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Alshinina, Remah, Elleithy, Khaled.  2018.  A highly accurate machine learning approach for developing wireless sensor network middleware. 2018 Wireless Telecommunications Symposium (WTS). :1–7.
Despite the popularity of wireless sensor networks (WSNs) in a wide range of applications, security problems associated with them have not been completely resolved. Middleware is generally introduced as an intermediate layer between WSNs and the end user to resolve some limitations, but most of the existing middleware is unable to protect data from malicious and unknown attacks during transmission. This paper introduces an intelligent middleware based on an unsupervised learning technique called Generative Adversarial Networks (GANs) algorithm. GANs contain two networks: a generator (G) network and a detector (D) network. The G creates fake data similar to the real samples and combines it with real data from the sensors to confuse the attacker. The D contains multi-layers that have the ability to differentiate between real and fake data. The output intended for this algorithm shows an actual interpretation of the data that is securely communicated through the WSN. The framework is implemented in Python with experiments performed using Keras. Results illustrate that the suggested algorithm not only improves the accuracy of the data but also enhances its security by protecting data from adversaries. Data transmission from the WSN to the end user then becomes much more secure and accurate compared to conventional techniques.
Kosmyna, Nataliya.  2019.  Brain-Computer Interfaces in the Wild: Lessons Learned from a Large-Scale Deployment. 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC). :4161–4168.
We present data from detailed observations of a “controlled in-the-wild” study of Brain-Computer Interface (BCI) system. During 10 days of demonstration at seven nonspecialized public events, 1563 people learned about the system in various social configurations. Observations of audience behavior revealed recurring behavioral patterns. From these observations a framework of interaction with BCI systems was deduced. It describes the phases of passing by an installation, viewing and reacting, passive and active interaction, group interactions, and follow-up actions. We also conducted semi-structured interviews with the people who interacted with the system. The interviews revealed the barriers and several directions for further research on BCIs. Our findings can be useful for designing the BCIs foxr everyday adoption by a wide range of people.
Sahay, Rashmi, Geethakumari, G., Mitra, Barsha, Thejas, V..  2018.  Exponential Smoothing based Approach for Detection of Blackhole Attacks in IoT. 2018 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS). :1–6.
Low power and lossy network (LLN) comprising of constrained devices like sensors and RFIDs, is a major component in the Internet of Things (IoT) environment as these devices provide global connectivity to physical devices or “Things”. LLNs are tied to the Internet or any High Performance Computing environment via an adaptation layer called 6LoWPAN (IPv6 over Low power Personal Area Network). The routing protocol used by 6LoWPAN is RPL (IPv6 Routing Protocol over LLN). Like many other routing protocols, RPL is susceptible to blackhole attacks which cause topological isolation for a subset of nodes in the LLN. A malicious node instigating the blackhole attack drops received packets from nodes in its subtree which it is supposed to forward. Thus, the malicious node successfully isolates nodes in its subtree from the rest of the network. In this paper, we propose an algorithm based on the concept of exponential smoothing to detect the topological isolation of nodes due to blackhole attack. Exponential smoothing is a technique for smoothing time series data using the exponential window function and is used for short, medium and long term forecasting. In our proposed algorithm, exponential smoothing is used to estimate the next arrival time of packets at the sink node from every other node in the LLN. Using this estimation, the algorithm is designed to identify the malicious nodes instigating blackhole attack in real time.
Kenarangi, Farid, Partin-Vaisband, Inna.  2019.  Security Network On-Chip for Mitigating Side-Channel Attacks. 2019 ACM/IEEE International Workshop on System Level Interconnect Prediction (SLIP). :1–6.
