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Ucar, Seyhan, Coleri Ergen, Sinem, Ozkasap, Oznur, Tsonev, Dobroslav, Burchardt, Harald.  2016.  SecVLC: Secure Visible Light Communication for Military Vehicular Networks. Proceedings of the 14th ACM International Symposium on Mobility Management and Wireless Access. :123–129.

Technology coined as the vehicular ad hoc network (VANET) is harmonizing with Intelligent Transportation System (ITS) and Intelligent Traffic System (ITF). An application scenario of VANET is the military communication where vehicles move as a convoy on roadways, requiring secure and reliable communication. However, utilization of radio frequency (RF) communication in VANET limits its usage in military applications, due to the scarce frequency band and its vulnerability to security attacks. Visible Light Communication (VLC) has been recently introduced as a more secure alternative, limiting the reception of neighboring nodes with its directional transmission. However, secure vehicular VLC that ensures confidential data transfer among the participating vehicles, is an open problem. In this paper, we propose a secure military light communication protocol (SecVLC) for enabling efficient and secure data sharing. We use the directionality property of VLC to ensure that only target vehicles participate in the communication. Vehicles use full-duplex communication where infra-red (IR) is utilized to share a secret key and VLC is used to receive encrypted data. We experimentally demonstrate the suitability of SecVLC in outdoor scenarios at varying inter-vehicular distances with key metrics of interest, including the security, data packet delivery ratio and delay.

Uda, Satoshi, Shikida, Mikifumi.  2016.  Challenges of Deploying PKI Based Client Digital Certification. Proceedings of the 2016 ACM on SIGUCCS Annual Conference. :55–60.

We are confronted with the threat from the theft of user-id / password information caused by phishing attacks. Now authentication by using the user-id and password is no longer safe. We can use the PKI-based authentication as a safer authentication mechanism. In our university, Japan Advanced Institute of Science and Technology (JAIST), we deployed On Demand Digital Certificate Issuing System for our users, and employ the PKI-based client certificates for log-on to web application, connecting to wireless network (including eduroam), using VPN service, and email sender signing. In addition, National In-stitute of Information (NII), which are providing common ICT infrastructure services for Japanese universities and institutes, started a service to issue client certificates in this year. So use of the electronic certificates will become more popular within a few years in Japan. However, there are not so enough cases deploying the electronic certificate based authentication in University infrastructure, we still has many tips and issues on operating this. In this paper, we introduce the use case of the electronic certificate in JAIST, the challenges and issues, and consider the future prospects.

Udayakumar, N., Saglani, V. J., Cupta, A. V., Subbulakshmi, T..  2018.  Malware Classification Using Machine Learning Algorithms. 2018 2nd International Conference on Trends in Electronics and Informatics (ICOEI). :1-9.

Lately, we are facing the Malware crisis due to various types of malware or malicious programs or scripts available in the huge virtual world - the Internet. But, what is malware? Malware can be a malicious software or a program or a script which can be harmful to the user's computer. These malicious programs can perform a variety of functions, including stealing, encrypting or deleting sensitive data, altering or hijacking core computing functions and monitoring users' computer activity without their permission. There are various entry points for these programs and scripts in the user environment, but only one way to remove them is to find them and kick them out of the system which isn't an easy job as these small piece of script or code can be anywhere in the user system. This paper involves the understanding of different types of malware and how we will use Machine Learning to detect these malwares.

Udd, Robert, Asplund, Mikael, Nadjm-Tehrani, Simin, Kazemtabrizi, Mehrdad, Ekstedt, Mathias.  2016.  Exploiting Bro for Intrusion Detection in a SCADA System. Proceedings of the 2Nd ACM International Workshop on Cyber-Physical System Security. :44–51.
Supervisory control and data acquisition (SCADA) systems that run our critical infrastructure are increasingly run with Internet-based protocols and devices for remote monitoring. The embedded nature of the components involved, and the legacy aspects makes adding new security mechanisms in an efficient manner far from trivial. In this paper we study an anomaly detection based approach that enables detecting zero-day malicious threats and benign malconfigurations and mishaps. The approach builds on an existing platform (Bro) that lends itself to modular addition of new protocol parsers and event handling mechanisms. As an example we have shown an application of the technique to the IEC-60870-5-104 protocol and tested the anomaly detector with mixed results. The detection accuracy and false positive rate, as well as real-time response was adequate for 3 of our 4 created attacks. We also discovered some additional work that needs to be done to an existing protocol parser to extend its reach.
Uddin, M. N., Lie, H., Li, H..  2017.  Hybrid Cloud Computing and Integrated Transport System. 2017 International Conference on Green Informatics (ICGI). :111–116.

