Visible to the public Biblio

Found 1565 results

Filters: First Letter Of Last Name is D  [Clear All Filters]
2020
Seneviratne, Piyumi, Perera, Dilanka, Samarasekara, Harinda, Keppitiyagama, Chamath, Thilakarathna, Kenneth, De Soyza, Kasun, Wijesekara, Primal.  2020.  Impact of Video Surveillance Systems on ATM PIN Security. 2020 20th International Conference on Advances in ICT for Emerging Regions (ICTer). :59–64.
ATM transactions are verified using two-factor authentication. The PIN is one of the factors (something you know) and the ATM Card is the other factor (something you have). Therefore, banks make significant investments on PIN Mailers and HSMs to preserve the security and confidentiality in the generation, validation, management and the delivery of the PIN to their customers. Moreover, banks install surveillance cameras inside ATM cubicles as a physical security measure to prevent fraud and theft. However, in some cases, ATM PIN-Pad and the PIN entering process get revealed through the surveillance camera footage itself. We demonstrate that visibility of forearm movements is sufficient to infer PINs with a significant level of accuracy. Video footage of the PIN entry process simulated in an experimental setup was analyzed using two approaches. The human observer-based approach shows that a PIN can be guessed with a 30% of accuracy within 3 attempts whilst the computer-assisted analysis of footage gave an accuracy of 50%. The results confirm that ad-hoc installation of surveillance cameras can weaken ATM PIN security significantly by potentially exposing one factor of a two-factor authentication system. Our investigation also revealed that there are no guidelines, standards or regulations governing the placement of surveillance cameras inside ATM cubicles in Sri Lanka.
Wang, H., Zeng, X., Lei, Y., Ren, S., Hou, F., Dong, N..  2020.  Indoor Object Identification based on Spectral Subtraction of Acoustic Room Impulse Response. 2020 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC). :1–4.
Object identification in the room environment is a key technique in many advanced engineering applications such as the unidentified object recognition in security surveillance, human identification and barrier recognition for AI robots. The identification technique based on the sound field perturbation analysis is capable of giving immersive identification which avoids the occlusion problem in the traditional vision-based method. In this paper, a new insight into the relation between the object and the variation of the sound field is presented. The sound field difference before and after the object locates in the environment is analyzed using the spectral subtraction based on the room impulse response. The spectral subtraction shows that the energy loss caused by the sound absorption is the essential factor which perturbs the sound field. By using the energy loss with high uniqueness as the extracted feature, an object identification technique is constructed under the classical supervised pattern recognition framework. The experiment in a real room validates that the system has high identification accuracy. In addition, based on the feature property of position insensitivity, this technique can achieve high identifying accuracy with a quite small training data set, which demonstrates that the technique has potential to be used in real engineering applications.
Korać, D., Damjanović, B., Simić, D..  2020.  Information Security in M-learning Systems: Challenges and Threats of Using Cookies. 2020 19th International Symposium INFOTEH-JAHORINA (INFOTEH). :1—6.
The trend of rapid development of mobile technologies has highlighted new challenges and threats regarding the information security by the using cookies in mobile learning (m-learning) systems. In order to overcome these challenges and threats, this paper has identified two main objectives. First, to give a review of most common types to cookies and second, to consider the challenges and threats regarding cookies with aspects that are directly related to issues of security and privacy. With these objectives is possible to bridge security gaps in m-learning systems. Moreover, the identified potential challenges and threats are discussed with the given proposals of pragmatic solutions for their mitigating or reducing. The findings of this research may help students to rise security awareness and security behavior in m-learning systems, and to better understand on-going security challenges and threats in m-learning systems.
Dinh, N., Tran, M., Park, Y., Kim, Y..  2020.  An Information-centric NFV-based System Implementation for Disaster Management Services. 2020 International Conference on Information Networking (ICOIN). :807–810.
