying cyber-attacks while the geometric information is also injected as an attack vector. In this paper, a machine learning based smart grid attack identification method is proposed. The proposed method is carried out by first collecting smart grid power flow data for machine learning training purposes which is later used to classify the attacks. The performance of both the proposed SVM method and the traditional SVE method are validated on IEEE 14, 30, 39, 57 and 118 bus systems, and the performance regarding the scale of the power system is evaluated. The results show that the SVM-based method performs better than the SVE-based in attack identification over a much wider scale of power systems.

Bogdan-Iulian, C., Vasilică-Gabriel, S., Alexandru, M. D., Nicolae, G., Andrei, V..  2020.  Improved Secure Internet of Things System using Web Services and Low Power Single-board Computers. 2020 International Conference on e-Health and Bioengineering (EHB). :1—5.

Internet of Things (IoT) systems are becoming widely used, which makes them to be a high-value target for both hackers and crackers. From gaining access to sensitive information to using them as bots for complex attacks, the variety of advantages after exploiting different security vulnerabilities makes the security of IoT devices to be one of the most challenging desideratum for cyber security experts. In this paper, we will propose a new IoT system, designed to ensure five data principles: confidentiality, integrity, availability, authentication and authorization. The innovative aspects are both the usage of a web-based communication and a custom dynamic data request structure.

Moran, Kevin, Palacio, David N., Bernal-Cárdenas, Carlos, McCrystal, Daniel, Poshyvanyk, Denys, Shenefiel, Chris, Johnson, Jeff.  2020.  Improving the Effectiveness of Traceability Link Recovery using Hierarchical Bayesian Networks. 2020 IEEE/ACM 42nd International Conference on Software Engineering (ICSE). :873—885.
Traceability is a fundamental component of the modern software development process that helps to ensure properly functioning, secure programs. Due to the high cost of manually establishing trace links, researchers have developed automated approaches that draw relationships between pairs of textual software artifacts using similarity measures. However, the effectiveness of such techniques are often limited as they only utilize a single measure of artifact similarity and cannot simultaneously model (implicit and explicit) relationships across groups of diverse development artifacts. In this paper, we illustrate how these limitations can be overcome through the use of a tailored probabilistic model. To this end, we design and implement a HierarchiCal PrObabilistic Model for SoftwarE Traceability (Comet) that is able to infer candidate trace links. Comet is capable of modeling relationships between artifacts by combining the complementary observational prowess of multiple measures of textual similarity. Additionally, our model can holistically incorporate information from a diverse set of sources, including developer feedback and transitive (often implicit) relationships among groups of software artifacts, to improve inference accuracy. We conduct a comprehensive empirical evaluation of Comet that illustrates an improvement over a set of optimally configured baselines of ≈14% in the best case and ≈5% across all subjects in terms of average precision. The comparative effectiveness of Comet in practice, where optimal configuration is typically not possible, is likely to be higher. Finally, we illustrate Comet's potential for practical applicability in a survey with developers from Cisco Systems who used a prototype Comet Jenkins plugin.
Alnsour, Rawan, Hamdan, Basil.  2020.  Incorporating SCADA Cybersecurity in Undergraduate Engineering Technology Information Technology Education. 2020 Intermountain Engineering, Technology and Computing (IETC). :1—4.

The purpose of this paper is threefold. First, it makes the case for incorporating cybersecurity principles into undergraduate Engineering Technology Education and for incorporating Industrial Control Systems (ICS) principles into undergraduate Information Technology (IT)/Cybersecurity Education. Specifically, the paper highlights the knowledge/skill gap between engineers and IT/Cybersecurity professionals with respect to the cybersecurity of the ICS. Secondly, it identifies several areas where traditional IT systems and ICS intercept. This interception not only implies that ICS are susceptible to the same cyber threats as traditional IT/IS but also to threats that are unique to ICS. Subsequently, the paper identifies several areas where cybersecurity principles can be applied to ICS. By incorporating cybersecurity principles into Engineering Technology Education, the paper hopes to provide IT/Cybersecurity and Engineering Students with (a) the theoretical knowledge of the cybersecurity issues associated with administering and operating ICS and (b) the applied technical skills necessary to manage and mitigate the cyber risks against these systems. Overall, the paper holds the promise of contributing to the ongoing effort aimed at bridging the knowledge/skill gap with respect to securing ICS against cyber threats and attacks.

