Showing papers by "International Institute of Information Technology, Hyderabad published in 2020"
TL;DR: A new secure remote user authentication scheme for a smart home environment that is efficient for resource-constrained smart devices with limited resources as it uses only one-way hash functions, bitwise XOR operations and symmetric encryptions/decryptions.
Abstract: The Information and Communication Technology (ICT) has been used in wide range of applications, such as smart living, smart health and smart transportation. Among all these applications, smart home is most popular, in which the users/residents can control the operations of the various smart sensor devices from remote sites also. However, the smart devices and users communicate over an insecure communication channel, i.e., the Internet. There may be the possibility of various types of attacks, such as smart device capture attack, user, gateway node and smart device impersonation attacks and privileged-insider attack on a smart home network. An illegal user, in this case, can gain access over data sent by the smart devices. Most of the existing schemes reported in the literature for the remote user authentication in smart home environment are not secure with respect to the above specified attacks. Thus, there is need to design a secure remote user authentication scheme for a smart home network so that only authorized users can gain access to the smart devices. To mitigate the aforementioned isses, in this paper, we propose a new secure remote user authentication scheme for a smart home environment. The proposed scheme is efficient for resource-constrained smart devices with limited resources as it uses only one-way hash functions, bitwise XOR operations and symmetric encryptions/decryptions. The security of the scheme is proved using the rigorous formal security analysis under the widely-accepted Real-Or-Random (ROR) model. Moreover, the rigorous informal security analysis and formal security verification using the broadly-accepted Automated Validation of Internet Security Protocols and Applications (AVISPA) tool is also done. Finally, the practical demonstration of the proposed scheme is also performed using the widely-accepted NS-2 simulation.
253 citations
TL;DR: This work investigates the problem of lip-syncing a talking face video of an arbitrary identity to match a target speech segment, and identifies key reasons pertaining to this and hence resolves them by learning from a powerful lip-sync discriminator.
Abstract: In this work, we investigate the problem of lip-syncing a talking face video of an arbitrary identity to match a target speech segment. Current works excel at producing accurate lip movements on a static image or videos of specific people seen during the training phase. However, they fail to accurately morph the lip movements of arbitrary identities in dynamic, unconstrained talking face videos, resulting in significant parts of the video being out-of-sync with the new audio. We identify key reasons pertaining to this and hence resolve them by learning from a powerful lip-sync discriminator. Next, we propose new, rigorous evaluation benchmarks and metrics to accurately measure lip synchronization in unconstrained videos. Extensive quantitative evaluations on our challenging benchmarks show that the lip-sync accuracy of the videos generated by our Wav2Lip model is almost as good as real synced videos. We provide a demo video clearly showing the substantial impact of our Wav2Lip model and evaluation benchmarks on our website: \url{this http URL}. The code and models are released at this GitHub repository: \url{this http URL}. You can also try out the interactive demo at this link: \url{this http URL}.
251 citations
TL;DR: A new cloud based user authentication scheme for secure authentication of medical data that provides the session-key security and protects active attacks and a detailed comparative analysis for the communication and computation costs along with security and functionality features which proves its efficiency in comparison to the other existing schemes of its category.
Abstract: Security and privacy are the major concerns in cloud computing as users have limited access on the stored data at the remote locations managed by different service providers. These become more challenging especially for the data generated from the wearable devices as it is highly sensitive and heterogeneous in nature. Most of the existing techniques reported in the literature are having high computation and communication costs and are vulnerable to various known attacks, which reduce their importance for applicability in real-world environment. Hence, in this paper, we propose a new cloud based user authentication scheme for secure authentication of medical data. After successful mutual authentication between a user and wearable sensor node, both establish a secret session key that is used for future secure communications. The extensively-used Real-Or-Random (ROR) model based formal security analysis and the broadly-accepted Automated Validation of Internet Security Protocols and Applications (AVISPA) tool based formal security verification show that the proposed scheme provides the session-key security and protects active attacks. The proposed scheme is also informally analyzed to show its resilience against other known attacks. Moreover, we have done a detailed comparative analysis for the communication and computation costs along with security and functionality features which proves its efficiency in comparison to the other existing schemes of its category.
185 citations
TL;DR: A new lightweight authentication mechanism in cloud-based IoT environment, called LAM-CIoT, which offers better security, and low communication and computation overheads as compared to the closely related authentication schemes.
166 citations
TL;DR: A new efficient lightweight blockchain-enabled radio frequency identification (RFID)-based authentication protocol for supply chains in 5G mobile edge computing environment, called LBRAPS, which is based on bitwise exclusive-or (XOR), one-way cryptographic hash and bitwise rotation operations only.