When disasters occur, they not only affect the human life. Therefore, communication in disaster management is very important. During the disaster recovery phase, the network infrastructure may be partially fragmented and mobile rescue operations may involve many teams with different roles which can dynamically change. Therefore, disaster management services require high flexibility both in terms of network infrastructure management and rescue group communication. Existing studies have shown that IP-based or traditional telephony solutions are not well-suited to deal with such flexible group communication and network management due to their connection-oriented communication, no built-in support for mobile devices, and no mechanism for network fragmentation. Recent studies show that information-centric networking offers scalable and flexible communication based on its name-based interest-oriented communication approach. However, considering the difficulty of deploying a new service on the existing network, the programmability and virtualization of the network are required. This paper presents our implementation of an information-centric disaster management system based on network function virtualization (vICSNF). We show a proof-of-concept system with a case study for Seoul disaster management services. The system achieves flexibility both in terms of network infrastructure management and rescue group communication. Obtained testbed results show that vICSNF achieves a low communication overhead compared to the IP-based approach and the auto-configuration of vICSNFs enables the quick deployment for disaster management services in disaster scenarios.
Klann, D., Aftowicz, M., Kabin, I., Dyka, Z., Langendoerfer, P..  2020.  Integration and Implementation of four different Elliptic Curves in a single high-speed Design considering SCA. 2020 15th Design Technology of Integrated Systems in Nanoscale Era (DTIS). :1–2.
Modern communication systems rely heavily on cryptography to ensure authenticity, confidentiality and integrity of exchanged messages. Elliptic Curve Cryptography 1 (ECC) is one of the common used standard methods for encrypting and signing messages. In this paper we present our implementation of a design supporting four different NIST Elliptic Curves. The design supports two B-curves (B-233, B-283) and two P-curves (P-224, P-256). The implemented designs are sharing the following hardware components bus, multiplier, alu and registers. By implementing the 4 curves in a single design and reusing some resources we reduced the area 20 by 14% compared to a design without resource sharing. Compared to a pure software solution running on an Arm Cortex A9 operating at 1GHz, our design ported to a FPGA is 1.2 to 6 times faster.
K, S., Devi, K. Suganya, Srinivasan, P., Dheepa, T., Arpita, B., singh, L. Dolendro.  2020.  Joint Correlated Compressive Sensing based on Predictive Data Recovery in WSNs. 2020 International Conference on Emerging Trends in Information Technology and Engineering (ic-ETITE). :1–5.
Data sampling is critical process for energy constrained Wireless Sensor Networks. In this article, we proposed a Predictive Data Recovery Compressive Sensing (PDR-CS) procedure for data sampling. PDR-CS samples data measurements from the monitoring field on the basis of spatial and temporal correlation and sparse measurements recovered at the Sink. Our proposed algorithm, PDR-CS extends the iterative re-weighted -ℓ1(IRW - ℓ1) minimization and regularization on the top of Spatio-temporal compressibility for enhancing accuracy of signal recovery and reducing the energy consumption. The simulation study shows that from the less number of samples are enough to recover the signal. And also compared with the other compressive sensing procedures, PDR-CS works with less time.
Goudos, S. K., Diamantoulakis, P. D., Boursianis, A. D., Papanikolaou, V. K., Karagiannidis, G. K..  2020.  Joint User Association and Power Allocation Using Swarm Intelligence Algorithms in Non-Orthogonal Multiple Access Networks. 2020 9th International Conference on Modern Circuits and Systems Technologies (MOCAST). :1–4.
In this paper, we address the problem of joint user association and power allocation for non-orthogonal multiple access (NOMA) networks with multiple base stations (BSs). A user grouping procedure into orthogonal clusters, as well as an allocation of different physical resource blocks (PRBs) is considered. The problem of interest is mathematically described using the maximization of the weighted sum rate. We apply two different swarm intelligence algorithms, namely, the recently introduced Grey Wolf Optimizer (GWO), and the popular Particle Swarm Optimization (PSO), in order to solve this problem. Numerical results demonstrate that the above-described problem can be satisfactorily addressed by both algorithms.