Lyshevski, S. E., Aved, A., Morrone, P..  2020.  Information-Centric Cyberattack Analysis and Spatiotemporal Networks Applied to Cyber-Physical Systems. 2020 IEEE Microwave Theory and Techniques in Wireless Communications (MTTW). 1:172—177.

Cyber-physical systems (CPS) depend on cybersecurity to ensure functionality, data quality, cyberattack resilience, etc. There are known and unknown cyber threats and attacks that pose significant risks. Information assurance and information security are critical. Many systems are vulnerable to intelligence exploitation and cyberattacks. By investigating cybersecurity risks and formal representation of CPS using spatiotemporal dynamic graphs and networks, this paper investigates topics and solutions aimed to examine and empower: (1) Cybersecurity capabilities; (2) Information assurance and system vulnerabilities; (3) Detection of cyber threat and attacks; (4) Situational awareness; etc. We introduce statistically-characterized dynamic graphs, novel entropy-centric algorithms and calculi which promise to ensure near-real-time capabilities.

Usher, Will, Pascucci, Valerio.  2020.  Interactive Visualization of Terascale Data in the Browser: Fact or Fiction? 2020 IEEE 10th Symposium on Large Data Analysis and Visualization (LDAV). :27—36.

Information visualization applications have become ubiquitous, in no small part thanks to the ease of wide distribution and deployment to users enabled by the web browser. Scientific visualization applications, relying on native code libraries and parallel processing, have been less suited to such widespread distribution, as browsers do not provide the required libraries or compute capabilities. In this paper, we revisit this gap in visualization technologies and explore how new web technologies, WebAssembly and WebGPU, can be used to deploy powerful visualization solutions for large-scale scientific data in the browser. In particular, we evaluate the programming effort required to bring scientific visualization applications to the browser through these technologies and assess their competitiveness against classic native solutions. As a main example, we present a new GPU-driven isosurface extraction method for block-compressed data sets, that is suitable for interactive isosurface computation on large volumes in resource-constrained environments, such as the browser. We conclude that web browsers are on the verge of becoming a competitive platform for even the most demanding scientific visualization tasks, such as interactive visualization of isosurfaces from a 1TB DNS simulation. We call on researchers and developers to consider investing in a community software stack to ease use of these upcoming browser features to bring accessible scientific visualization to the browser.

Susanto, Stiawan, D., Arifin, M. A. S., Idris, M. Y., Budiarto, R..  2020.  IoT Botnet Malware Classification Using Weka Tool and Scikit-learn Machine Learning. 2020 7th International Conference on Electrical Engineering, Computer Sciences and Informatics (EECSI). :15—20.

Botnet is one of the threats to internet network security-Botmaster in carrying out attacks on the network by relying on communication on network traffic. Internet of Things (IoT) network infrastructure consists of devices that are inexpensive, low-power, always-on, always connected to the network, and are inconspicuous and have ubiquity and inconspicuousness characteristics so that these characteristics make IoT devices an attractive target for botnet malware attacks. In identifying whether packet traffic is a malware attack or not, one can use machine learning classification methods. By using Weka and Scikit-learn analysis tools machine learning, this paper implements four machine learning algorithms, i.e.: AdaBoost, Decision Tree, Random Forest, and Naïve Bayes. Then experiments are conducted to measure the performance of the four algorithms in terms of accuracy, execution time, and false positive rate (FPR). Experiment results show that the Weka tool provides more accurate and efficient classification methods. However, in false positive rate, the use of Scikit-learn provides better results.

