Visible to the public Biblio

Found 12254 results

Siritoglou, Petros, Oriti, Giovanna.  2020.  Distributed Energy Resources Design Method to Improve Energy Security in Critical Facilities. 2020 IEEE International Conference on Environment and Electrical Engineering and 2020 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I CPS Europe). :1–6.

This paper presents a user-friendly design method for accurately sizing the distributed energy resources of a stand-alone microgrid to meet the critical load demands of a military, commercial, industrial, or residential facility when the utility power is not available. The microgrid combines renewable resources such as photovoltaics (PV) with an energy storage system to increase energy security for facilities with critical loads. The design tool's novelty includes compliance with IEEE standards 1562 and 1013 and addresses resilience, which is not taken into account in existing design methods. Several case studies, simulated with a physics-based model, validate the proposed design method. Additionally, the design and the simulations were validated by 24-hour laboratory experiments conducted on a microgrid assembled using commercial off the shelf components.

Ahmedova, Oydin, Mardiyev, Ulugbek, Tursunov, Otabek.  2020.  Generation and Distribution Secret Encryption Keys with Parameter. 2020 International Conference on Information Science and Communications Technologies (ICISCT). :1—4.
This article describes a new way to generate and distribute secret encryption keys, in which the processes of generating a public key and formicating a secret encryption key are performed in algebra with a parameter, the secrecy of which provides increased durability of the key.
Cai, Feiyang, Li, Jiani, Koutsoukos, Xenofon.  2020.  Detecting Adversarial Examples in Learning-Enabled Cyber-Physical Systems using Variational Autoencoder for Regression. 2020 IEEE Security and Privacy Workshops (SPW). :208–214.

Learning-enabled components (LECs) are widely used in cyber-physical systems (CPS) since they can handle the uncertainty and variability of the environment and increase the level of autonomy. However, it has been shown that LECs such as deep neural networks (DNN) are not robust and adversarial examples can cause the model to make a false prediction. The paper considers the problem of efficiently detecting adversarial examples in LECs used for regression in CPS. The proposed approach is based on inductive conformal prediction and uses a regression model based on variational autoencoder. The architecture allows to take into consideration both the input and the neural network prediction for detecting adversarial, and more generally, out-of-distribution examples. We demonstrate the method using an advanced emergency braking system implemented in an open source simulator for self-driving cars where a DNN is used to estimate the distance to an obstacle. The simulation results show that the method can effectively detect adversarial examples with a short detection delay.

Susilo, Willy, Duong, Dung Hoang, Le, Huy Quoc.  2020.  Efficient Post-quantum Identity-based Encryption with Equality Test. 2020 IEEE 26th International Conference on Parallel and Distributed Systems (ICPADS). :633—640.
Public key encryption with equality test (PKEET) enables the testing whether two ciphertexts encrypt the same message. Identity-based encryption with equality test (IBEET) simplify the certificate management of PKEET, which leads to many potential applications such as in smart city applications or Wireless Body Area Networks. Lee et al. (ePrint 2016) proposed a generic construction of IBEET scheme in the standard model utilising a 3-level hierachy IBE together with a one-time signature scheme, which can be instantiated in lattice setting. Duong et al. (ProvSec 2019) proposed the first direct construction of IBEET in standard model from lattices. However, their scheme achieve CPA security only. In this paper, we improve the Duong et al.'s construction by proposing an IBEET in standard model which achieves CCA2 security and with smaller ciphertext and public key size.
Anubi, Olugbenga Moses, Konstantinou, Charalambos, Wong, Carlos A., Vedula, Satish.  2020.  Multi-Model Resilient Observer under False Data Injection Attacks. 2020 IEEE Conference on Control Technology and Applications (CCTA). :1–8.

In this paper, we present the concept of boosting the resiliency of optimization-based observers for cyber-physical systems (CPS) using auxiliary sources of information. Due to the tight coupling of physics, communication and computation, a malicious agent can exploit multiple inherent vulnerabilities in order to inject stealthy signals into the measurement process. The problem setting considers the scenario in which an attacker strategically corrupts portions of the data in order to force wrong state estimates which could have catastrophic consequences. The goal of the proposed observer is to compute the true states in-spite of the adversarial corruption. In the formulation, we use a measurement prior distribution generated by the auxiliary model to refine the feasible region of a traditional compressive sensing-based regression problem. A constrained optimization-based observer is developed using l1-minimization scheme. Numerical experiments show that the solution of the resulting problem recovers the true states of the system. The developed algorithm is evaluated through a numerical simulation example of the IEEE 14-bus system.