Hardware security is a critical concern in design and fabrication of integrated circuits (ICs). Contemporary hardware threats comprise tens of advance invasive and non-invasive attacks for compromising security of modern ICs. Numerous attack-specific countermeasures against the individual threats have been proposed, trading power, area, speed, and design complexity of a system for security. These typical overheads combined with strict performance requirements in advanced technology nodes and high complexity of modern ICs often make the codesign of multiple countermeasures impractical. In this paper, on-chip distribution networks are exploited for detecting those hardware security threats that require non-invasive, yet physical interaction with an operating device-under-attack (e.g., measuring equipment for collecting sensitive information in side-channel attacks). With the proposed approach, the effect of the malicious physical interference with the device-under-attack is captured in the form of on-chip voltage variations and utilized for detecting malicious activity in the compromised device. A machine learning (ML) security IC is trained to predict system security based on sensed variations of signals within on-chip distribution networks. The trained ML ICs are distributed on-chip, yielding a robust and high-confidence security network on-chip. To halt an active attack, a variety of desired counteractions can be executed in a cost-effective manner upon the attack detection. The applicability and effectiveness of these security networks is demonstrated in this paper with respect to power, timing, and electromagnetic analysis attacks.
Su, Yu, Wu, Jing, Long, Chengnian, Li, Shaoyuan.  2018.  Event-triggered Control for Networked Control Systems Under Replay Attacks. 2018 Chinese Automation Congress (CAC). :2636—2641.
With wide application of networked control systems(N CSs), NCSs security have encountered severe challenges. In this paper, we propose a robust event-triggered controller design method under replay attacks, and the control signal on the plant is updated only when the event-triggering condition is satisfied. We develop a general random replay attack model rather than predetermined specific patterns for the occurrences of replay attacks, which allows to obtain random states to replay. We show that the proposed event-triggered control (ETC) scheme, if well designed, can tolerate some consecutive replay attacks, without affecting the corresponding closed-loop system stability and performance. A numerical examples is finally given to illustrate the effectiveness of our method.
Jie, Bao, Liu, Jingju, Wang, Yongjie, Zhou, Xuan.  2019.  Digital Ant Mechanism and Its Application in Network Security. 2019 IEEE 3rd Information Technology, Networking, Electronic and Automation Control Conference (ITNEC). :710–714.
Digital ant technology is a new distributed and self-organization cyberspace defense paradigm. This paper describes digital ants system's developing process, characteristics, system architecture and mechanisms to illustrate its superiority, searches the possible applications of digital ants system. The summary of the paper and the trends of digital ants system are pointed out.
Liew, Seng Pei, Ikeda, Satoshi.  2019.  Detecting Adversary using Windows Digital Artifacts. 2019 IEEE International Conference on Big Data (Big Data). :3210—3215.

We consider the possibility of detecting malicious behaviors of the advanced persistent threat (APT) at endpoints during incident response or forensics investigations. Specifically, we study the case where third-party sensors are not available; our observables are obtained solely from inherent digital artifacts of Windows operating systems. What is of particular interest is an artifact called the Application Compatibility Cache (Shimcache). As it is not apparent from the Shimcache when a file has been executed, we propose an algorithm of estimating the time of file execution up to an interval. We also show guarantees of the proposed algorithm's performance and various possible extensions that can improve the estimation. Finally, combining this approach with methods of machine learning, as well as information from other digital artifacts, we design a prototype system called XTEC and demonstrate that it can help hunt for the APT in a real-world case study.

Simpson, Oluyomi, Sun, Yichuang.  2019.  A Stochastic Method to Physical Layer Security of an Amplify-and-Forward Spectrum Sensing in Cognitive Radio Networks: Secondary User to Relay. 2019 15th International Wireless Communications Mobile Computing Conference (IWCMC). :197—202.