Abstract: Secure real-time data about goods in transit in supply chains needs bandwidth having capacity that is not fulfilled with the current infrastructure. Hence, 5G-enabled Internet of Things (IoT) in mobile edge computing is intended to substantially increase this capacity. To deal with this issue, in this article, we design a new efficient lightweight blockchain-enabled radio frequency identification (RFID)-based authentication protocol for supply chains in 5G mobile edge computing environment, called lightweight blockchain-enabled RFID-based authentication protocol (LBRAPS). LBRAPS is based on bitwise exclusive-or (XOR), one-way cryptographic hash and bitwise rotation operations only. LBRAPS is shown to be secure against various attacks. Moreover, the simulation-based formal security verification using the broadly-accepted Automated Validation of Internet Security Protocols and Applications (AVISPA) tool assures that LBRAPS is secure. Finally, it is shown that LBRAPS has better trade-off among its security and functionality features, communication and computation costs as compared to those for existing protocols.
147 citations
TL;DR: This paper introduces a blockchain-based access control scheme in the IoD environment that allows secure communication among the drones, and also among therones and the G S S and provides all sorts of security analysis including formal security under the random oracle model, informal security and simulation-based formal security verification.
135 citations
TL;DR: A novel blockchain enabled authentication key agreement protocol for IoMT environment, called BAKMP-IoMT, which provides secure key management between implantable medical devices and personal servers and betweenpersonal servers and cloud servers and needs low communication and computational costs as compared to other schemes.
Abstract: The Internet of Medical Things (IoMT) is a kind of connected infrastructure of smart medical devices along with software applications, health systems and services. These medical devices and applications are connected to healthcare systems through the Internet. The Wi-Fi enabled devices facilitate machine-to-machine communication and link to the cloud platforms for data storage. IoMT has the ability to make accurate diagnoses, with fewer mistakes and lower costs of care. IoMT with smartphone applications permits the patients to exchange their health related confidential and private information to the healthcare experts (i.e., doctors) for the better control of diseases, and also for tracking and preventing chronic illnesses. Due to insecure communication among the entities involved in IoMT, an attacker can tamper with the confidential and private health related information for example an attacker can not only intercept the messages, but can also modify, delete or insert malicious messages during communication. To deal this sensitive issue, we design a novel blockchain enabled authentication key agreement protocol for IoMT environment, called BAKMP-IoMT. BAKMP-IoMT provides secure key management between implantable medical devices and personal servers and between personal servers and cloud servers. The legitimate users can also access the healthcare data from the cloud servers in a secure way. The entire healthcare data is stored in a blockchain maintained by the cloud servers. A detailed formal security including the security verification of BAKMP-IoMT using the widely-accepted Automated Validation of Internet Security Protocols and Applications (AVISPA) tool is performed to demonstrate its resilience against the different types of possible attack. The comparison of BAKMP-IoMT with relevant existing schemes is conducted which identifies that the proposed system furnishes better security and functionality, and also needs low communication and computational costs as compared to other schemes. Finally, the simulation of BAKMP-IoMT is conducted to demonstrate its impact on the performance parameters.
128 citations
TL;DR: A new blokchain based secure framework for data management among IoD communication entities is proposed and analyzed that has ability to resist several potential attacks that are essential in IoT-enabled IoD environment and also provides less communication and computation overheads.
Abstract: The Internet of Drones (IoD) is widely used in a wide range of applications from military to civilian applications from the past years. However, during communication either with the control room/ground station server(s) or moving access points in the sky, security and privacy is one the crucial issues which needs to be tackled efficiently. In this direction, blokchain technology can be one of the viable solutions due to the immutability and traceability of various transactions and decentralized nature. In this paper, we provide in-depth challenges and issues of applicability of blokchain in 5G-based Internet of Things (IoT)-enabled IoD environment. We propose and analyze a new blokchain based secure framework for data management among IoD communication entities. The proposed scheme has ability to resist several potential attacks that are essential in IoT-enabled IoD environment. A detailed comparative analysis exhibits that the proposed scheme offers better security and functionality requirements, and also provides less communication and computation overheads as compared to other related schemes.
127 citations
TL;DR: A novel ASMC methodology is proposed which does not require a priori bounded uncertainty, and a general class of Euler–Lagrange systems is taken as a case study to show the applicability of the proposed design.
127 citations
TL;DR: A new lightweight hash-chain-based and forward secure authentication scheme for wireless body area networks in health-care IoT that is secure against various known attacks obliged for WBANs, and it supports more security features compared to related schemes.