[Anonymous].  2020.  B-DCT based Watermarking Algorithm for Patient Data Protection in IoMT. 2020 International Conference on Information Security and Cryptology (ISCTURKEY). :1—4.
Internet of Medical Things (IoMT) is the connection between medical devices and information systems to share, collect, process, store, and integrate patient and health data using network technologies. X-Rays, MR, MRI, and CT scans are the most frequently used patient medical image data. These images usually include patient information in one of the corners of the image. In this research work, to protect patient information, a new robust and secure watermarking algorithm developed for a selected region of interest (ROI) of medical images. First ROI selected from the medical image, then selected part divided equal blocks and applied Discrete Cosine Transformation (DCT) algorithm to embed a watermark into the selected coefficients. Several geometric and removal attacks are applied to the watermarked multimedia element such as lossy image compression, the addition of Gaussian noise, denoising, filtering, median filtering, sharpening, contrast enhancement, JPEG compression, and rotation. Experimental results show very promising results in PSNR and similarity ratio (SR) values after blocked DCT (B-DCT) based embedding algorithm against the Discrete Wavelet Transformation (DWT), Least Significant Bits (LSB) and DCT algorithms.
ÇELİK, Mahmut, ALKAN, Mustafa, ALKAN, Abdulkerim Oğuzhan.  2020.  Protection of Personal Data Transmitted via Web Service Against Software Developers. 2020 International Conference on Information Security and Cryptology (ISCTURKEY). :88—92.
Through the widespread use of information technologies, institutions have started to offer most of their services electronically. The best example of this is e-government. Since institutions provide their services to the electronic environment, the quality of the services they provide increases and their access to services becomes easier. Since personal information can be verified with inter-agency information sharing systems, wrong or unfair transactions can be prevented. Since information sharing between institutions is generally done through web services, protection of personal data transmitted via web services is of great importance. There are comprehensive national and international regulations on the protection of personal data. According to these regulations, protection of personal data shared between institutions is a legal obligation; protection of personal data is an issue that needs to be handled comprehensively. This study, protection of personal data shared between institutions through web services against software developers is discussed. With a proposed application, it is aimed to take a new security measure for the protection of personal data. The proposed application consists of a web interface prepared using React and Java programming languages and rest services that provide anonymization of personal data.
Satılmış, Hami, Akleylek, Sedat.  2020.  Efficient Implementation of HashSieve Algorithm for Lattice-Based Cryptography. 2020 International Conference on Information Security and Cryptology (ISCTURKEY). :75—79.
The security of lattice-based cryptosystems that are secure for the post-quantum period is based on the difficulty of the shortest vector problem (SVP) and the closest vector problem (CVP). In the literature, many sieving algorithms are proposed to solve these hard problems. In this paper, efficient implementation of HashSieve sieving algorithm is discussed. A modular software library to have an efficient implementation of HashSieve algorithm is developed. Modular software library is used as an infrastructure in order for the HashSieve efficient implementation to be better than the sample in the literature (Laarhoven's standard HashSieve implementation). According to the experimental results, it is observed that HashSieve efficient implementation has a better running time than the example in the literature. It is concluded that both implementations are close to each other in terms of the memory space used.
Ajorlou, Amir, Abbasfar, Aliazam.  2020.  An Optimized Structure of State Channel Network to Improve Scalability of Blockchain Algorithms. 2020 17th International ISC Conference on Information Security and Cryptology (ISCISC). :73—76.
Nowadays, blockchain is very common and widely used in various fields. The properties of blockchain-based algorithms such as being decentralized and uncontrolled by institutions and governments, are the main reasons that has attracted many applications. The security and the scalability limitations are the main challenges for the development of these systems. Using second layer network is one of the various methods proposed to improve the scalability of these systems. This network can increase the total number of transactions per second by creating extra channels between the nodes that operate in a different layer not obligated to be on consensus ledger. In this paper, the optimal structure for the second layer network has been presented. In the proposed structure we try to distribute the parameters of the second layer network as symmetrically as possible. To prove the optimality of this structure we first introduce the maximum scalability bound, and then calculate it for the proposed structure. This paper will show how the second layer method can improve the scalability without any information about the rate of transactions between nodes.
Karimov, Madjit, Tashev, Komil, Rustamova, Sanobar.  2020.  Application of the Aho-Corasick algorithm to create a network intrusion detection system. 2020 International Conference on Information Science and Communications Technologies (ICISCT). :1—5.
