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2021-10-12
Jayabalan, Manoj.  2020.  Towards an Approach of Risk Analysis in Access Control. 2020 13th International Conference on Developments in eSystems Engineering (DeSE). :287–292.
Information security provides a set of mechanisms to be implemented in the organisation to protect the disclosure of data to the unauthorised person. Access control is the primary security component that allows the user to authorise the consumption of resources and data based on the predefined permissions. However, the access rules are static in nature, which does not adapt to the dynamic environment includes but not limited to healthcare, cloud computing, IoT, National Security and Intelligence Arena and multi-centric system. There is a need for an additional countermeasure in access decision that can adapt to those working conditions to assess the threats and to ensure privacy and security are maintained. Risk analysis is an act of measuring the threats to the system through various means such as, analysing the user behaviour, evaluating the user trust, and security policies. It is a modular component that can be integrated into the existing access control to predict the risk. This study presents the different techniques and approaches applied for risk analysis in access control. Based on the insights gained, this paper formulates the taxonomy of risk analysis and properties that will allow researchers to focus on areas that need to be improved and new features that could be beneficial to stakeholders.
Adibi, Mahya, van der Woude, Jacob.  2020.  Distributed Learning Control for Economic Power Dispatch: A Privacy Preserved Approach*. 2020 IEEE 29th International Symposium on Industrial Electronics (ISIE). :821–826.
We present a privacy-preserving distributed reinforcement learning-based control scheme to address the problem of frequency control and economic dispatch in power generation systems. The proposed control approach requires neither a priori system model knowledge nor the mathematical formulation of the generation cost functions. Due to not requiring the generation cost models, the control scheme is capable of dealing with scenarios in which the cost functions are hard to formulate and/or non-convex. Furthermore, it is privacy-preserving, i.e. none of the units in the network needs to communicate its cost function and/or control policy to its neighbors. To realize this, we propose an actor-critic algorithm with function approximation in which the actor step is performed individually by each unit with no need to infer the policies of others. Moreover, in the critic step each generation unit shares its estimate of the local measurements and the estimate of its cost function with the neighbors, and via performing a consensus algorithm, a consensual estimate is achieved. The performance of our proposed control scheme, in terms of minimizing the overall cost while persistently fulfilling the demand and fast reaction and convergence of our distributed algorithm, is demonstrated on a benchmark case study.
Ferraro, Angelo.  2020.  When AI Gossips. 2020 IEEE International Symposium on Technology and Society (ISTAS). :69–71.
The concept of AI Gossip is presented. It is analogous to the traditional understanding of a pernicious human failing. It is made more egregious by the technology of AI, internet, current privacy policies, and practices. The recognition by the technological community of its complacency is critical to realizing its damaging influence on human rights. A current example from the medical field is provided to facilitate the discussion and illustrate the seriousness of AI Gossip. Further study and model development is encouraged to support and facilitate the need to develop standards to address the implications and consequences to human rights and dignity.
Zhou, Yimin, Zhang, Kai.  2020.  DoS Vulnerability Verification of IPSec VPN. 2020 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA). :698–702.
This paper analyzes the vulnerability in the process of key negotiation between the main mode and aggressive mode of IKEv1 protocol in IPSec VPN, and proposes a DOS attack method based on OSPF protocol adjacent route spoofing. The experiment verifies the insecurity of IPSec VPN using IKEv1 protocol. This attack method has the advantages of lower cost and easier operation compared with using botnet.
Vinarskii, Evgenii, Demakov, Alexey, Kamkin, Alexander, Yevtushenko, Nina.  2020.  Verifying cryptographic protocols by Tamarin Prover. 2020 Ivannikov Memorial Workshop (IVMEM). :69–75.