Das, Debayan, Nath, Mayukh, Ghosh, Santosh, Sen, Shreyas.  2020.  Killing EM Side-Channel Leakage at its Source. 2020 IEEE 63rd International Midwest Symposium on Circuits and Systems (MWSCAS). :1108—1111.
Side-channel analysis (SCA) is a big threat to the security of connected embedded devices. Over the last few years, physical non-invasive SCA attacks utilizing the electromagnetic (EM) radiation (EM side-channel `leakage') from a crypto IC has gained huge momentum owing to the availability of the low-cost EM probes and development of the deep-learning (DL) based profiling attacks. In this paper, our goal is to understand the source of the EM leakage by analyzing a white-box modeling of the EM leakage from the crypto IC, leading towards a low-overhead generic countermeasure. To kill this EM leakage from its source, the solution utilizes a signature attenuation hardware (SAH) encapsulating the crypto core locally within the lower metal layers such that the critical correlated crypto current signature is significantly attenuated before it passes through the higher metal layers to connect to the external pin. The protection circuit utilizing AES256 as the crypto core is fabricated in 65nm process and shows for the first time the effects of metal routing on the EM leakage. The \textbackslashtextgreater 350× signature attenuation of the SAH together with the local lower metal routing ensured that the protected AES remains secure even after 1B measurements for both EM and power SCA, which is an 100× improvement over the state-of-the-art with comparable overheads. Overall, with the combination of the 2 techniques - signature suppression and local lower metal routing, we are able to kill the EM side-channel leakage at its source such that the correlated signature is not passed through the top-level metals, MIM capacitors, or on-board inductors, which are the primary sources of EM leakage, thereby preventing EM SCA attacks.
Diamanti, Alessio, Vilchez, José Manuel Sanchez, Secci, Stefano.  2020.  LSTM-based radiography for anomaly detection in softwarized infrastructures. 2020 32nd International Teletraffic Congress (ITC 32). :28–36.
Legacy and novel network services are expected to be migrated and designed to be deployed in fully virtualized environments. Starting with 5G, NFV becomes a formally required brick in the specifications, for services integrated within the infrastructure provider networks. This evolution leads to deployment of virtual resources Virtual-Machine (VM)-based, container-based and/or server-less platforms, all calling for a deep virtualization of infrastructure components. Such a network softwarization also unleashes further logical network virtualization, easing multi-layered, multi-actor and multi-access services, so as to be able to fulfill high availability, security, privacy and resilience requirements. However, the derived increased components heterogeneity makes the detection and the characterization of anomalies difficult, hence the relationship between anomaly detection and corresponding reconfiguration of the NFV stack to mitigate anomalies. In this article we propose an unsupervised machine-learning data-driven approach based on Long-Short- Term-Memory (LSTM) autoencoders to detect and characterize anomalies in virtualized networking services. With a radiography visualization, this approach can spot and describe deviations from nominal parameter values of any virtualized network service by means of a lightweight and iterative mean-squared reconstruction error analysis of LSTM-based autoencoders. We implement and validate the proposed methodology through experimental tests on a vIMS proof-of-concept deployed using Kubernetes.
Dong, D., Ye, Z., Su, J., Xie, S., Cao, Y., Kochan, R..  2020.  A Malware Detection Method Based on Improved Fireworks Algorithm and Support Vector Machine. 2020 IEEE 15th International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering (TCSET). :846–851.
The increasing of malwares has presented a serious threat to the security of computer systems in recent years. Traditional signature-based anti-virus systems are not able to detect metamorphic and previously unseen malwares and it inspires people to use machine learning methods such as Naive Bayes and Decision Tree to identity malicious executables. Among these methods, detecting malwares by using Support Vector Machine (SVM) is one of the most effective approaches. However, the parameters of SVM have serious impacts on its classification performance. In order to find the optimal parameter combination and avoid the problem of falling into local optimal solution, many methods based on evolutionary algorithms are proposed, including Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Differential Evolution (DE) and others. But these algorithms still face the problem of being trapped into local solution spaces in different degree. In this paper, an improved fireworks algorithm is presented and applied to search parameters of SVM: penalty factor c and kernel function parameter g. To research the performance of the proposed algorithm, numeric experiments are made and compared with some typical algorithms, the experimental results demonstrate it outperforms other algorithms.