One of the main goals of studying pattern matching techniques is their significant role in real-world applications, such as the intrusion detection systems branch. The purpose of the network attack detection systems NIDS is to protect the infocommunication network from unauthorized access. This article provides an analysis of the exact match and fuzzy matching methods, and discusses a new implementation of the classic Aho-Korasik pattern matching algorithm at the hardware level. The proposed approach to the implementation of the Aho-Korasik algorithm can make it possible to ensure the efficient use of resources, such as memory and energy.
Tashev, Komil, Rustamova, Sanobar.  2020.  Analysis of Subject Recognition Algorithms based on Neural Networks. 2020 International Conference on Information Science and Communications Technologies (ICISCT). :1—4.
This article describes the principles of construction, training and use of neural networks. The features of the neural network approach are indicated, as well as the range of tasks for which it is most preferable. Algorithms of functioning, software implementation and results of work of an artificial neural network are presented.
Bakhtiyor, Abdurakhimov, Zarif, Khudoykulov, Orif, Allanov, Ilkhom, Boykuziev.  2020.  Algebraic Cryptanalysis of O'zDSt 1105:2009 Encryption Algorithm. 2020 International Conference on Information Science and Communications Technologies (ICISCT). :1—7.
In this paper, we examine algebraic attacks on the O'zDSt 1105:2009. We begin with a brief review of the meaning of algebraic cryptanalysis, followed by an algebraic cryptanalysis of O'zDSt 1105:2009. Primarily O'zDSt 1105:2009 encryption algorithm is decomposed and each transformation in it is algebraic described separately. Then input and output of each transformation are expressed with other transformation, encryption key, plaintext and cipher text. Created equations, unknowns on it and degree of unknowns are analyzed, and then overall result is given. Based on experimental results, it is impossible to save all system of equations that describes all transformations in O'zDSt 1105:2009 standard. Because, this task requires 273 bytes for the second round. For this reason, it is advisable to evaluate the parameters of the system of algebraic equations, representing the O'zDSt 1105:2009 standard, theoretically.
Tian, Nianfeng, Guo, Qinglai, Sun, Hongbin, Huang, Jianye.  2020.  A Synchronous Iterative Method of Power Flow in Inter-Connected Power Grids Considering Privacy Preservation: A CPS Perspective. 2020 IEEE 4th Conference on Energy Internet and Energy System Integration (EI2). :782–787.
The increasing development of smart grid facilitates that modern power grids inter-connect with each other and form a large power system, making it possible and advantageous to conduct coordinated power flow among several grids. The communication burden and privacy issue are the prominent challenges in the application of synchronous iteration power flow method. In this paper, a synchronous iterative method of power flow in inter-connected power grid considering privacy preservation is proposed. By establishing the masked model of power flow for each sub-grid, the synchronous iteration is conducted by gathering the masked model of sub-grids in the coordination center and solving the masked correction equation in a concentration manner at each step. Generally, the proposed method can concentrate the major calculation of power flow on the coordination center, reduce the communication burden and guarantee the privacy preservation of sub-grids. A case study on IEEE 118-bus test system demonstrate the feasibility and effectiveness of the proposed methodology.
Ramasubramanian, Bhaskar, Niu, Luyao, Clark, Andrew, Bushnell, Linda, Poovendran, Radha.  2020.  Privacy-Preserving Resilience of Cyber-Physical Systems to Adversaries. 2020 59th IEEE Conference on Decision and Control (CDC). :3785–3792.

A cyber-physical system (CPS) is expected to be resilient to more than one type of adversary. In this paper, we consider a CPS that has to satisfy a linear temporal logic (LTL) objective in the presence of two kinds of adversaries. The first adversary has the ability to tamper with inputs to the CPS to influence satisfaction of the LTL objective. The interaction of the CPS with this adversary is modeled as a stochastic game. We synthesize a controller for the CPS to maximize the probability of satisfying the LTL objective under any policy of this adversary. The second adversary is an eavesdropper who can observe labeled trajectories of the CPS generated from the previous step. It could then use this information to launch other kinds of attacks. A labeled trajectory is a sequence of labels, where a label is associated to a state and is linked to the satisfaction of the LTL objective at that state. We use differential privacy to quantify the indistinguishability between states that are related to each other when the eavesdropper sees a labeled trajectory. Two trajectories of equal length will be differentially private if they are differentially private at each state along the respective trajectories. We use a skewed Kantorovich metric to compute distances between probability distributions over states resulting from actions chosen according to policies from related states in order to quantify differential privacy. Moreover, we do this in a manner that does not affect the satisfaction probability of the LTL objective. We validate our approach on a simulation of a UAV that has to satisfy an LTL objective in an adversarial environment.