In this paper, a framework for capitalizing on the potential benefits of physical layer security in an amplify-and-forward cooperative spectrum sensing (AF-CSS) in a cognitive radio network (CRN) using a stochastic geometry is proposed. In the CRN network the sensing data from secondary users (SUs) are collected by a fusion center (FC) with the help of access points (AP) as relays, and when malicious eavesdropping secondary users (SUs) are listening. We focus on the secure transmission of active SUs transmitting their sensing data to the AP. Closed expressions for the average secrecy rate are presented. Numerical results corroborate our analysis and show that multiple antennas at the APs can enhance the security of the AF-CSS-CRN. The obtained numerical results show that average secrecy rate between the AP and its correlated FC decreases when the number of AP is increased. Nevertheless, we find that an increase in the number of AP initially increases the overall average secrecy rate, with a perilous value at which the overall average secrecy rate then decreases. While increasing the number of active SUs, there is a decrease in the secrecy rate between the sensor and its correlated AP.
Srinu, Sesham, Reddy, M. Kranthi Kumar, Temaneh-Nyah, Clement.  2019.  Physical layer security against cooperative anomaly attack using bivariate data in distributed CRNs. 2019 11th International Conference on Communication Systems Networks (COMSNETS). :410—413.
Wireless communication network (WCN) performance is primarily depends on physical layer security which is critical among all other layers of OSI network model. It is typically prone to anomaly/malicious user's attacks owing to openness of wireless channels. Cognitive radio networking (CRN) is a recently emerged wireless technology that is having numerous security challenges because of its unlicensed access of wireless channels. In CRNs, the security issues occur mainly during spectrum sensing and is more pronounced during distributed spectrum sensing. In recent past, various anomaly effects are modelled and developed detectors by applying advanced statistical techniques. Nevertheless, many of these detectors have been developed based on sensing data of one variable (energy measurement) and degrades their performance drastically when the data is contaminated with multiple anomaly nodes, that attack the network cooperatively. Hence, one has to develop an efficient multiple anomaly detection algorithm to eliminate all possible cooperative attacks. To achieve this, in this work, the impact of anomaly on detection probability is verified beforehand in developing an efficient algorithm using bivariate data to detect possible attacks with mahalanobis distance measure. Result discloses that detection error of cooperative attacks by anomaly has significant impact on eigenvalue-based sensing.
Zhang, Yang, Chen, Pengfei, Hao, Long.  2019.  Research on Privacy Protection with Weak Security Network Coding for Mobile Computing. 2019 Seventh International Conference on Advanced Cloud and Big Data (CBD). :174—179.

With the rapid development of the contemporary society, wide use of smart phone and vehicle sensing devices brings a huge influence on the extensive data collection. Network coding can only provide weak security privacy protection. Aiming at weak secure feature of network coding, this paper proposes an information transfer mechanism, Weak Security Network Coding with Homomorphic Encryption (HE-WSNC), and it is integrated into routing policy. In this mechanism, a movement model is designed, which allows information transmission process under Wi-Fi and Bluetooth environment rather than consuming 4G data flow. Not only does this application reduce the cost, but also improve reliability of data transmission. Moreover, it attracts more users to participate.

Hassan, Galal, Rashwan, Abdulmonem M., Hassanein, Hossam S..  2019.  SandBoxer: A Self-Contained Sensor Architecture for Sandboxing the Industrial Internet of Things. 2019 IEEE International Conference on Communications Workshops (ICC Workshops). :1–6.
The Industrial Internet-of-Things (IIoT) has gained significant interest from both the research and industry communities. Such interest came with a vision towards enabling automation and intelligence for futuristic versions of our day to day devices. However, such a vision demands the need for accelerated research and development of IIoT systems, in which sensor integration, due to their diversity, impose a significant roadblock. Such roadblocks are embodied in both the cost and time to develop an IIoT platform, imposing limits on the innovation of sensor manufacturers, as a result of the demand to maintain interface compatibility for seamless integration and low development costs. In this paper, we propose an IIoT system architecture (SandBoxer) tailored for sensor integration, that utilizes a collaborative set of efforts from various technologies and research fields. The paper introduces the concept of ”development-sandboxing” as a viable choice towards building the foundation for enabling true-plug-and-play IIoT. We start by outlining the key characteristics desired to create an architecture that catalyzes IIoT research and development. We then present our vision of the architecture through the use of a sensor-hosted EEPROM and scripting to ”sandbox” the sensors, which in turn accelerates sensor integration for developers and creates a broader innovation path for sensor manufacturers. We also discuss multiple design alternative, challenges, and use cases in both the research and industry.