118 citations
TL;DR: The forecasting results across all five buildings validate the robustness of the proposed deep learning framework for the short-term building-level electrical load forecasting tasks, and the formulated methods are found to be robust against weather forecasting errors.
TL;DR: A new authentication scheme related to the cloud-assisted CPS in two directions, which provides high security as compared to other related works and is shown to be efficient in terms of communication and computation costs asCompared to those for other related existing schemes.
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TL;DR: Although the existing models perform reasonably well on certain types of questions, there is large performance gap compared to human performance (94.36% accuracy).
Abstract: We present a new dataset for Visual Question Answering (VQA) on document images called DocVQA. The dataset consists of 50,000 questions defined on 12,000+ document images. Detailed analysis of the dataset in comparison with similar datasets for VQA and reading comprehension is presented. We report several baseline results by adopting existing VQA and reading comprehension models. Although the existing models perform reasonably well on certain types of questions, there is large performance gap compared to human performance (94.36% accuracy). The models need to improve specifically on questions where understanding structure of the document is crucial. The dataset, code and leaderboard are available at this http URL
TL;DR: This work proposes a new user authenticated key agreement scheme in which only authorized users can access the services from the designated IoT sensing devices installed in the IIoT environment, and carries out the formal security analysis using the broadly accepted Real-Or-Random (ROR) model and also the non-mathematical (informal) security analysis on the proposed scheme.
Abstract: With an exponential increase in the popularity of Internet, the real-time data collected by various smart sensing devices can be analyzed remotely by a remote user (e.g., a manager) in the Industrial Internet of Things (IIoT). However, in the IIoT environment, the gathered real-time data is transmitted over the public channel, which raises the issues of security and privacy in this environment. Therefore, to protect illegal access by an adversary, user authentication mechanism is one of the promising security solutions in the IIoT environment. To achieve this goal, we propose a new user authenticated key agreement scheme in which only authorized users can access the services from the designated IoT sensing devices installed in the IIoT environment. In the proposed scheme, fuzzy extractor technique is used for biometric verification. Moreover, three factors, namely smart card, password and personal biometrics of a legal registered user are applied in the proposed scheme to increase the level of security in the system. The proposed scheme supports new devices addition after initial deployment of the devices, password/biometric change phase and also smart card revocation phase in case the smart card is lost or stolen by an adversary. In addition, the proposed scheme is lightweight in nature. We carry out the formal security analysis using the broadly accepted Real-Or-Random (ROR) model and also the non-mathematical (informal) security analysis on the proposed scheme. Furthermore, the formal security verification using the popularly-used AVISPA (Automated Validation of Internet Security Protocols and Applications) tool is carried out on the proposed scheme. The detailed security analysis assures that the proposed scheme can withstand several well-known attacks in the IIoT environment. A practical demonstration using the NS2 simulation study is also performed for the proposed scheme and other related existing schemes. Also, a detailed comparative study shows that the proposed scheme is efficient, and provides superior security in comparison to the other schemes.
TL;DR: A critical literature survey of recent intrusion detection protocols for IoT and WSN environments along with their comparative analysis is provided and a taxonomy of security and privacy-preservation protocols in WSN and IoT is highlighted.
Abstract: As we all know that the technology is projected to be next to humans very soon because of its holistic growth. Now-a-days, we see a lot of applications that are making our lives comfortable such as smart cars, smart homes, smart traffic management, smart offices, smart medical consultation, smart cities, etc. All such facilities are in the reach of a common man because of the advancement in Information and Communications Technology (ICT). Because of this advancement, new computing and communication environment such as Internet of Things (IoT) came into picture. Lot of research work is in progress in IoT domain which helps for the overall development of the society and makes the lives easy and comfortable. But in the resource constrained environment of Wireless Sensor Network (WSN) and IoT, it is almost inconceivable to establish a fully secure system. As we are moving forward very fast, technology is becoming more and more vulnerable to the security threats. In future, the number of Internet connected people will be less than the smart objects so we need to prepare a robust system for keeping the above mentioned environments safe and standardized it for the smooth conduction of communication among IoT objects. In this survey paper, we provide the details of threat model applicable for the security of WSN and IoT based communications. We also discuss the security requirements and various attacks possible in WSN and IoT based communication environments. The emerging projects of WSNs integrated to IoT are also briefed. We then provide the details of different architectures of WSN and IoT based communication environments. Next, we discuss the current issues and challenges related to WSN and IoT. We also provide a critical literature survey of recent intrusion detection protocols for IoT and WSN environments along with their comparative analysis. A taxonomy of security and privacy-preservation protocols in WSN and IoT is also highlighted. Finally, we discuss some research challenges which need to be addressed in the coming future.