Cryptographic protocols are utilized for establishing a secure session between “honest” agents which communicate strictly according to the protocol rules as well as for ensuring the authenticated and confidential transmission of messages. The specification of a cryptographic protocol is usually presented as a set of requirements for the sequences of transmitted messages including the format of such messages. Note that protocol can describe several execution scenarios. All these requirements lead to a huge formal specification for a real cryptographic protocol and therefore, it is difficult to verify the security of the whole cryptographic protocol at once. In this paper, to overcome this problem, we suggest verifying the protocol security for its fragments. Namely, we verify the security properties for a special set of so-called traces of the cryptographic protocol. Intuitively, a trace of the cryptographic protocol is a sequence of computations, value checks, and transmissions on the sides of “honest” agents permitted by the protocol. In order to choose such set of traces, we introduce an Adversary model and the notion of a similarity relation for traces. We then verify the security properties of selected traces with Tamarin Prover. Experimental results for the EAP and Noise protocols clearly show that this approach can be promising for automatic verification of large protocols.
Hassan, Mehmood, Sultan, Aiman, Awan, Ali Afzal, Tahir, Shahzaib, Ihsan, Imran.  2020.  An Enhanced and Secure Multiserver-based User Authentication Protocol. 2020 International Conference on Cyber Warfare and Security (ICCWS). :1–6.
The extensive use of the internet and web-based applications spot the multiserver authentication as a significant component. The users can get their services after authenticating with the service provider by using similar registration records. Various protocol schemes are developed for multiserver authentication, but the existing schemes are not secure and often lead towards various vulnerabilities and different security issues. Recently, Zhao et al. put forward a proposal for smart card and user's password-based authentication protocol for the multiserver environment and showed that their proposed protocol is efficient and secure against various security attacks. This paper points out that Zhao et al.'s authentication scheme is susceptive to traceability as well as anonymity attacks. Thus, it is not feasible for the multiserver environment. Furthermore, in their scheme, it is observed that a user while authenticating does not send any information with any mention of specific server identity. Therefore, this paper proposes an enhanced, efficient and secure user authentication scheme for use in any multiserver environment. The formal security analysis and verification of the protocol is performed using state-of-the-art tool “ProVerif” yielding that the proposed scheme provides higher levels of security.
Kai, Wang, Wei, Li, Tao, Chen, Longmei, Nan.  2020.  Research on Secure JTAG Debugging Model Based on Schnorr Identity Authentication Protocol. 2020 IEEE 15th International Conference on Solid-State Integrated Circuit Technology (ICSICT). :1–3.
As a general interface for chip system testing and on-chip debugging, JTAG is facing serious security threats. By analyzing the typical JTAG attack model and security protection measures, this paper designs a secure JTAG debugging model based on Schnorr identity authentication protocol, and takes RISCV as an example to build a set of SoC prototype system to complete functional verification. Experiments show that this secure JTAG debugging model has high security, flexible implementation, and good portability. It can meet the JTAG security protection requirements in various application scenarios. The maximum clock frequency can reach 833MHZ, while the hardware overhead is only 47.93KGate.
Li, Yongjian, Cao, Taifeng, Jansen, David N., Pang, Jun, Wei, Xiaotao.  2020.  Accelerated Verification of Parametric Protocols with Decision Trees. 2020 IEEE 38th International Conference on Computer Design (ICCD). :397–404.
Within a framework for verifying parametric network protocols through induction, one needs to find invariants based on a protocol instance of a small number of nodes. In this paper, we propose a new approach to accelerate parameterized verification by adopting decision trees to represent the state space of a protocol instance. Such trees can be considered as a knowledge base that summarizes all behaviors of the protocol instance. With this knowledge base, we are able to efficiently construct an oracle to effectively assess candidates of invariants of the protocol, which are suggested by an invariant finder. With the discovered invariants, a formal proof for the correctness of the protocol can be derived in the framework after proper generalization. The effectiveness of our method is demonstrated by experiments with typical benchmarks.
He, Leifeng, Liu, Guanjun.  2020.  Petri Nets Based Verification of Epistemic Logic and Its Application on Protocols of Privacy and Security. 2020 IEEE World Congress on Services (SERVICES). :25–28.