Kalashnikov, A.O., Anikina, E.V..  2019.  Complex Network Cybersecurity Monitoring Method. 2019 Twelfth International Conference "Management of large-scale system development" (MLSD). :1–3.
This paper considers one of the methods of efficient allocation of limited resources in special-purpose devices (sensors) to monitor complex network unit cybersecurity.
Cortés, Francisco Muñoz, Gaviria Gómez, Natalia.  2019.  A Hybrid Alarm Management Strategy in Signature-Based Intrusion Detection Systems. 2019 IEEE Colombian Conference on Communications and Computing (COLCOM). :1–6.

Signature-based Intrusion Detection Systems (IDS) are a key component in the cybersecurity defense strategy for any network being monitored. In order to improve the efficiency of the intrusion detection system and the corresponding mitigation action, it is important to address the problem of false alarms. In this paper, we present a comparative analysis of two approaches that consider the false alarm minimization and alarm correlation techniques. The output of this analysis provides us the elements to propose a parallelizable strategy designed to achieve better results in terms of precision, recall and alarm load reduction in the prioritization of alarms. We use Prelude SIEM as the event normalizer in order to process security events from heterogeneous sensors and to correlate them. The alarms are verified using the dynamic network context information collected from the vulnerability analysis, and they are prioritized using the HP Arsight priority formula. The results show an important reduction in the volume of alerts, together with a high precision in the identification of false alarms.

Vatanparvar, Korosh, Al Faruque, Mohammad Abdullah.  2019.  Self-Secured Control with Anomaly Detection and Recovery in Automotive Cyber-Physical Systems. 2019 Design, Automation Test in Europe Conference Exhibition (DATE). :788–793.

Cyber-Physical Systems (CPS) are growing with added complexity and functionality. Multidisciplinary interactions with physical systems are the major keys to CPS. However, sensors, actuators, controllers, and wireless communications are prone to attacks that compromise the system. Machine learning models have been utilized in controllers of automotive to learn, estimate, and provide the required intelligence in the control process. However, their estimation is also vulnerable to the attacks from physical or cyber domains. They have shown unreliable predictions against unknown biases resulted from the modeling. In this paper, we propose a novel control design using conditional generative adversarial networks that will enable a self-secured controller to capture the normal behavior of the control loop and the physical system, detect the anomaly, and recover from them. We experimented our novel control design on a self-secured BMS by driving a Nissan Leaf S on standard driving cycles while under various attacks. The performance of the design has been compared to the state-of-the-art; the self-secured BMS could detect the attacks with 83% accuracy and the recovery estimation error of 21% on average, which have improved by 28% and 8%, respectively.

Lv, Chengcai, Shen, Binjian, Guo, Xinxin, Zhu, Chengwei.  2019.  Communication Design for Underwater Acoustic Positioning Networks. 2019 IEEE 4th International Conference on Signal and Image Processing (ICSIP). :573–577.
The past decade has seen a growing interest in underwater acoustic positioning networks (UAPNs) because of their wide applications in marine research, ocean monitoring, offshore exploration, and defense or homeland security. Efficient communication among all sensors and receivers is crucial so as to make positioning service available. Traditional UAPNs could locate only one target, that are growing obsolete due to increasing demands for multiple users working at the same time. Due to the demands for multiple users working simultaneously and narrow acoustic bandwidth, new efficient and reliable communication and networking protocols are required in design for UAPNs. In this paper, we aim to provide the procedure of communication design for UAPNs based on sonar equation and spread spectrum communication. What's more, signal design and performance analysis are supplied. The results show that the signal we designed have ideal correlation performance and high processing gain. The signal is suitable for multiple users UAPNs and thus show favorable potential in ocean engineering applications.