In the 21st century, integrated transport, service and mobility concepts for real-life situations enabled by automation system and smarter connectivity. These services and ideas can be blessed from cloud computing, and big data management techniques for the transport system. These methods could also include automation, security, and integration with other modes. Integrated transport system can offer new means of communication among vehicles. This paper presents how hybrid could computing influence to make urban transportation smarter besides considering issues like security and privacy. However, a simple structured framework based on a hybrid cloud computing system might prevent common existing issues.

Uddin, M. Y. S., Venkatasubramanian, N..  2018.  Edge Caching for Enriched Notifications Delivery in Big Active Data. 2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS). :696–705.
In this paper, we propose a set of caching strategies for big active data (BAD) systems. BAD is a data management paradigm that allows ingestion of massive amount of data from heterogeneous sources, such as sensor data, social networks, web and crowdsourced data in a large data cluster consisting of many computing and storage nodes, and enables a very large number of end users to subscribe to those data items through declarative subscriptions. A set of distributed broker nodes connect these end users to the backend data cluster, manage their subscriptions and deliver the subscription results to the end users. Unlike the most traditional publish-subscribe systems that match subscriptions against a single stream of publications to generate notifications, BAD can match subscriptions across multiple publications (by leveraging storage in the backend) and thus can enrich notifications with a rich set of diverse contents. As the matched results are delivered to the end users through the brokers, the broker node caches the results for a while so that the subscribers can retrieve them with reduced latency. Interesting research questions arise in this context so as to determine which result objects to cache or drop when the cache becomes full (eviction-based caching) or to admit objects with an explicit expiration time indicating how much time they should reside in the cache (TTL based caching). To this end, we propose a set of caching strategies for the brokers and show that the schemes achieve varying degree of efficiency in terms of notification delivery in the BAD system. We evaluate our schemes via a prototype implementation and through detailed simulation studies.
Uddin, M.P., Abu Marjan, M., Binte Sadia, N., Islam, M.R..  2014.  Developing a cryptographic algorithm based on ASCII conversions and a cyclic mathematical function. Informatics, Electronics Vision (ICIEV), 2014 International Conference on. :1-5.

Encryption and decryption of data in an efficient manner is one of the challenging aspects of modern computer science. This paper introduces a new algorithm for Cryptography to achieve a higher level of security. In this algorithm it becomes possible to hide the meaning of a message in unprintable characters. The main issue of this paper is to make the encrypted message undoubtedly unprintable using several times of ASCII conversions and a cyclic mathematical function. Dividing the original message into packets binary matrices are formed for each packet to produce the unprintable encrypted message through making the ASCII value for each character below 32. Similarly, several ASCII conversions and the inverse cyclic mathematical function are used to decrypt the unprintable encrypted message. The final encrypted message received from three times of encryption becomes an unprintable text through which the algorithm possesses higher level of security without increasing the size of data or loosing of any data.