Alabadi, Montdher, Albayrak, Zafer.  2020.  Q-Learning for Securing Cyber-Physical Systems : A survey. 2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA). :1–13.
A cyber-physical system (CPS) is a term that implements mainly three parts, Physical elements, communication networks, and control systems. Currently, CPS includes the Internet of Things (IoT), Internet of Vehicles (IoV), and many other systems. These systems face many security challenges and different types of attacks, such as Jamming, DDoS.CPS attacks tend to be much smarter and more dynamic; thus, it needs defending strategies that can handle this level of intelligence and dynamicity. Last few years, many researchers use machine learning as a base solution to many CPS security issues. This paper provides a survey of the recent works that utilized the Q-Learning algorithm in terms of security enabling and privacy-preserving. Different adoption of Q-Learning for security and defending strategies are studied. The state-of-the-art of Q-learning and CPS systems are classified and analyzed according to their attacks, domain, supported techniques, and details of the Q-Learning algorithm. Finally, this work highlight The future research trends toward efficient utilization of Q-learning and deep Q-learning on CPS security.
Zanin, M., Menasalvas, E., González, A. Rodriguez, Smrz, P..  2020.  An Analytics Toolbox for Cyber-Physical Systems Data Analysis: Requirements and Challenges. 2020 43rd International Convention on Information, Communication and Electronic Technology (MIPRO). :271–276.
The fast improvement in telecommunication technologies that has characterised the last decade is enabling a revolution centred on Cyber-Physical Systems (CPSs). Elements inside cities, from vehicles to cars, can now be connected and share data, describing both our environment and our behaviours. These data can also be used in an active way, by becoming the tenet of innovative services and products, i.e. of Cyber-Physical Products (CPPs). Still, having data is not tantamount to having knowledge, and an important overlooked topic is how should them be analysed. In this contribution we tackle the issue of the development of an analytics toolbox for processing CPS data. Specifically, we review and quantify the main requirements that should be fulfilled, both functional (e.g. flexibility or dependability) and technical (e.g. scalability, response time, etc.). We further propose an initial set of analysis that should in it be included. We finally review some challenges and open issues, including how security and privacy could be tackled by emerging new technologies.
Murguia, Carlos, Tabuada, Paulo.  2020.  Privacy Against Adversarial Classification in Cyber-Physical Systems. 2020 59th IEEE Conference on Decision and Control (CDC). :5483–5488.
For a class of Cyber-Physical Systems (CPSs), we address the problem of performing computations over the cloud without revealing private information about the structure and operation of the system. We model CPSs as a collection of input-output dynamical systems (the system operation modes). Depending on the mode the system is operating on, the output trajectory is generated by one of these systems in response to driving inputs. Output measurements and driving inputs are sent to the cloud for processing purposes. We capture this "processing" through some function (of the input-output trajectory) that we require the cloud to compute accurately - referred here as the trajectory utility. However, for privacy reasons, we would like to keep the mode private, i.e., we do not want the cloud to correctly identify what mode of the CPS produced a given trajectory. To this end, we distort trajectories before transmission and send the corrupted data to the cloud. We provide mathematical tools (based on output-regulation techniques) to properly design distorting mechanisms so that: 1) the original and distorted trajectories lead to the same utility; and the distorted data leads the cloud to misclassify the mode.
Dodson, Michael, Beresford, Alastair R., Richardson, Alexander, Clarke, Jessica, Watson, Robert N. M..  2020.  CHERI Macaroons: Efficient, host-based access control for cyber-physical systems. 2020 IEEE European Symposium on Security and Privacy Workshops (EuroS PW). :688–693.
Cyber-Physical Systems (CPS) often rely on network boundary defence as a primary means of access control; therefore, the compromise of one device threatens the security of all devices within the boundary. Resource and real-time constraints, tight hardware/software coupling, and decades-long service lifetimes complicate efforts for more robust, host-based access control mechanisms. Distributed capability systems provide opportunities for restoring access control to resource-owning devices; however, such a protection model requires a capability-based architecture for CPS devices as well as task compartmentalisation to be effective.This paper demonstrates hardware enforcement of network bearer tokens using an efficient translation between CHERI (Capability Hardware Enhanced RISC Instructions) architectural capabilities and Macaroon network tokens. While this method appears to generalise to any network-based access control problem, we specifically consider CPS, as our method is well-suited for controlling resources in the physical domain. We demonstrate the method in a distributed robotics application and in a hierarchical industrial control application, and discuss our plans to evaluate and extend the method.