Shrestha, Babins, Mohamed, Manar, Saxena, Nitesh.  2019.  ZEMFA: Zero-Effort Multi-Factor Authentication based on Multi-Modal Gait Biometrics. 2019 17th International Conference on Privacy, Security and Trust (PST). :1–10.
In this paper, we consider the problem of transparently authenticating a user to a local terminal (e.g., a desktop computer) as she approaches towards the terminal. Given its appealing usability, such zero-effort authentication has already been deployed in the real-world where a computer terminal or a vehicle can be unlocked by the mere proximity of an authentication token (e.g., a smartphone). However, existing systems based on a single authentication factor contains one major security weakness - unauthorized physical access to the token, e.g., during lunch-time or upon theft, allows the attacker to have unfettered access to the terminal. We introduce ZEMFA, a zero-effort multi-factor authentication system based on multiple authentication tokens and multi-modal behavioral biometrics. Specifically, ZEMFA utilizes two types of authentication tokens, a smartphone and a smartwatch (or a bracelet) and two types of gait patterns captured by these tokens, mid/lower body movements measured by the phone and wrist/arm movements captured by the watch. Since a user's walking or gait pattern is believed to be unique, only that user (no impostor) would be able to gain access to the terminal even when the impostor is given access to both of the authentication tokens. We present the design and implementation of ZEMFA. We demonstrate that ZEMFA offers a high degree of detection accuracy, based on multi-sensor and multi-device fusion. We also show that ZEMFA can resist active attacks that attempt to mimic a user's walking pattern, especially when multiple devices are used.
Jiang, Qi, Zhang, Xin, Zhang, Ning, Tian, Youliang, Ma, Xindi, Ma, Jianfeng.  2019.  Two-Factor Authentication Protocol Using Physical Unclonable Function for IoV. 2019 IEEE/CIC International Conference on Communications in China (ICCC). :195–200.
As an extension of Internet of Things (IoT) in transportation sector, the Internet of Vehicles (IoV) can greatly facilitate vehicle management and route planning. With ever-increasing penetration of IoV, the security and privacy of driving data should be guaranteed. Moreover, since vehicles are often left unattended with minimum human interventions, the onboard sensors are vulnerable to physical attacks. Therefore, the physically secure authentication and key agreement (AKA) protocol is urgently needed for IoV to implement access control and information protection. In this paper, physical unclonable function (PUF) is introduced in the AKA protocol to ensure that the system is secure even if the user devices or sensors are compromised. Specifically, PUF, as a hardware fingerprint generator, eliminates the storage of any secret information in user devices or vehicle sensors. By combining password with PUF, the user device cannot be used by someone else to be successfully authenticated as the user. By resorting to public key cryptography, the proposed protocol can provide anonymity and desynchronization resilience. Finally, the elaborate security analysis demonstrates that the proposed protocol is free from the influence of known attacks and can achieve expected security properties, and the performance evaluation indicates the efficiency of our protocol.
Ibrokhimov, Sanjar, Hui, Kueh Lee, Abdulhakim Al-Absi, Ahmed, lee, hoon jae, Sain, Mangal.  2019.  Multi-Factor Authentication in Cyber Physical System: A State of Art Survey. 2019 21st International Conference on Advanced Communication Technology (ICACT). :279–284.
Digital Multifactor authentication is one of the best ways to make secure authentication. It covers many different areas of a Cyber-connected world, including online payments, communications, access right management, etc. Most of the time, Multifactor authentication is little complex as it require extra step from users. With two-factor authentication, along with the user-ID and password, user also needs to enter a special code which they normally receive by short message service or some special code which they got in advance. This paper will discuss the evolution from single authentication to Multi-Factor Authentication (MFA) starting from Single-Factor Authentication (SFA) and through Two-Factor Authentication (2FA). In addition, this paper presents five high-level categories of features of user authentication in the gadget-free world including security, privacy, and usability aspects. These are adapted and extended from earlier research on web authentication methods. In conclusion, this paper gives future research directions and open problems that stem from our observations.