Udod, Kyryll, Kushnarenko, Volodymyr, Wesner, Stefan, Svjatnyj, Volodymyr.  2019.  Preservation System for Scientific Experiments in High Performance Computing: Challenges and Proposed Concept. 2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS). 2:809–813.
Continuously growing amount of research experiments using High Performance Computing (HPC) leads to the questions of research data management and in particular how to preserve a scientific experiment including all related data for long term for its future reproduction. This paper covers some challenges and possible solutions related to the preservation of scientific experiments on HPC systems and represents a concept of the preservation system for HPC computations. Storage of the experiment itself with some related data is not only enough for its future reproduction, especially in the long term. For that case preservation of the whole experiment's environment (operating system, used libraries, environment variables, input data, etc.) via containerization technology (e.g. using Docker, Singularity) is proposed. This approach allows to preserve the entire environment, but is not always possible on every HPC system because of security issues. And it also leaves a question, how to deal with commercial software that was used within the experiment. As a possible solution we propose to run a preservation process outside of the computing system on the web-server and to replace all commercial software inside the created experiment's image with open source analogues that should allow future reproduction of the experiment without any legal issues. The prototype of such a system was developed, the paper provides the scheme of the system, its main features and describes the first experimental results and further research steps.
Uemura, Toshiaki, Kashiwabara, Yuta, Kawanuma, Daiki, Tomii, Takashi.  2016.  Accuracy Evaluation by GPS Data Correction for the EV Energy Consumption Database. Adjunct Proceedings of the 13th International Conference on Mobile and Ubiquitous Systems: Computing Networking and Services. :213–218.
Electric vehicles (EVs) are expected to be applicable to smart grids because they have large-capacity batteries. It is important that smart grid users be able to estimate surplus battery energy and/or surplus capacity in advance of deploying EVs. We constructed a database, the Energy COnsumption LOG (ECOLOG) Database System, to store vehicle daily logs acquired by smartphones placed in vehicles. The electrical energy consumption is estimated from GPS coordinate data using an EV energy-consumption model. This research specifically examines commuting with a vehicle used for same route every day. We corrected GPS coordinate data by map matching, and input the data to the EV energy consumption model. We regard the remaining battery capacity data acquired by the EV CAN as correct data. Then we evaluate the accuracy of driving energy consumption logs as estimated using the corrected GPS coordinate data.
Ueta, K., Xue, X., Nakamoto, Y., Murakami, S..  2016.  A Distributed Graph Database for the Data Management of IoT Systems. 2016 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData). :299–304.

The Internet of Things(IoT) has become a popular technology, and various middleware has been proposed and developed for IoT systems. However, there have been few studies on the data management of IoT systems. In this paper, we consider graph database models for the data management of IoT systems because these models can specify relationships in a straightforward manner among entities such as devices, users, and information that constructs IoT systems. However, applying a graph database to the data management of IoT systems raises issues regarding distribution and security. For the former issue, we propose graph database operations integrated with REST APIs. For the latter, we extend a graph edge property by adding access protocol permissions and checking permissions using the APIs with authentication. We present the requirements for a use case scenario in addition to the features of a distributed graph database for IoT data management to solve the aforementioned issues, and implement a prototype of the graph database.

Ugwoke, F. N., Okafor, K. C., Chijindu, V. C..  2015.  Security QoS profiling against cyber terrorism in airport network systems. 2015 International Conference on Cyberspace (CYBER-Abuja). :241–251.

Attacks on airport information network services in the form of Denial of Service (DoS), Distributed DoS (DDoS), and hijacking are the most effective schemes mostly explored by cyber terrorists in the aviation industry running Mission Critical Services (MCSs). This work presents a case for Airport Information Resource Management Systems (AIRMS) which is a cloud based platform proposed for the Nigerian aviation industry. Granting that AIRMS is susceptible to DoS attacks, there is need to develop a robust counter security network model aimed at pre-empting such attacks and subsequently mitigating the vulnerability in such networks. Existing works in literature regarding cyber security DoS and other schemes have not explored embedded Stateful Packet Inspection (SPI) based on OpenFlow Application Centric Infrastructure (OACI) for securing critical network assets. As such, SPI-OACI was proposed to address the challenge of Vulnerability Bandwidth Depletion DDoS Attacks (VBDDA). A characterization of the Cisco 9000 router firewall as an embedded network device with support for Virtual DDoS protection was carried out in the AIRMS threat mitigation design. Afterwards, the mitigation procedure and the initial phase of the design with Riverbed modeler software were realized. For the security Quality of Service (QoS) profiling, the system response metrics (i.e. SPI-OACI delay, throughput and utilization) in cloud based network were analyzed only for normal traffic flows. The work concludes by offering practical suggestion for securing similar enterprise management systems running on cloud infrastructure against cyber terrorists.

Ugwuoke, C., Erkin, Z., Lagendijk, R. L..  2017.  Privacy-safe linkage analysis with homomorphic encryption. 2017 25th European Signal Processing Conference (EUSIPCO). :961–965.