Ouchani, Samir, Khebbeb, Khaled, Hafsi, Meriem.  2020.  Towards Enhancing Security and Resilience in CPS: A Coq-Maude based Approach. 2020 IEEE/ACS 17th International Conference on Computer Systems and Applications (AICCSA). :1—6.
Cyber-Physical Systems (CPS) have gained considerable interest in the last decade from both industry and academia. Such systems have proven particularly complex and provide considerable challenges to master their design and ensure their functionalities. In this paper, we intend to tackle some of these challenges related to the security and the resilience of CPS at the design level. We initiate a CPS modeling approach to specify such systems structure and behaviors, analyze their inherent properties and to overcome threats in terms of security and correctness. In this initiative, we consider a CPS as a network of entities that communicate through physical and logical channels, and which purpose is to achieve a set of tasks expressed as an ordered tree. Our modeling approach proposes a combination of the Coq theorem prover and the Maude rewriting system to ensure the soundness and correctness of CPS design. The introduced solution is illustrated through an automobile manufacturing case study.
Ravikumar, Gelli, Hyder, Burhan, Govindarasu, Manimaran.  2020.  Next-Generation CPS Testbed-based Grid Exercise - Synthetic Grid, Attack, and Defense Modeling. 2020 Resilience Week (RWS). :92—98.
Quasi-Realistic cyber-physical system (QR-CPS) testbed architecture and operational environment are critical for testing and validating various cyber attack-defense algorithms for the wide-area resilient power systems. These QR-CPS testbed environments provide a realistic platform for conducting the Grid Exercise (GridEx), CPS security training, and attack-defense exercise at a broader scale for the cybersecurity of Energy Delivery Systems. The NERC has established a tabletop based GridEx platform for the North American power utilities to demonstrate how they would respond to and recover from cyber threats and incidents. The NERC-GridEx is a bi-annual activity with tabletop attack injects and incidence response management. There is a significant need to build a testbed-based hands-on GridEx for the utilities by leveraging the CPS testbeds, which imitates the pragmatic CPS grid environment. We propose a CPS testbed-based Quasi-Realistic Grid Exercise (QR-GridEx), which is a model after the NERC's tabletop GridEx. We have designed the CPS testbed-based QR-GridEx into two parts. Part-I focuses on the modeling of synthetic grid models for the utilities, including SCADA and WAMS communications, and attack-and-defense software systems; and the Part-II focuses on the incident response management and risk-based CPS grid investment strategies. This paper presents the Part-I of the CPS testbed-based QRGridEx, which includes modeling of the synthetic grid models in the real-time digital simulator, stealthy, and coordinated cyberattack vectors, and integration of intrusion/anomaly detection systems. We have used our existing HIL CPS security testbed to demonstrate the testbed-based QR-GridEx for a Texas-2000 bus US synthetic grid model and the IEEE-39 bus grid models. The experiments demonstrated significant results by 100% real-time performance with zero overruns for grid impact characteristics against stealthy and coordinated cyberattack vectors.
Bosio, Alberto, Canal, Ramon, Di Carlo, Stefano, Gizopoulos, Dimitris, Savino, Alessandro.  2020.  Cross-Layer Soft-Error Resilience Analysis of Computing Systems. 2020 50th Annual IEEE-IFIP International Conference on Dependable Systems and Networks-Supplemental Volume (DSN-S). :79—79.
In a world with computation at the epicenter of every activity, computing systems must be highly resilient to errors even if miniaturization makes the underlying hardware unreliable. Techniques able to guarantee high reliability are associated to high costs. Early resilience analysis has the potential to support informed design decisions to maximize system-level reliability while minimizing the associated costs. This tutorial focuses on early cross-layer (hardware and software) resilience analysis considering the full computing continuum (from IoT/CPS to HPC applications) with emphasis on soft errors.
Barbeau, Michel, Cuppens, Frédéric, Cuppens, Nora, Dagnas, Romain, Garcia-Alfaro, Joaquin.  2020.  Metrics to Enhance the Resilience of Cyber-Physical Systems. 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom). :1167—1172.