Solomon Doss, J. Kingsleen, Kamalakkannan, S..  2020.  IoT System Accomplishment using BlockChain in Validating and Data Security with Cloud. 2020 Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC). :60—64.
In a block channel IoT system, sensitive details can be leaked by means of the proof of work or address check, as data or application Validation data is applied on the blockchain. In this, the zero-knowledge evidence is applied to a smart metering system to show how to improve the anonymity of the blockchain for privacy safety without disclosing information as a public key. Within this article, a blockchain has been implemented to deter security risks such as data counterfeiting by utilizing intelligent meters. Zero-Knowledge Proof, an anonymity blockchain technology, has been implemented through block inquiry to prevent threats to security like personal information infringement. It was suggested that intelligent contracts would be used to avoid falsification of intelligent meter data and abuse of personal details.
Inshi, S., Chowdhury, R., Elarbi, M., Ould-Slimane, H., Talhi, C..  2020.  LCA-ABE: Lightweight Context-Aware Encryption for Android Applications. 2020 International Symposium on Networks, Computers and Communications (ISNCC). :1—6.

The evolving of context-aware applications are becoming more readily available as a major driver of the growth of future connected smart, autonomous environments. However, with the increasing of security risks in critical shared massive data capabilities and the increasing regulation requirements on privacy, there is a significant need for new paradigms to manage security and privacy compliances. These challenges call for context-aware and fine-grained security policies to be enforced in such dynamic environments in order to achieve efficient real-time authorization between applications and connected devices. We propose in this work a novel solution that aims to provide context-aware security model for Android applications. Specifically, our proposition provides automated context-aware access control model and leverages Attribute-Based Encryption (ABE) to secure data communications. Thorough experiments have been performed and the evaluation results demonstrate that the proposed solution provides an effective lightweight adaptable context-aware encryption model.

Zhao, Yi, Jia, Xian, An, Dou, Yang, Qingyu.  2020.  LSTM-Based False Data Injection Attack Detection in Smart Grids. 2020 35th Youth Academic Annual Conference of Chinese Association of Automation (YAC). :638—644.
As a typical cyber-physical system, smart grid has attracted growing attention due to the safe and efficient operation. The false data injection attack against energy management system is a new type of cyber-physical attack, which can bypass the bad data detector of the smart grid to influence the results of state estimation directly, causing the energy management system making wrong estimation and thus affects the stable operation of power grid. We transform the false data injection attack detection problem into binary classification problem in this paper, which use the long-term and short-term memory network (LSTM) to construct the detection model. After that, we use the BP algorithm to update neural network parameters and utilize the dropout method to alleviate the overfitting problem and to improve the detection accuracy. Simulation results prove that the LSTM-based detection method can achieve higher detection accuracy comparing with the BPNN-based approach.
Moussa, Y., Alexan, W..  2020.  Message Security Through AES and LSB Embedding in Edge Detected Pixels of 3D Images. 2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES). :224—229.

This paper proposes an advanced scheme of message security in 3D cover images using multiple layers of security. Cryptography using AES-256 is implemented in the first layer. In the second layer, edge detection is applied. Finally, LSB steganography is executed in the third layer. The efficiency of the proposed scheme is measured using a number of performance metrics. For instance, mean square error (MSE), peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), mean absolute error (MAE) and entropy.