Epistemic logic can specify many design requirements of privacy and security of multi-agent systems (MAS). The existing model checkers of epistemic logic use some programming languages to describe MAS, induce Kripke models as the behavioral representation of MAS, apply Ordered Binary Decision Diagrams (OBDD) to encode Kripke models to solve their state explosion problem and verify epistemic logic based on the encoded Kripke models. However, these programming languages are usually non-intuitive. More seriously, their OBDD-based model checking processes are often time-consuming due to their dynamic variable ordering for OBDD. Therefore, we define Knowledge-oriented Petri Nets (KPN) to intuitively describe MAS, induce similar reachability graphs as the behavioral representation of KPN, apply OBDD to encode all reachable states, and finally verify epistemic logic. Although we also use OBDD, we adopt a heuristic method for the computation of a static variable order instead of dynamic variable ordering. More importantly, while verifying an epistemic formula, we dynamically generate its needed similar relations, which makes our model checking process much more efficient. In this paper, we introduce our work.
Remlein, Piotr, Rogacki, Mikołaj, Stachowiak, Urszula.  2020.  Tamarin software – the tool for protocols verification security. 2020 Baltic URSI Symposium (URSI). :118–123.
In order to develop safety-reliable standards for IoT (Internet of Things) networks, appropriate tools for their verification are needed. Among them there is a group of tools based on automated symbolic analysis. Such a tool is Tamarin software. Its usage for creating formal proofs of security protocols correctness has been presented in this paper using the simple example of an exchange of messages with asynchronous encryption between two agents. This model can be used in sensor networks or IoT e.g. in TLS protocol to provide a mechanism for secure cryptographic key exchange.
Naveed, Sarah, Sultan, Aiman, Mansoor, Khwaja.  2020.  An Enhanced SIP Authentication Protocol for Preserving User Privacy. 2020 International Conference on Cyber Warfare and Security (ICCWS). :1–6.
Owing to the advancements in communication media and devices all over the globe, there has arisen a dire need for to limit the alarming number of attacks targeting these and to enhance their security. Multiple techniques have been incorporated in different researches and various protocols and schemes have been put forward to cater security issues of session initiation protocol (SIP). In 2008, Qiu et al. presented a proposal for SIP authentication which while effective than many existing schemes, was still found vulnerable to many security attacks. To overcome those issues, Zhang et al. proposed an authentication protocol. This paper presents the analysis of Zhang et al. authentication scheme and concludes that their proposed scheme is susceptible to user traceablity. It also presents an improved SIP authentication scheme that eliminates the possibility of traceability of user's activities. The proposed scheme is also verified by contemporary verification tool, ProVerif and it is found to be more secure, efficient and practical than many similar SIP authetication scheme.
Chang, Kai Chih, Nokhbeh Zaeem, Razieh, Barber, K. Suzanne.  2020.  Is Your Phone You? How Privacy Policies of Mobile Apps Allow the Use of Your Personally Identifiable Information 2020 Second IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA). :256–262.
People continue to store their sensitive information in their smart-phone applications. Users seldom read an app's privacy policy to see how their information is being collected, used, and shared. In this paper, using a reference list of over 600 Personally Identifiable Information (PII) attributes, we investigate the privacy policies of 100 popular health and fitness mobile applications in both Android and iOS app markets to find the set of personal information these apps collect, use and share. The reference list of PII was independently built from a longitudinal study at The University of Texas investigating thousands of identity theft and fraud cases where PII attributes and associated value and risks were empirically quantified. This research leverages the reference PII list to identify and analyze the value of personal information collected by the mobile apps and the risk of disclosing this information. We found that the set of PII collected by these mobile apps covers 35% of the entire reference set of PII and, due to dependencies between PII attributes, these mobile apps have a likelihood of indirectly impacting 70% of the reference PII if breached. For a specific app, we discovered the monetary loss could reach \$1M if the set of sensitive data it collects is breached. We finally utilize Bayesian inference to measure risks of a set of PII gathered by apps: the probability that fraudsters can discover, impersonate and cause harm to the user by misusing only the PII the mobile apps collected.