Genetic data are important dataset utilised in genetic epidemiology to investigate biologically coded information within the human genome. Enormous research has been delved into in recent years in order to fully sequence and understand the genome. Personalised medicine, patient response to treatments and relationships between specific genes and certain characteristics such as phenotypes and diseases, are positive impacts of studying the genome, just to mention a few. The sensitivity, longevity and non-modifiable nature of genetic data make it even more interesting, consequently, the security and privacy for the storage and processing of genomic data beg for attention. A common activity carried out by geneticists is the association analysis between allele-allele, or even a genetic locus and a disease. We demonstrate the use of cryptographic techniques such as homomorphic encryption schemes and multiparty computations, how such analysis can be carried out in a privacy friendly manner. We compute a 3 × 3 contingency table, and then, genome analyses algorithms such as linkage disequilibrium (LD) measures, all on the encrypted domain. Our computation guarantees privacy of the genome data under our security settings, and provides up to 98.4% improvement, compared to an existing solution.

Ugwuoke, Chibuike, Erkin, Zekeriya, Lagendijk, Reginald L..  2018.  Secure Fixed-Point Division for Homomorphically Encrypted Operands. Proceedings of the 13th International Conference on Availability, Reliability and Security. :33:1–33:10.

Due to privacy threats associated with computation of outsourced data, processing data on the encrypted domain has become a viable alternative. Secure computation of encrypted data is relevant for analysing datasets in areas (such as genome processing, private data aggregation, cloud computations) that require basic arithmetic operations. Performing division operation over-all encrypted inputs has not been achieved using homomorphic schemes in non-interactive modes. In interactive protocols, the cost of obtaining an encrypted quotient (from encrypted values) is computationally expensive. To the best of our knowledge, existing homomorphic solutions on encrypted division are often relaxed to consider public or private divisor. We acknowledge that there are other techniques such as secret sharing and garbled circuits adopted to compute secure division, but we are interested in homomorphic solutions. We propose an efficient and interactive two-party protocol that computes the fixed-point quotient of two encrypted inputs, using an efficient and secure comparison protocol as a sub-protocol. Our proposal provides a computational advantage, with a linear complexity in the digit precision of the quotient. We provide proof of security in the universally composable framework and complexity analyses. We present experimental results for two cryptosystem implementations in order to compare performance. An efficient prototype of our protocol is implemented using additive homomorphic scheme (Paillier), whereas a non-efficient fully-homomorphic scheme (BGV) version is equally presented as a proof of concept and analyses of our proposal.

Ukwandu, E., Buchanan, W. J., Russell, G..  2017.  Performance Evaluation of a Fragmented Secret Share System. 2017 International Conference On Cyber Situational Awareness, Data Analytics And Assessment (Cyber SA). :1–6.
There are many risks in moving data into public storage environments, along with an increasing threat around large-scale data leakage. Secret sharing scheme has been proposed as a keyless and resilient mechanism to mitigate this, but scaling through large scale data infrastructure has remained the bane of using secret sharing scheme in big data storage and retrievals. This work applies secret sharing methods as used in cryptography to create robust and secure data storage and retrievals in conjunction with data fragmentation. It outlines two different methods of distributing data equally to storage locations as well as recovering them in such a manner that ensures consistent data availability irrespective of file size and type. Our experiments consist of two different methods - data and key shares. Using our experimental results, we were able to validate previous works on the effects of threshold on file recovery. Results obtained also revealed the varying effects of share writing to and retrieval from storage locations other than computer memory. The implication is that increase in fragment size at varying file and threshold sizes rather than add overheads to file recovery, do so on creation instead, underscoring the importance of choosing a varying fragment size as file size increases.
Ullah, Faheem, Ali Babar, M..  2019.  QuickAdapt: Scalable Adaptation for Big Data Cyber Security Analytics. 2019 24th International Conference on Engineering of Complex Computer Systems (ICECCS). :81–86.
Big Data Cyber Security Analytics (BDCA) leverages big data technologies for collecting, storing, and analyzing a large volume of security events data to detect cyber-attacks. Accuracy and response time, being the most important quality concerns for BDCA, are impacted by changes in security events data. Whilst it is promising to adapt a BDCA system's architecture to the changes in security events data for optimizing accuracy and response time, it is important to consider large search space of architectural configurations. Searching a large space of configurations for potential adaptation incurs an overwhelming adaptation time, which may cancel the benefits of adaptation. We present an adaptation approach, QuickAdapt, to enable quick adaptation of a BDCA system. QuickAdapt uses descriptive statistics (e.g., mean and variance) of security events data and fuzzy rules to (re) compose a system with a set of components to ensure optimal accuracy and response time. We have evaluated QuickAdapt for a distributed BDCA system using four datasets. Our evaluation shows that on average QuickAdapt reduces adaptation time by 105× with a competitive adaptation accuracy of 70% as compared to an existing solution.
Ullah, I., Mahmoud, Q. H..  2017.  A hybrid model for anomaly-based intrusion detection in SCADA networks. 2017 IEEE International Conference on Big Data (Big Data). :2160–2167.