Quigley, Kevin, Enslin, Johan H., Nazir, Moazzam, Greenwood, Austin.  2020.  Microgrid Design and Control of a Hybrid Building Complex. 2020 IEEE 11th International Symposium on Power Electronics for Distributed Generation Systems (PEDG). :51—56.
Microgrids are a promising alternative to the traditional distribution systems due to their highly desirable features, such as, reliability, resiliency, and efficiency. This paper covers the design, simulation, and economic analysis of a theoretically designed modern, mixed-use commercial and residential building on a feeder in Charleston, SC, USA. The designed system is simulated in PSCAD/EMTDC. The system combines a natural gas CHP turbine and generator block set, solar photovoltaics (PV), and a battery energy storage system (BESS). It is planned to provide power through a DC lighting bus and an AC to several different commercial load profiles as well as 40 apartments of varying sizes. Additionally, a comprehensive economic analysis is completed with available or estimated pricing to prove the feasibility of such a project.
Cedillo, Priscila, Riofrio, Xavier, Prado, Daniela, Orellana, Marcos.  2020.  A Middleware for Managing the Heterogeneity of Data Provining from IoT Devices in Ambient Assisted Living Environments. 2020 IEEE ANDESCON. :1—6.
Internet of Things (IoT) has been growing exponentially in the commercial market in recent years. It is also a fact that people hold one or more computing devices at home. Many of them have been developed to operate through internet connectivity with cloud computing technologies that result in the demand for fast, robust, and secure services. In most cases, the lack of these services makes difficult the transfer of data to fulfill the devices' purposes. Under these conditions, an intermediate layer or middleware is needed to process, filter, and send data through a more efficient alternative. This paper presents the adaptive solution of a middleware architecture as an intermediate layer between smart devices and cloud computing to enhance the management of the heterogeneity of data provining from IoT devices. The proposed middleware provides easy configuration, adaptability, and bearability for different environments. Finally, this solution has been implemented in the healthcare domain, in which IoT solutions are deployed into Ambient Assisted Living (AAL) environments.
Chalkiadakis, Nikolaos, Deyannis, Dimitris, Karnikis, Dimitris, Vasiliadis, Giorgos, Ioannidis, Sotiris.  2020.  The Million Dollar Handshake: Secure and Attested Communications in the Cloud. 2020 IEEE 13th International Conference on Cloud Computing (CLOUD). :63—70.

The number of applications and services that are hosted on cloud platforms is constantly increasing. Nowadays, more and more applications are hosted as services on cloud platforms, co-existing with other services in a mutually untrusted environment. Facilities such as virtual machines, containers and encrypted communication channels aim to offer isolation between the various applications and protect sensitive user data. However, such techniques are not always able to provide a secure execution environment for sensitive applications nor they offer guarantees that data are not monitored by an honest but curious provider once they reach the cloud infrastructure. The recent advancements of trusted execution environments within commodity processors, such as Intel SGX, provide a secure reverse sandbox, where code and data are isolated even from the underlying operating system. Moreover, Intel SGX provides a remote attestation mechanism, allowing the communicating parties to verify their identity as well as prove that code is executed on hardware-assisted software enclaves. Many approaches try to ensure code and data integrity, as well as enforce channel encryption schemes such as TLS, however, these techniques are not enough to achieve complete isolation and secure communications without hardware assistance or are not efficient in terms of performance. In this work, we design and implement a practical attestation system that allows the service provider to offer a seamless attestation service between the hosted applications and the end clients. Furthermore, we implement a novel caching system that is capable to eliminate the latencies introduced by the remote attestation process. Our approach allows the parties to attest one another before each communication attempt, with improved performance when compared to a standard TLS handshake.

Chang, H.-C., Lin, C.-Y., Liao, D.-J., Koo, T.-M..  2020.  The Modbus Protocol Vulnerability Test in Industrial Control Systems. 2020 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC). :375—378.

Industrial Control Systems (ICSs) are widely used in critical infrastructure around the world to provide services that sustain peoples' livelihoods and economic operations. However, compared with the critical infrastructure, the security of the ICS itself is still insufficient, and there will be a degree of damage, if it is attacked or invaded. In the past, an ICS was designed to operate in a traditional closed network, so the industrial equipment and transmission protocol lacked security verification. In addition, an ICS has high availability requirements, so that its equipment is rarely replaced and upgraded. Although many scholars have proposed the defense mechanism that is applicable to ICS in the past, there is still a lack of tested means to verify these defense technologies. The purpose of this study is to analyze the security of a system using the Modbus transmission protocol in an ICS, to establish a modular security test system based on four types of attacks that have been identified in the past literature, namely, a detection attack, a command injection attack, a response injection attack and a denial of service, to implement the attack results and to display the process in the virtual environment of Conpot and Rapid SCADA, and finally, to adopt the ICS security standards mentioned by previous scholars, namely, confidentiality, integrity and availability, as the performance evaluation criteria of this study.