Liao, Guocheng, Chen, Xu, Huang, Jianwei.  2020.  Privacy Policy in Online Social Network with Targeted Advertising Business. IEEE INFOCOM 2020 - IEEE Conference on Computer Communications. :934–943.
In an online social network, users exhibit personal information to enjoy social interaction. The social network provider (SNP) exploits users' information for revenue generation through targeted advertising. The SNP can present ads to proper users efficiently. Therefore, an advertiser is more willing to pay for targeted advertising. However, the over-exploitation of users' information would invade users' privacy, which would negatively impact users' social activeness. Motivated by this, we study the optimal privacy policy of the SNP with targeted advertising business. We characterize the privacy policy in terms of the fraction of users' information that the provider should exploit, and formulate the interactions among users, advertiser, and SNP as a three-stage Stackelberg game. By carefully leveraging supermodularity property, we reveal from the equilibrium analysis that higher information exploitation will discourage users from exhibiting information, lowering the overall amount of exploited information and harming advertising revenue. We further characterize the optimal privacy policy based on the connection between users' information levels and privacy policy. Numerical results reveal some useful insights that the optimal policy can well balance the users' trade-off between social benefit and privacy loss.
Faurie, Pascal, Moldovan, Arghir-Nicolae, Tal, Irina.  2020.  Privacy Policy – ``I Agree''⁈ – Do Alternatives to Text-Based Policies Increase the Awareness of the Users? 2020 International Conference on Cyber Security and Protection of Digital Services (Cyber Security). :1–6.
Since GDPR was introduced, there is a reinforcement of the fact that users must give their consent before their personal data can be managed by any website. However, many studies have demonstrated that users often skip these policies and click the "I agree" button to continue browsing, being unaware of what the consent they gave was about, hence defeating the purpose of GDPR. This paper investigates if different ways of presenting users the privacy policy can change this behaviour and can lead to an increased awareness of the user in relation to what the user agrees with. Three different types of policies were used in the study: a full-text policy, a so-called usable policy, and a video-based policy. Results demonstrated that the type of policy has a direct influence on the user awareness and user satisfaction. The two alternatives to the text-based policy lead to a significant increase of user awareness in relation to the content of the policy and to a significant increase in the user satisfaction in relation to the usability of the policy.
Farooq, Emmen, Nawaz UI Ghani, M. Ahmad, Naseer, Zuhaib, Iqbal, Shaukat.  2020.  Privacy Policies' Readability Analysis of Contemporary Free Healthcare Apps. 2020 14th International Conference on Open Source Systems and Technologies (ICOSST). :1–7.
mHealth apps have a vital role in facilitation of human health management. Users have to enter sensitive health related information in these apps to fully utilize their functionality. Unauthorized sharing of sensitive health information is undesirable by the users. mHealth apps also collect data other than that required for their functionality like surfing behavior of a user or hardware details of devices used. mHealth software and their developers also share such data with third parties for reasons other than medical support provision to the user, like advertisements of medicine and health insurance plans. Existence of a comprehensive and easy to understand data privacy policy, on user data acquisition, sharing and management is a salient requirement of modern user privacy protection demands. Readability is one parameter by which ease of understanding of privacy policy is determined. In this research, privacy policies of 27 free Android, medical apps are analyzed. Apps having user rating of 4.0 and downloads of 1 Million or more are included in data set of this research.RGL, Flesch-Kincaid Reading Grade Level, SMOG, Gunning Fox, Word Count, and Flesch Reading Ease of privacy policies are calculated. Average Reading Grade Level of privacy policies is 8.5. It is slightly greater than average adult RGL in the US. Free mHealth apps have a large number of users in other, less educated parts of the World. Privacy policies with an average RGL of 8.5 may be difficult to comprehend in less educated populations.