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TL;DR: A transfer learning model is proposed to automate the process of identifying the people who are not wearing mask and outperformed the other recently proposed approaches by achieving an accuracy of 99.9% during training and 100% during testing.
Abstract: The world is facing a huge health crisis due to the rapid transmission of coronavirus (COVID-19). Several guidelines were issued by the World Health Organization (WHO) for protection against the spread of coronavirus. According to WHO, the most effective preventive measure against COVID-19 is wearing a mask in public places and crowded areas. It is very difficult to monitor people manually in these areas. In this paper, a transfer learning model is proposed to automate the process of identifying the people who are not wearing mask. The proposed model is built by fine-tuning the pre-trained state-of-the-art deep learning model, InceptionV3. The proposed model is trained and tested on the Simulated Masked Face Dataset (SMFD). Image augmentation technique is adopted to address the limited availability of data for better training and testing of the model. The model outperformed the other recently proposed approaches by achieving an accuracy of 99.9% during training and 100% during testing.
12 Oct 2020
TL;DR: Wav2Lip as mentioned in this paper proposes a powerful lip-sync discriminator to resolve the problem of significant parts of the video being out-of-sync with the new audio.
Abstract: In this work, we investigate the problem of lip-syncing a talking face video of an arbitrary identity to match a target speech segment. Current works excel at producing accurate lip movements on a static image or videos of specific people seen during the training phase. However, they fail to accurately morph the lip movements of arbitrary identities in dynamic, unconstrained talking face videos, resulting in significant parts of the video being out-of-sync with the new audio. We identify key reasons pertaining to this and hence resolve them by learning from a powerful lip-sync discriminator. Next, we propose new, rigorous evaluation benchmarks and metrics to accurately measure lip synchronization in unconstrained videos. Extensive quantitative evaluations on our challenging benchmarks show that the lip-sync accuracy of the videos generated by our Wav2Lip model is almost as good as real synced videos. We provide a demo video clearly showing the substantial impact of our Wav2Lip model, and also publicly release the code, models, and evaluation benchmarks on our website.
TL;DR: The security of CSUAC-IoT under the real-or-random (ROR) model is proved, and it is demonstrated that it can resist several common attacks found in a typical IoT environment using the AVISPA tool.
Abstract: User access control is a crucial requirement in any Internet of Things (IoT) deployment, as it allows one to provide authorization, authentication, and revocation of a registered legitimate user to access real-time information and/or service directly from the IoT devices. To complement the existing literature, we design a new three-factor certificateless-signcryption-based user access control for the IoT environment (CSUAC-IoT). Specifically, in our scheme, a user $U$ ’s password, personal biometrics, and mobile device are used as the three authentication factors. By executing the login and access control phase of CSUAC-IoT, a registered user $(U)$ and a designated smart device $(S_{i})$ can authorize and authenticate mutually via the trusted gateway node (GN) in a particular cell of the IoT environment. In our setting, the environment is partitioned into disjoint cells, and each cell will contain a certain number of IoT devices along with a GN. With the established session key between $U$ and $S_{i}$ , both entities can then communicate securely. In addition, CSUAC-IoT supports new IoT devices deployment, user revocation, and password/biometric update functionality features. We prove the security of CSUAC-IoT under the real-or-random (ROR) model, and demonstrate that it can resist several common attacks found in a typical IoT environment using the AVISPA tool. A comparative analysis also reveals that CSUAC-IoT achieves better tradeoff for security and functionality, and computational and communication costs, in comparison to five other competing approaches.
TL;DR: The creation of the real prototype of the smart container, the development of the waste management application and a real-scale experiment use case show that the proposed system can efficiently change the way people deal with their garbage and optimize economic and material resources.
Abstract: Global industry is undergoing major transformations with the genesis of a new paradigm known as the Internet of Things (IoT) with its underlying technologies. Many company leaders are investing more effort and money in transforming their services to capitalize on the benefits provided by the IoT. Thereby, the decision makers in public waste management do not want to be outdone, and it is challenging to provide an efficient and real-time waste management system. This paper proposes a solution (hardware, software, and communications) that aims to optimize waste management and include a citizen in the process. The system follows an IoT-based approach where the discarded waste from the smart bin is continuously monitored by sensors that inform the filling level of each compartment, in real-time. These data are stored and processed in an IoT middleware providing information for collection with optimized routes and generating important statistical data for monitoring the waste collection accurately in terms of resource management and the provided services for the community. Citizens can easily access information about the public waste bins through the Web or a mobile application. The creation of the real prototype of the smart container, the development of the waste management application and a real-scale experiment use case for evaluation, demonstration, and validation show that the proposed system can efficiently change the way people deal with their garbage and optimize economic and material resources.