Supervisory Control and Data Acquisition (SCADA) systems complexity and interconnectivity increase in recent years have exposed the SCADA networks to numerous potential vulnerabilities. Several studies have shown that anomaly-based Intrusion Detection Systems (IDS) achieves improved performance to identify unknown or zero-day attacks. In this paper, we propose a hybrid model for anomaly-based intrusion detection in SCADA networks using machine learning approach. In the first part, we present a robust hybrid model for anomaly-based intrusion detection in SCADA networks. Finally, we present a feature selection model for anomaly-based intrusion detection in SCADA networks by removing redundant and irrelevant features. Irrelevant features in the dataset can affect modeling power and reduce predictive accuracy. These models were evaluated using an industrial control system dataset developed at the Distributed Analytics and Security Institute Mississippi State University Starkville, MS, USA. The experimental results show that our proposed model has a key effect in reducing the time and computational complexity and achieved improved accuracy and detection rate. The accuracy of our proposed model was measured as 99.5 % for specific-attack-labeled.

Ullah, Imtiaz, Mahmoud, Qusay H..  2019.  A Two-Level Hybrid Model for Anomalous Activity Detection in IoT Networks. 2019 16th IEEE Annual Consumer Communications Networking Conference (CCNC). :1–6.
In this paper we propose a two-level hybrid anomalous activity detection model for intrusion detection in IoT networks. The level-1 model uses flow-based anomaly detection, which is capable of classifying the network traffic as normal or anomalous. The flow-based features are extracted from the CICIDS2017 and UNSW-15 datasets. If an anomaly activity is detected then the flow is forwarded to the level-2 model to find the category of the anomaly by deeply examining the contents of the packet. The level-2 model uses Recursive Feature Elimination (RFE) to select significant features and Synthetic Minority Over-Sampling Technique (SMOTE) for oversampling and Edited Nearest Neighbors (ENN) for cleaning the CICIDS2017 and UNSW-15 datasets. Our proposed model precision, recall and F score for level-1 were measured 100% for the CICIDS2017 dataset and 99% for the UNSW-15 dataset, while the level-2 model precision, recall, and F score were measured at 100 % for the CICIDS2017 dataset and 97 % for the UNSW-15 dataset. The predictor we introduce in this paper provides a solid framework for the development of malicious activity detection in IoT networks.
Ullah, N., Ali, S. M., Khan, B., Mehmood, C. A., Anwar, S. M., Majid, M., Farid, U., Nawaz, M. A., Ullah, Z..  2019.  Energy Efficiency: Digital Signal Processing Interactions Within Smart Grid. 2019 International Conference on Engineering and Emerging Technologies (ICEET). :1–6.
Smart Grid (SG) is regarded as complex electrical power system due to massive penetration of Renewable Energy Resources and Distribution Generations. The implementation of adjustable speed drives, advance power electronic devices, and electric arc furnaces are incorporated in SG (the transition from conventional power system). Moreover, SG is an advance, automated, controlled, efficient, digital, and intelligent system that ensures pertinent benefits, such as: (a) consumer empowerment, (b) advanced communication infrastructure, (c) user-friendly system, and (d) supports bi-directional power flow. Digital Signal Processing (DSP) is key tool for SG deployment and provides key solutions to a vast array of complex SG challenges. This research provides a comprehensive study on DSP interactions within SG. The prominent challenges posed by conventional grid, such as: (a) monitoring and control, (b) Electric Vehicles infrastructure, (c) cyber data injection attack, (d) Demand Response management and (e) cyber data injection attack are thoroughly investigated in this research.
Ullah, Rehmat, Ur Rehman, Muhammad Atif, Kim, Byung-Seo, Sonkoly, Balázs, Tapolcai, János.  2019.  On Pending Interest Table in Named Data Networking based Edge Computing: The Case of Mobile Augmented Reality. 2019 Eleventh International Conference on Ubiquitous and Future Networks (ICUFN). :263–265.
Future networks require fast information response time, scalable content distribution, security and mobility. In order to enable future Internet many key enabling technologies have been proposed such as Edge computing (EC) and Named Data Networking (NDN). In EC substantial compute and storage resources are placed at the edge of the network, in close proximity to end users. Similarly, NDN provides an alternative to traditional host centric IP architecture which seems a perfect candidate for distributed computation. Although NDN with EC seems a promising approach for enabling future Internet, it can cause various challenges such as expiry time of the Pending Interest Table (PIT) and non-trivial computation of the edge node. In this paper we discuss the expiry time and non-trivial computation in NDN based EC. We argue that if NDN is integrated in EC, then the PIT expiry time will be affected in relation with the processing time on the edge node. Our analysis shows that integrating NDN in EC without considering PIT expiry time may result in the degradation of network performance in terms of Interest Satisfaction Rate.
Ullah, S., Li, X. Y., Zhang, L..  2017.  A Review of Signcryption Schemes Based on Hyper Elliptic Curve. 2017 3rd International Conference on Big Data Computing and Communications (BIGCOM). :51–58.