Al Omar, Abdullah, Jamil, Abu Kaisar, Nur, Md. Shakhawath Hossain, Hasan, Md Mahamudul, Bosri, Rabeya, Bhuiyan, Md Zakirul Alam, Rahman, Mohammad Shahriar.  2020.  Towards A Transparent and Privacy-Preserving Healthcare Platform with Blockchain for Smart Cities. 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom). :1291–1296.
In smart cities, data privacy and security issues of Electronic Health Record(EHR) are grabbing importance day by day as cyber attackers have identified the weaknesses of EHR platforms. Besides, health insurance companies interacting with the EHRs play a vital role in covering the whole or a part of the financial risks of a patient. Insurance companies have specific policies for which patients have to pay them. Sometimes the insurance policies can be altered by fraudulent entities. Another problem that patients face in smart cities is when they interact with a health organization, insurance company, or others, they have to prove their identity to each of the organizations/companies separately. Health organizations or insurance companies have to ensure they know with whom they are interacting. To build a platform where a patient's personal information and insurance policy are handled securely, we introduce an application of blockchain to solve the above-mentioned issues. In this paper, we present a solution for the healthcare system that will provide patient privacy and transparency towards the insurance policies incorporating blockchain. Privacy of the patient information will be provided using cryptographic tools.
Martiny, Karsten, Denker, Grit.  2020.  Partial Decision Overrides in a Declarative Policy Framework. 2020 IEEE 14th International Conference on Semantic Computing (ICSC). :271–278.
The ability to specify various policies with different overriding criteria allows for complex sets of sharing policies. This is particularly useful in situations in which data privacy depends on various properties of the data, and complex policies are needed to express the conditions under which data is protected. However, if overriding policy decisions constrain the affected data, decisions from overridden policies should not be suppressed completely, because they can still apply to subsets of the affected data. This article describes how a privacy policy framework can be extended with a mechanism to partially override decisions based on specified constraints. Our solution automatically generates complementary sets of decisions for both the overridden and the complementary, non-overridden subsets of the data, and thus, provides a means to specify a complex policies tailored to specific properties of the protected data.
Zaeem, Razieh Nokhbeh, Anya, Safa, Issa, Alex, Nimergood, Jake, Rogers, Isabelle, Shah, Vinay, Srivastava, Ayush, Barber, K. Suzanne.  2020.  PrivacyCheck's Machine Learning to Digest Privacy Policies: Competitor Analysis and Usage Patterns. 2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT). :291–298.
Online privacy policies are lengthy and hard to comprehend. To address this problem, researchers have utilized machine learning (ML) to devise tools that automatically summarize online privacy policies for web users. One such tool is our free and publicly available browser extension, PrivacyCheck. In this paper, we enhance PrivacyCheck by adding a competitor analysis component-a part of PrivacyCheck that recommends other organizations in the same market sector with better privacy policies. We also monitored the usage patterns of about a thousand actual PrivacyCheck users, the first work to track the usage and traffic of an ML-based privacy analysis tool. Results show: (1) there is a good number of privacy policy URLs checked repeatedly by the user base; (2) the users are particularly interested in privacy policies of software services; and (3) PrivacyCheck increased the number of times a user consults privacy policies by 80%. Our work demonstrates the potential of ML-based privacy analysis tools and also sheds light on how these tools are used in practice to give users actionable knowledge they can use to pro-actively protect their privacy.
Tavakolan, Mona, Faridi, Ismaeel A..  2020.  Applying Privacy-Aware Policies in IoT Devices Using Privacy Metrics. 2020 International Conference on Communications, Computing, Cybersecurity, and Informatics (CCCI). :1–5.