Davis, B., Glenski, M., Sealy, W., Arendt, D..  2020.  Measure Utility, Gain Trust: Practical Advice for XAI Researchers. 2020 IEEE Workshop on TRust and EXpertise in Visual Analytics (TREX). :1–8.
Research into the explanation of machine learning models, i.e., explainable AI (XAI), has seen a commensurate exponential growth alongside deep artificial neural networks throughout the past decade. For historical reasons, explanation and trust have been intertwined. However, the focus on trust is too narrow, and has led the research community astray from tried and true empirical methods that produced more defensible scientific knowledge about people and explanations. To address this, we contribute a practical path forward for researchers in the XAI field. We recommend researchers focus on the utility of machine learning explanations instead of trust. We outline five broad use cases where explanations are useful and, for each, we describe pseudo-experiments that rely on objective empirical measurements and falsifiable hypotheses. We believe that this experimental rigor is necessary to contribute to scientific knowledge in the field of XAI.
Gupta, K., Hajika, R., Pai, Y. S., Duenser, A., Lochner, M., Billinghurst, M..  2020.  Measuring Human Trust in a Virtual Assistant using Physiological Sensing in Virtual Reality. 2020 IEEE Conference on Virtual Reality and 3D User Interfaces (VR). :756–765.
With the advancement of Artificial Intelligence technology to make smart devices, understanding how humans develop trust in virtual agents is emerging as a critical research field. Through our research, we report on a novel methodology to investigate user's trust in auditory assistance in a Virtual Reality (VR) based search task, under both high and low cognitive load and under varying levels of agent accuracy. We collected physiological sensor data such as electroencephalography (EEG), galvanic skin response (GSR), and heart-rate variability (HRV), subjective data through questionnaire such as System Trust Scale (STS), Subjective Mental Effort Questionnaire (SMEQ) and NASA-TLX. We also collected a behavioral measure of trust (congruency of users' head motion in response to valid/ invalid verbal advice from the agent). Our results indicate that our custom VR environment enables researchers to measure and understand human trust in virtual agents using the matrices, and both cognitive load and agent accuracy play an important role in trust formation. We discuss the implications of the research and directions for future work.
Mahamat, A. D., Ali, A., Tanguier, J. L., Donnot, A., Benelmir, R..  2020.  Mechanical and thermophysical characterization of local clay-based building materials. 2020 5th International Conference on Renewable Energies for Developing Countries (REDEC). :1–6.
The work we present is a comparative study based on an experimental approach to the mechanical and thermal properties of different local clay-based building materials with the incorporation of agricultural waste in Chad. These local building materials have been used since ancient times by the low-income population. They were the subject of a detailed characterization of their mechanical and thermal parameters. The objective is to obtain lightweight materials with good thermomechanical performance and which can contribute to improving thermal comfort, energy-saving, and security in social housing in Chad while reducing the cost of investment. Several clay-based samples with increasing incorporation of 0 to 8% of agricultural waste (cow dung or millet pod) were made. We used appropriate experimental methods for porous materials (the hydraulic press for mechanical tests and the box method for thermal tests). In this article, we have highlighted the values and variations of the mechanical compressive resistances, thermal conductivities, and thermal resistances of test pieces made with these materials. Knowing the mechanical and thermal characteristics, we also carried out a thermomechanical study. The thermal data made it possible to make Dynamic Thermal Simulations (STD) of the buildings thanks to the Pléiades + COMFIE software. The results obtained show that the use of these materials in a building presents good mechanical and thermal performance with low consumption of electrical energy for better thermal comfort of the occupants. Thus agricultural waste can be recovered thanks to its integration into building materials based on clay.
Guerrini, F., Dalai, M., Leonardi, R..  2020.  Minimal Information Exchange for Secure Image Hash-Based Geometric Transformations Estimation. IEEE Transactions on Information Forensics and Security. 15:3482—3496.