Griffioen, Paul, Weerakkody, Sean, Sinopoli, Bruno.  2019.  An Optimal Design of a Moving Target Defense for Attack Detection in Control Systems. 2019 American Control Conference (ACC). :4527–4534.
In this paper, we consider the problem of designing system parameters to improve detection of attacks in control systems. Specifically, we study control systems which are vulnerable to integrity attacks on sensors and actuators. We aim to defend against strong model aware adversaries that can read and modify all sensors and actuators. Previous work has proposed a moving target defense for detecting integrity attacks on control systems. Here, an authenticating subsystem with time-varying dynamics coupled to the original plant is introduced. Due to this coupling, an attack on the original system will affect the authenticating subsystem and in turn be revealed by a set of sensors measuring the extended plant. Moreover, the time-varying dynamics of the extended plant act as a moving target, preventing an adversary from developing an effective adaptive attack strategy. Previous work has failed to consider the design of the time-varying system matrices and as such provides little in terms of guidelines for implementation in real systems. This paper proposes two optimization problems for designing these matrices. The first designs the auxiliary actuators to maximize detection performance while the second designs the coupling matrices to maximize system estimation performance. Numerical examples are presented that validate our approach.
Arshad, Akashah, Hanapi, Zurina Mohd, Subramaniam, Shamala K., Latip, Rohaya.  2019.  Performance Evaluation of the Geographic Routing Protocols Scalability. 2019 International Conference on Information Networking (ICOIN). :396–398.
Scalability is an important design factor for evaluating the performance of routing protocols as the network size or traffic load increases. One of the most appropriate design methods is to use geographic routing approach to ensure scalability. This paper describes a scalability study comparing Secure Region Based Geographic Routing (SRBGR) and Dynamic Window Secure Implicit Geographic Forwarding (DWSIGF) protocols in various network density scenarios based on an end-to-end delay performance metric. The simulation studies were conducted in MATLAB 2106b where the network densities were varied according to the network topology size with increasing traffic rates. The results showed that DWSIGF has a lower end-to-end delay as compared to SRBGR for both sparse (15.4%) and high density (63.3%) network scenarios.Despite SRBGR having good security features, there is a need to improve the performance of its end-to-end delay to fulfil the application requirements.
Belej, Olexander, Nestor, Natalia, Polotai, Orest, Sadeckii, Jan.  2019.  Features of Application of Data Transmission Protocols in Wireless Networks of Sensors. 2019 3rd International Conference on Advanced Information and Communications Technologies (AICT). :317–322.
This article discusses the vulnerabilities and complexity of designing secure IoT-solutions, and then presents proven approaches to protecting devices and gateways. Specifically, security mechanisms such as device authentication (including certificate-based authentication), device authentication, and application a verification of identification are described. The authors consider a protocol of message queue telemetry transport for speech and sensor networks on the Internet, its features, application variants, and characteristic procedures. The principle of "publishersubscriber" is considered. An analysis of information elements and messages is carried out. The urgency of the theme is due to the rapid development of "publisher-subscriber" architecture, for which the protocol is most characteristic.
Wen, Jinming, Yu, Wei.  2019.  Exact Sparse Signal Recovery via Orthogonal Matching Pursuit with Prior Information. ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). :5003–5007.
The orthogonal matching pursuit (OMP) algorithm is a commonly used algorithm for recovering K-sparse signals x ∈ ℝn from linear model y = Ax, where A ∈ ℝm×n is a sensing matrix. A fundamental question in the performance analysis of OMP is the characterization of the probability that it can exactly recover x for random matrix A. Although in many practical applications, in addition to the sparsity, x usually also has some additional property (for example, the nonzero entries of x independently and identically follow the Gaussian distribution), none of existing analysis uses these properties to answer the above question. In this paper, we first show that the prior distribution information of x can be used to provide an upper bound on \textbackslashtextbar\textbackslashtextbarx\textbackslashtextbar\textbackslashtextbar21/\textbackslashtextbar\textbackslashtextbarx\textbackslashtextbar\textbackslashtextbar22, and then explore the bound to develop a better lower bound on the probability of exact recovery with OMP in K iterations. Simulation tests are presented to illustrate the superiority of the new bound.