We focus on resilience towards covert attacks on Cyber-Physical Systems (CPS). We define the new k-steerability and l-monitorability control-theoretic concepts. k-steerability reflects the ability to act on every individual plant state variable with at least k different groups of functionally diverse input signals. l-monitorability indicates the ability to monitor every individual plant state variable with £ different groups of functionally diverse output signals. A CPS with k-steerability and l-monitorability is said to be (k, l)-resilient. k and l, when both greater than one, provide the capability to mitigate the impact of covert attacks when some signals, but not all, are compromised. We analyze the influence of k and l on the resilience of a system and the ability to recover its state when attacks are perpetrated. We argue that the values of k and l can be augmented by combining redundancy and diversity in hardware and software techniques that apply the moving target paradigm.
Hopkins, Stephen, Kalaimannan, Ezhil, John, Caroline Sangeetha.  2020.  Cyber Resilience using State Estimation Updates Based on Cyber Attack Matrix Classification. 2020 IEEE Kansas Power and Energy Conference (KPEC). :1—6.
Cyber-physical systems (CPS) maintain operation, reliability, and safety performance using state estimation and control methods. Internet connectivity and Internet of Things (IoT) devices are integrated with CPS, such as in smart grids. This integration of Operational Technology (OT) and Information Technology (IT) brings with it challenges for state estimation and exposure to cyber-threats. This research establishes a state estimation baseline, details the integration of IT, evaluates the vulnerabilities, and develops an approach for detecting and responding to cyber-attack data injections. Where other approaches focus on integration of IT cyber-controls, this research focuses on development of classification tools using data currently available in state estimation methods to quantitatively determine the presence of cyber-attack data. The tools may increase computational requirements but provide methods which can be integrated with existing state estimation methods and provide for future research in state estimation based cyber-attack incident response. A robust cyber-resilient CPS includes the ability to detect and classify a cyber-attack, determine the true system state, and respond to the cyber-attack. The purpose of this paper is to establish a means for a cyber aware state estimator given the existence of sub-erroneous outlier detection, cyber-attack data weighting, cyber-attack data classification, and state estimation cyber detection.
Nazemi, Mostafa, Dehghanian, Payman, Alhazmi, Mohannad, Wang, Fei.  2020.  Multivariate Uncertainty Characterization for Resilience Planning in Electric Power Systems. 2020 IEEE/IAS 56th Industrial and Commercial Power Systems Technical Conference (I CPS). :1—8.
Following substantial advancements in stochastic classes of decision-making optimization problems, scenario-based stochastic optimization, robust\textbackslashtextbackslash distributionally robust optimization, and chance-constrained optimization have recently gained an increasing attention. Despite the remarkable developments in probabilistic forecast of uncertainties (e.g., in renewable energies), most approaches are still being employed in a univariate framework which fails to unlock a full understanding on the underlying interdependence among uncertain variables of interest. In order to yield cost-optimal solutions with predefined probabilistic guarantees, conditional and dynamic interdependence in uncertainty forecasts should be accommodated in power systems decision-making. This becomes even more important during the emergencies where high-impact low-probability (HILP) disasters result in remarkable fluctuations in the uncertain variables. In order to model the interdependence correlation structure between different sources of uncertainty in power systems during both normal and emergency operating conditions, this paper aims to bridge the gap between the probabilistic forecasting methods and advanced optimization paradigms; in particular, perdition regions are generated in the form of ellipsoids with probabilistic guarantees. We employ a modified Khachiyan's algorithm to compute the minimum volume enclosing ellipsoids (MVEE). Application results based on two datasets on wind and photovoltaic power are used to verify the efficiency of the proposed framework.
Segovia, Mariana, Rubio-Hernan, Jose, Cavalli, Ana R., Garcia-Alfaro, Joaquin.  2020.  Cyber-Resilience Evaluation of Cyber-Physical Systems. 2020 IEEE 19th International Symposium on Network Computing and Applications (NCA). :1—8.
Cyber-Physical Systems (CPS) use computational resources to control physical processes and provide critical services. For this reason, an attack in these systems may have dangerous consequences in the physical world. Hence, cyber- resilience is a fundamental property to ensure the safety of the people, the environment and the controlled physical processes. In this paper, we present metrics to quantify the cyber-resilience level based on the design, structure, stability, and performance under the attack of a given CPS. The metrics provide reference points to evaluate whether the system is better prepared or not to face the adversaries. This way, it is possible to quantify the ability to recover from an adversary using its mathematical model based on actuators saturation. Finally, we validate our approach using a numeric simulation on the Tennessee Eastman control challenge problem.