Signal processing applications dealing with secure transmission are enjoying increasing attention lately. This paper provides some theoretical insights as well as a practical solution for transmitting a hash of an image to a central server to be compared with a reference image. The proposed solution employs a rigid image registration technique viewed in a distributed source coding perspective. In essence, it embodies a phase encoding framework to let the decoder estimate the transformation parameters using a very modest amount of information about the original image. The problem is first cast in an ideal setting and then it is solved in a realistic scenario, giving more prominence to low computational complexity in both the transmitter and receiver, minimal hash size, and hash security. Satisfactory experimental results are reported on a standard images set.
Majhi, D., Rao, M., Sahoo, S., Dash, S. P., Mohapatra, D. P..  2020.  Modified Grey Wolf Optimization(GWO) based Accident Deterrence in Internet of Things (IoT) enabled Mining Industry. 2020 International Conference on Computer Science, Engineering and Applications (ICCSEA). :1–4.
The occurrences of accidents in mining industries owing to the fragile health conditions of mine workers are reportedly increasing. Health conditions measured as heart rate or pulse, glycemic index, and blood pressure are often crucial parameters that lead to failure in proper reasoning when not within acceptable ranges. These parameters, such as heartbeat rate can be measured continuously using sensors. The data can be monitored remotely and, when found to be of concern, can send necessary alarms to the mine manager. The early alarm notification enables the mine manager with better preparedness for managing the reach of first aid to the accident spot and thereby reduce mine fatalities drastically. This paper presents a framework for deterring accidents in mines with the help of the Grey Wolf Optimization approach.
Boato, G., Dang-Nguyen, D., Natale, F. G. B. De.  2020.  Morphological Filter Detector for Image Forensics Applications. IEEE Access. 8:13549—13560.
Mathematical morphology provides a large set of powerful non-linear image operators, widely used for feature extraction, noise removal or image enhancement. Although morphological filters might be used to remove artifacts produced by image manipulations, both on binary and gray level documents, little effort has been spent towards their forensic identification. In this paper we propose a non-trivial extension of a deterministic approach originally detecting erosion and dilation of binary images. The proposed approach operates on grayscale images and is robust to image compression and other typical attacks. When the image is attacked the method looses its deterministic nature and uses a properly trained SVM classifier, using the original detector as a feature extractor. Extensive tests demonstrate that the proposed method guarantees very high accuracy in filtering detection, providing 100% accuracy in discriminating the presence and the type of morphological filter in raw images of three different datasets. The achieved accuracy is also good after JPEG compression, equal or above 76.8% on all datasets for quality factors above 80. The proposed approach is also able to determine the adopted structuring element for moderate compression factors. Finally, it is robust against noise addition and it can distinguish morphological filter from other filters.
Dilshan, D., Piumika, S., Rupasinghe, C., Perera, I., Siriwardena, P..  2020.  MSChain: Blockchain based Decentralized Certificate Transparency for Microservices. 2020 Moratuwa Engineering Research Conference (MERCon). :1–6.
Microservices architecture has become one of the most prominent software architectures in the software development processes due to its features such as scalability, maintainability, resilience, and composability. It allows developing business applications in a decentralized manner by dividing the important business logic into separate independent services. Digital certificates are used to verify the identity of microservices in most cases. However, the certificate authorities (CA) who issue the certificates to microservices cannot be trusted always since they can issue certificates without the consent of the relevant microservice. Nevertheless, existing implementations of certificate transparency are mostly centralized and has the vulnerability of the single point of failure. The distributed ledger technologies such as blockchain can be used to achieve decentralized nature in certificate transparency implementations. A blockchain-based decentralized certificate transparency system specified for microservices architecture is proposed in this paper to ensure secure communication among services. After the implementation and deployment in a cloud service, the system expressed average certificate querying time of 643 milliseconds along with the highly secured service provided.