Bansal, Bhawana, Sharma, Monika.  2019.  Client-Side Verification Framework for Offline Architecture of IoT. 2019 3rd International conference on Electronics, Communication and Aerospace Technology (ICECA). :1044–1050.
Internet of things is a network formed between two or more devices through internet which helps in sharing data and resources. IoT is present everywhere and lot of applications in our day-to-day life such as smart homes, smart grid system which helps in reducing energy consumption, smart garbage collection to make cities clean, smart cities etc. It has some limitations too such as concerns of security of the network and the cost of installations of the devices. There have been many researches proposed various method in improving the IoT systems. In this paper, we have discussed about the scope and limitations of IoT in various fields and we have also proposed a technique to secure offline architecture of IoT.
Shahinzadeh, Hossein, Moradi, Jalal, Gharehpetian, Gevork B., Nafisi, Hamed, Abedi, Mehrdad.  2019.  IoT Architecture for Smart Grids. 2019 International Conference on Protection and Automation of Power System (IPAPS). :22–30.
The tremendous advances in information and communications technology (ICT), as well as the embedded systems, have been led to the emergence of the novel concept of the internet of things (IoT). Enjoying IoT-based technologies, many objects and components can be connected to each other through the internet or other modern communicational platforms. Embedded systems which are computing machines for special purposes like those utilized in high-tech devices, smart buildings, aircraft, and vehicles including advanced controllers, sensors, and meters with the ability of information exchange using IT infrastructures. The phrase "internet", in this context, does not exclusively refer to the World Wide Web rather than any type of server-based or peer-to-peer networks. In this study, the application of IoT in smart grids is addressed. Hence, at first, an introduction to the necessity of deployment of IoT in smart grids is presented. Afterwards, the applications of IoT in three levels of generation, transmission, and distribution is proposed. The generation level is composed of applications of IoT in renewable energy resources, wind and solar in particular, thermal generation, and energy storage facilities. The deployment of IoT in transmission level deals with congestion management in power system and guarantees the security of the system. In the distribution level, the implications of IoT in active distribution networks, smart cities, microgrids, smart buildings, and industrial sector are evaluated.
Mowla, Nishat I, Doh, Inshil, Chae, Kijoon.  2019.  Binarized Multi-Factor Cognitive Detection of Bio-Modality Spoofing in Fog Based Medical Cyber-Physical System. 2019 International Conference on Information Networking (ICOIN). :43–48.
Bio-modalities are ideal for user authentication in Medical Cyber-Physical Systems. Various forms of bio-modalities, such as the face, iris, fingerprint, are commonly used for secure user authentication. Concurrently, various spoofing approaches have also been developed over time which can fail traditional bio-modality detection systems. Image synthesis with play-doh, gelatin, ecoflex etc. are some of the ways used in spoofing bio-identifiable property. Since the bio-modality detection sensors are small and resource constrained, heavy-weight detection mechanisms are not suitable for these sensors. Recently, Fog based architectures are proposed to support sensor management in the Medical Cyber-Physical Systems (MCPS). A thin software client running in these resource-constrained sensors can enable communication with fog nodes for better management and analysis. Therefore, we propose a fog-based security application to detect bio-modality spoofing in a Fog based MCPS. In this regard, we propose a machine learning based security algorithm run as an application at the fog node using a binarized multi-factor boosted ensemble learner algorithm coupled with feature selection. Our proposal is verified on real datasets provided by the Replay Attack, Warsaw and LiveDet 2015 Crossmatch benchmark for face, iris and fingerprint modality spoofing detection used for authentication in an MCPS. The experimental analysis shows that our approach achieves significant performance gain over the state-of-the-art approaches.