Now-a-days security is a challenging task in different types of networks, such as Mobile Networks, Wireless Sensor Networks (WSN) and Radio Frequency Identifications Systems (RFIS) etc, to overcome these challenges we use sincryption. Signcryption is a new public key cryptographic primitive that performs the functions of digital signature and encryption in single logical step. The main contribution of signcrytion scheme, it is more suitable for low constrained environment. Moreover some signcryption schemes based on RSA, Elliptic Curve (EC) and Hyper Elliptic Curve (HEC). This paper contains a critical review of signcryption schemes based on hyper elliptic curve, since it reduce communication and computational costs for low constrained devices. It also explores advantages and disadvantages of different signcryption schemes based on HEC.

Ulrich, J., Drahos, J., Govindarasu, M..  2017.  A symmetric address translation approach for a network layer moving target defense to secure power grid networks. 2017 Resilience Week (RWS). :163–169.

This paper will suggest a robust method for a network layer Moving Target Defense (MTD) using symmetric packet scheduling rules. The MTD is implemented and tested on a Supervisory Control and Data Acquisition (SCADA) network testbed. This method is shown to be efficient while providing security benefits to the issues faced by the static nature of SCADA networks. The proposed method is an automated tool that may provide defense in depth when be used in conjunction with other MTDs and traditional security devices.

Ulz, T., Pieber, T., Steger, C., Haas, S., Matischek, R., Bock, H..  2017.  Hardware-Secured Configuration and Two-Layer Attestation Architecture for Smart Sensors. 2017 Euromicro Conference on Digital System Design (DSD). :229–236.
Summary form only given. Strong light-matter coupling has been recently successfully explored in the GHz and THz [1] range with on-chip platforms. New and intriguing quantum optical phenomena have been predicted in the ultrastrong coupling regime [2], when the coupling strength Ω becomes comparable to the unperturbed frequency of the system ω. We recently proposed a new experimental platform where we couple the inter-Landau level transition of an high-mobility 2DEG to the highly subwavelength photonic mode of an LC meta-atom [3] showing very large Ω/ωc = 0.87. Our system benefits from the collective enhancement of the light-matter coupling which comes from the scaling of the coupling Ω ∝ √n, were n is the number of optically active electrons. In our previous experiments [3] and in literature [4] this number varies from 104-103 electrons per meta-atom. We now engineer a new cavity, resonant at 290 GHz, with an extremely reduced effective mode surface Seff = 4 × 10-14 m2 (FE simulations, CST), yielding large field enhancements above 1500 and allowing to enter the few (\textbackslashtextless;100) electron regime. It consist of a complementary metasurface with two very sharp metallic tips separated by a 60 nm gap (Fig.1(a, b)) on top of a single triangular quantum well. THz-TDS transmission experiments as a function of the applied magnetic field reveal strong anticrossing of the cavity mode with linear cyclotron dispersion. Measurements for arrays of only 12 cavities are reported in Fig.1(c). On the top horizontal axis we report the number of electrons occupying the topmost Landau level as a function of the magnetic field. At the anticrossing field of B=0.73 T we measure approximately 60 electrons ultra strongly coupled (Ω/ω- \textbackslashtextbar\textbackslashtextbar
Ulz, T., Pieber, T., Steger, C., Lesjak, C., Bock, H., Matischek, R..  2017.  SECURECONFIG: NFC and QR-code based hybrid approach for smart sensor configuration. 2017 IEEE International Conference on RFID (RFID). :41–46.