In recent years, user's privacy has become an important aspect in the development of Internet of Things (IoT) devices. However, there has been comparatively little research so far that aims to understanding user's privacy in connection with IoT. Many users are worried about protecting their personal information, which may be gathered by IoT devices. In this paper, we present a new method for applying the user's preferences within the privacy-aware policies in IoT devices. Users can prioritize a set of extendable privacy policies based on their preferences. This is achieved by assigning weights to these policies to form ranking criteria. A privacy-aware index is then calculated based on these ranking. In addition, IoT devices can be clustered based on their privacy-aware index value. In this paper, we present a new method for applying the user's preferences within the privacy-aware policies in IoT devices. Users can prioritize a set of extendable privacy policies based on their preferences. This is achieved by assigning weights to these policies to form ranking criteria. A privacy-aware index is then calculated based on these ranking. In addition, IoT devices can be clustered based on their privacy-aware index value.
Onu, Emmanuel, Mireku Kwakye, Michael, Barker, Ken.  2020.  Contextual Privacy Policy Modeling in IoT. 2020 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech). :94–102.
The Internet of Things (IoT) has been one of the biggest revelations of the last decade. These cyber-physical systems seamlessly integrate and improve the activities in our daily lives. Hence, creating a wide application for it in several domains, such as smart buildings and cities. However, the integration of IoT also comes with privacy challenges. The privacy challenges result from the ability of these devices to pervasively collect personal data about individuals through sensors in ways that could be unknown to them. A number of research efforts have evaluated privacy policy awareness and enforcement as key components for addressing these privacy challenges. This paper provides a framework for understanding contextualized privacy policy within the IoT domain. This will enable IoT privacy researchers to better understand IoT privacy policies and their modeling.
2021-10-04
Mohiuddin, Irfan, Almogren, Ahmad.  2020.  Security Challenges and Strategies for the IoT in Cloud Computing. 2020 11th International Conference on Information and Communication Systems (ICICS). :367–372.
The Internet of Things is progressively turning into a pervasive computing service, needing enormous volumes of data storage and processing. However, due to the distinctive properties of resource constraints, self-organization, and short-range communication in Internet of Things (IoT), it always adopts to cloud for outsourced storage and computation. This integration of IoT with cloud has a row of unfamiliar security challenges for the data at rest. Cloud computing delivers highly scalable and flexible computing and storage resources on pay-per-use policy. Cloud computing services for computation and storage are getting increasingly popular and many organizations are now moving their data from in-house data centers to the Cloud Storage Providers (CSPs). Time varying workload and data intensive IoT applications are vulnerable to encounter challenges while using cloud computing services. Additionally, the encryption techniques and third-party auditors to maintain data integrity are still in their developing stage and therefore the data at rest is still a concern for IoT applications. In this paper, we perform an analysis study to investigate the challenges and strategies adapted by Cloud Computing to facilitate a safe transition of IoT applications to the Cloud.
Qu, Dapeng, Zhang, Jiankun, Hou, Zhenhuan, Wang, Min, Dong, Bo.  2020.  A Trust Routing Scheme Based on Identification of Non-complete Cooperative Nodes in Mobile Peer-to-Peer Networks. 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom). :22–29.
Mobile peer-to-peer network (MP2P) attracts increasing attentions due to the ubiquitous use of mobile communication and huge success of peer-to-peer (P2P) mode. However, open p2p mode makes nodes tend to be selfish, and the scarcity of resources in mobile nodes aggravates this problem, thus the nodes easily express a non-complete cooperative (NCC) attitude. Therefore, an identification of non-complete cooperative nodes and a corresponding trust routing scheme are proposed for MP2P in this paper. The concept of octant is firstly introduced to build a trust model which analyzes nodes from three dimensions, namely direct trust, internal state and recommendation reliability, and then the individual non-complete cooperative (INCC) nodes can be identified by the division of different octants. The direct trust monitors nodes' external behaviors, and the consideration of internal state and recommendation reliability contributes to differentiate the subjective and objective non-cooperation, and mitigate the attacks about direct trust values respectively. Thus, the trust model can identify various INCC nodes accurately. On the basis of identification of INCC nodes, cosine similarity method is applied to identify collusive non-complete cooperate (CNCC) nodes. Moreover, a trust routing scheme based on the identification of NCC nodes is presented to reasonably deal with different kinds of NCC nodes. Results from extensive simulation experiments demonstrate that this proposed identification and routing scheme have better performances, in terms of identification precision and packet delivery fraction than current schemes respectively.