Aski, Vidyadhar, Dhaka, Vijaypal Singh, Kumar, Sunil, Parashar, Anubha, Ladagi, Akshata.  2020.  A Multi-Factor Access Control and Ownership Transfer Framework for Future Generation Healthcare Systems. 2020 Sixth International Conference on Parallel, Distributed and Grid Computing (PDGC). :93–98.
The recent advancements in ubiquitous sensing powered by Wireless Computing Technologies (WCT) and Cloud Computing Services (CCS) have introduced a new thinking ability amongst researchers and healthcare professionals for building secure and connected healthcare systems. The integration of Internet of Things (IoT) in healthcare services further brings in several challenges with it, mainly including encrypted communication through vulnerable wireless medium, authentication and access control algorithms and ownership transfer schemes (important patient information). Major concern of such giant connected systems lies in creating the data handling strategies which is collected from the billions of heterogeneous devices distributed across the hospital network. Besides, the resource constrained nature of IoT would make these goals difficult to achieve. Motivated by aforementioned deliberations, this paper introduces a novel approach in designing a security framework for edge-computing based connected healthcare systems. An efficient, multi-factor access control and ownership transfer mechanism for edge-computing based futuristic healthcare applications is the core of proposed framework. Data scalability is achieved by employing distributed approach for clustering techniques that analyze and aggregate voluminous data acquired from heterogeneous devices individually before it transits the to the cloud. Moreover, data/device ownership transfer scheme is considered to be the first time in its kind. During ownership transfer phase, medical server facilitates user to transfer the patient information/ device ownership rights to the other registered users. In order to avoid the existing mistakes, we propose a formal and informal security analysis, that ensures the resistance towards most common IoT attacks such as insider attack, denial of distributed service (DDoS) attack and traceability attacks.
Marechal, Emeline, Donnet, Benoit.  2020.  Network Fingerprinting: Routers under Attack. 2020 IEEE European Symposium on Security and Privacy Workshops (EuroS PW). :594–599.
Nowadays, simple tools such as traceroute can be used by attackers to acquire topology knowledge remotely. Worse still, attackers can use a lightweight fingerprinting technique, based on traceroute and ping, to retrieve the routers brand, and use that knowledge to launch targeted attacks. In this paper, we show that the hardware ecosystem of network operators can greatly vary from one to another, with all potential security implications it brings. Indeed, depending on the autonomous system (AS), not all brands play the same role in terms of network connectivity. An attacker could find an interest in targeting a specific hardware vendor in a particular AS, if known defects are present in this hardware, and if the AS relies heavily on it for forwarding its traffic.
Kamal, A., Dahshan, H., Elbayoumy, A. D..  2020.  A New Homomorphic Message Authentication Code Scheme for Network Coding. 2020 3rd International Conference on Information and Computer Technologies (ICICT). :520—524.
Network coding (NC) can significantly increase network performance and make lossy networks more reliable. Since the middle nodes modify the packets during their path to destination, integrity of the original packets cannot be checked using classical methods (MACs, Signatures, etc). Though, pollution attacks are the most common threat to network coded systems, where an infected node can inject the data flow of a network with a number of false packets and ban the receiver from properly decoding the packets. A lot of work in the security of NC in resisting pollution attacks has been investigated in recent years, majority have the same security parameter 1/q. A Homomorphic MAC scheme is presented earlier to resist pollution attacks with a security level 1/qˆl, In this paper, we will show that the mentioned scheme is subject to known-plaintext attacks. This is due to that part of the key can be revealed in an initial process. Also, the whole key could be revealed if the key is used more than once. Then, a modification to the mentioned scheme is proposed to overcome this issue. Besides, the MAC length is adjustable according to the required security level and not variable according to the vector's length which will accordingly increase the performance and efficiency of the scheme.
Ibrahim, A. A., Ata, S. Özgür, Durak-Ata, L..  2020.  Performance Analysis of FSO Systems over Imperfect Málaga Atmospheric Turbulence Channels with Pointing Errors. 2020 12th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP). :1–5.