In smart factories and smart homes, devices such as smart sensors are connected to the Internet. Independent of the context in which such a smart sensor is deployed, the possibility to change its configuration parameters in a secure way is essential. Existing solutions do provide only minimal security or do not allow to transfer arbitrary configuration data. In this paper, we present an NFC- and QR-code based configuration interface for smart sensors which improves the security and practicability of the configuration altering process while introducing as little overhead as possible. We present a protocol for configuration as well as a hardware extension including a dedicated security controller (SC) for smart sensors. For customers, no additional hardware other than a commercially available smartphone will be necessary which makes the proposed approach highly applicable for smart factory and smart home contexts alike.

Ulz, T., Pieber, T., Steger, C., Matischek, R., Bock, H..  2017.  Towards trustworthy data in networked control systems: A hardware-based approach. 2017 22nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA). :1–8.

The importance of Networked Control Systems (NCS) is steadily increasing due to recent trends such as smart factories. Correct functionality of such NCS needs to be protected as malfunctioning systems could have severe consequences for the controlled process or even threaten human lives. However, with the increase in NCS, also attacks targeting these systems are becoming more frequent. To mitigate attacks that utilize captured sensor data in an NCS, transferred data needs to be protected. While using well-known methods such as Transport Layer Security (TLS) might be suitable to protect the data, resource constraint devices such as sensors often are not powerful enough to perform the necessary cryptographic operations. Also, as we will show in this paper, applying simple encryption in an NCS may enable easy Denial-of-Service (DoS) attacks by attacking single bits of the encrypted data. Therefore, in this paper, we present a hardware-based approach that enables sensors to perform the necessary encryption while being robust against (injected) bit failures.

Umam, E.G., Sriramb, E.G..  2014.  Robust encryption algorithm based SHT in wireless sensor networks. Information Communication and Embedded Systems (ICICES), 2014 International Conference on. :1-5.

In bound applications, the locations of events reportable by a device network have to be compelled to stay anonymous. That is, unauthorized observers should be unable to notice the origin of such events by analyzing the network traffic. The authors analyze 2 forms of downsides: Communication overhead and machine load problem. During this paper, the authors give a new framework for modeling, analyzing, and evaluating obscurity in device networks. The novelty of the proposed framework is twofold: initial, it introduces the notion of "interval indistinguishability" and provides a quantitative live to model obscurity in wireless device networks; second, it maps supply obscurity to the applied mathematics downside the authors showed that the present approaches for coming up with statistically anonymous systems introduce correlation in real intervals whereas faux area unit unrelated. The authors show however mapping supply obscurity to consecutive hypothesis testing with nuisance Parameters ends up in changing the matter of exposing non-public supply data into checking out associate degree applicable knowledge transformation that removes or minimize the impact of the nuisance data victimization sturdy cryptography algorithmic rule. By doing therefore, the authors remodeled the matter of analyzing real valued sample points to binary codes, that opens the door for committal to writing theory to be incorporated into the study of anonymous networks. In existing work, unable to notice unauthorized observer in network traffic. However this work in the main supported enhances their supply obscurity against correlation check, the most goal of supply location privacy is to cover the existence of real events.