LAPIQUE, Maxime, GAVAGSAZ-GHOACHANI, Roghayeh, MARTIN, Jean-Philippe, PIERFEDERICI, Serge, ZAIM, Sami.  2020.  Flatness-based control of a 3-phases PWM rectifier with LCL-filter amp; disturbance observer. IECON 2020 The 46th Annual Conference of the IEEE Industrial Electronics Society. :4685–4690.
In more electrical aircraft, the embedded electrical network is handling more and more vital functions, being more and more strained as well. Attenuation of switching harmonics is a key step in the network reliability, thus filtering elements play a central role. To keep the weight of the embedded network reasonable, weakly damped high-order filters shall be preferred. Flatness-based control (FBC) can offer both high bandwidth regulation and large signal stability proof. This make FBC a good candidate to handle the inherent oscillating behavior of aforementioned filters. However, this control strategy can be tricky to implement, especially with high order systems. Moreover, FBC is more sensor demanding than classic PI-based control. This paper address these two drawbacks. First, a novel trajectory planning for high order systems is proposed. This method does not require multiple derivations. Then the input sensors are removed thanks to a parameters estimator. Feasibility and performances are verified with experimental results. Performances comparison with cascaded-loop topologies are given in final section to prove the relevance of the proposed control strategy.
Pilehvar, Mohsen S., Mirafzal, Behrooz.  2020.  Energy-Storage Fed Smart Inverters for Mitigation of Voltage Fluctuations in Islanded Microgrids. 2020 IEEE Electric Power and Energy Conference (EPEC). :1–6.
The continuous integration of intermittent low-carbon energy resources makes islanded microgrids vulnerable to voltage fluctuations. Besides, different dynamic response of synchronous-based and inverter-based distributed generation (DG) units can result in an instantaneous power imbalance between supply and demand during transients. As a result, the ac-bus voltage of microgrid starts oscillating which might have severe consequences such as blackouts. This paper modifies the conventional control scheme of battery energy storage systems (BESSs) to participate in improving the dynamic behavior of islanded microgrids by mitigating the voltage fluctuations. A piecewise linear-elliptic (PLE) droop is proposed and employed in BESS to achieve an enhanced voltage profile by injecting/absorbing reactive power during transients. In this way, the conventional inverter implemented in BESS turns into a smart inverter to cope with fast transients. Using the proposed approach in this paper, any linear droop curve with a specified coefficient can be replaced by a PLE droop curve. Compared with linear droop, an enhanced dynamic response is achieved by utilizing the proposed PLE droop. Case study results are presented using PSCAD/EMTDC to demonstrate the superiority of the proposed approach in improving the dynamic behavior of islanded microgrids.
Jha, Prabhat Kumar, Prajapat, Ganesh P., Bansal, S. K., Solanki, Urmila.  2020.  Mode Identification and Small Signal Stability Analysis of Variable Speed Wind Power Systems. 2020 International Conference on Power Electronics IoT Applications in Renewable Energy and its Control (PARC). :286–291.
The high penetration of wind power generation into the grid evokes all the concerns for the deep understanding of its behavior and impact on the existing power system. This paper investigates the optimal operation of the Doubly Fed Induction Generator (DFIG) for the maximum power point tracking in deep with modal analysis. The grid connected DFIG system has been examined in two cases viz. open-loop case and closed-loop case where closed-loop case consists the system with the Flux Magnitude Angle Control (FMAC) and Direct Torque Control (DTC) approach. Various modes of the oscillation and their damping factor has been found in both the cases for the examination of the internal behavior of the system. Further, the effectiveness of the all the employed controls along with MPPT when the system is subjected to a stepped wind speed disturbance and voltage-dip have been confirmed. It was found from the simulation and the modal analysis that the frequency of the various oscillating modes is lesser while the damping is improved in the case of DTC control.