In this study, we investigate the performance of FSO communication systems under more realistic channel model considering atmospheric turbulence, pointing errors and channel estimation errors together. For this aim, we first derived the composite probability density function (PDF) of imperfect Málaga turbulence channel with pointing errors. Then using this PDF, we obtained bit-error-rate (BER) and ergodic channel capacity (ECC) expressions in closed forms. Additionally, we present the BER and ECC metrics of imperfect Gamma-Gamma and K turbulence channels with pointing errors as special cases of Málaga channel. We further verified our analytic results through Monte-Carlo simulations.
Padala, S. K., D'Souza, J..  2020.  Performance of Spatially Coupled LDPC Codes over Underwater Acoustic Communication Channel. 2020 National Conference on Communications (NCC). :1–5.
Underwater acoustic (UWA) channel is complex because of its multipath environment, Doppler shift and rapidly changing characteristics. Many of the UWA communication- based applications demand high data rates and reliable communication. The orthogonal frequency division multiplexing (OFDM) system is very effective in UWA channels and provides high data rate with low equalization complexity. It is a challenging task to achieve reliability over these channels. The low-density parity-check (LDPC) codes give a better error performance than turbo codes, for UWA channels. The spatially-coupled low-density parity-check (SC-LDPC) codes have been shown to have the capacity-achieving performance over terrestrial communication. In this paper, we have studied by simulation, the performance of protograph based SC-LDPC codes over shallow water acoustic environment with a communication range of 1000 m and channel bandwidth of 10 KHz. Our results show that SC-LDPC codes give 1 dB performance improvement over LDPC codes at a Bit Error Rate (BER) of 10-3 for the same latency constraints.
Ding, K., Meng, Z., Yu, Z., Ju, Z., Zhao, Z., Xu, K..  2020.  Photonic Compressive Sampling of Sparse Broadband RF Signals using a Multimode Fiber. 2020 Asia Communications and Photonics Conference (ACP) and International Conference on Information Photonics and Optical Communications (IPOC). :1–3.
We propose a photonic compressive sampling scheme based on multimode fiber for radio spectrum sensing, which shows high accuracy and stability, and low complexity and cost. Pulse overlapping is utilized for a fast detection. © 2020 The Author(s).
Ditton, S., Tekeoglu, A., Bekiroglu, K., Srinivasan, S..  2020.  A Proof of Concept Denial of Service Attack Against Bluetooth IoT Devices. 2020 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops). :1—6.
Bluetooth technologies have widespread applications in personal area networks, device-to-device communications and forming ad hoc networks. Studying Bluetooth devices security is a challenging task as they lack support for monitor mode available with other wireless networks (e.g. 802.11 WiFi). In addition, the frequency-hoping spread spectrum technique used in its operation necessitates special hardware and software to study its operation. This investigation examines methods for analyzing Bluetooth devices' security and presents a proof-of-concept DoS attack on the Link Manager Protocol (LMP) layer using the InternalBlue framework. Through this study, we demonstrate a method to study Bluetooth device security using existing tools without requiring specialized hardware. Consequently, the methods proposed in the paper can be used to study Bluetooth security in many applications.
Anupadma, S., Dharshini, B. S., Roshini, S., K, J. Singh.  2020.  Random selective block encryption technique for image cryptography using chaotic cryptography. 2020 International Conference on Emerging Trends in Information Technology and Engineering (ic-ETITE). :1–5.
Dynamic random growth technique and a hybrid chaotic map which is proposed in this paper are used to perform block-based image encryption. The plaintext attack can easily crack the cat map, as it is periodic, and therefore cat map securely used in which it can eliminate the cyclical occurrence and withstand the plaintext attack's effect. The diffusion process calculates the intermediate parameters according to the image block. For the generation of the random data stream in the chaotic map, we use an intermediate parameter as an initial parameter. In this way, the generated data stream depends on the plain text image that can withstand the attack on plain text. The experimental results of this process prove that the proposed dynamic random growth technique and a hybrid chaotic map for image encryption is a secured one in which it can be used in secured image transmission systems.