TL;DR: The proposed scheme is shown to be highly secure against a passive/active adversary through various security analysis, such as random oracle based formal security, formal security verification via automated simulation tool, and also informal security analysis.
Abstract: In the Internet of Vehicles (IoV), secure information sharing among vehicles is crucial in order to upgrade driving safety as well as to strengthen vehicular services. However, public communication among vehicles leads to various potential attacks, such as replay, man-in-the-middle, impersonation, unlinkability and traceability attacks. To address this issue, we design a new conditional privacy preserving batch verification-based authentication mechanism in the IoV environment using Elliptic Curve Cryptography $(ECC)$ technique, where a vehicle can authenticate its neighbor vehicle and also a Road-Side Unit $(RSU)$ can authenticate its nearby vehicles in a batch. The proposed scheme is shown to be highly secure against a passive/active adversary through various security analysis, such as random oracle based formal security, formal security verification via automated simulation tool, and also informal security analysis. An exhaustive comparative analysis reveals that the proposed scheme offers better security and functionality attributes, and comparable storage, communication and computation overheads when these are compared with the relevant schemes.
TL;DR: Various security aspects, threats and attacks, network and threat models related to the IoV environment are discussed, and a taxonomy of security protocols is given that is essential to provide IoV data security.
Abstract: Internet of Vehicles (IoV) is treated as an extension of Vehicle-to-Vehicle (V2V) communication network. IoV helps in enhancing driving aids with the help of vehicle Artificial Intelligence (AI) awareness of other vehicles and their actions. IoV is connected in an adhoc networking environment which utilizes each vehicle in the network as a node, called Vehicular Ad Hoc Network (VANET), where the vehicles may be also connected to the public Internet. It is specifically important for the autonomous vehicles because they can instantaneously communicate with other vehicles surrounding them. In addition, safely avoiding accident prone zones is crucial in order to continue secure and smart transportation. Since the communication among various entities involved in the IoV environment is via open channel, it gives an opportunity to a passive/active adversary to intercept, modify, delete or even insert fake information during communication. It is then a serious concern for the vehicles users to determine whether the received information is genuine. In this survey paper, various security aspects, threats and attacks, network and threat models related to the IoV environment are discussed. Next, a taxonomy of security protocols is given that is essential to provide IoV data security. In particular, focus on various authentication protocols is given that is needed for mutual authentication among the involved entities in the IoV environment for secure communication. A detailed comparative analysis among various state-of-art authentication protocols proposed in the related IoV environment is provided to show their effectiveness as well as security and functionality features. Moreover, some testbeds are described that were designed and implemented for the IoV environment. In addition, some future challenges for IoV security protocols are also highlighted that are necessary to address in the future.
TL;DR: In this paper, the relative abundance of tree palms in tropical and subtropical moist forests was quantified to help improve understanding of tropical forests and reduce uncertainty about these ecosystems under climate change.
Abstract: Aim: Palms are an iconic, diverse and often abundant component of tropical ecosystems that provide many ecosystem services. Being monocots, tree palms are evolutionarily, morphologically and physiologically distinct from other trees, and these differences have important consequences for ecosystem services (e.g., carbon sequestration and storage) and in terms of responses to climate change. We quantified global patterns of tree palm relative abundance to help improve understanding of tropical forests and reduce uncertainty about these ecosystems under climate change. Location: Tropical and subtropical moist forests. Time period: Current. Major taxa studied: Palms (Arecaceae). Methods: We assembled a pantropical dataset of 2,548 forest plots (covering 1,191 ha) and quantified tree palm (i.e., ≥10 cm diameter at breast height) abundance relative to co-occurring non-palm trees. We compared the relative abundance of tree palms across biogeographical realms and tested for associations with palaeoclimate stability, current climate, edaphic conditions and metrics of forest structure. Results: On average, the relative abundance of tree palms was more than five times larger between Neotropical locations and other biogeographical realms. Tree palms were absent in most locations outside the Neotropics but present in >80% of Neotropical locations. The relative abundance of tree palms was more strongly associated with local conditions (e.g., higher mean annual precipitation, lower soil fertility, shallower water table and lower plot mean wood density) than metrics of long-term climate stability. Life-form diversity also influenced the patterns; palm assemblages outside the Neotropics comprise many non-tree (e.g., climbing) palms. Finally, we show that tree palms can influence estimates of above-ground biomass, but the magnitude and direction of the effect require additional work. Conclusions: Tree palms are not only quintessentially tropical, but they are also overwhelmingly Neotropical. Future work to understand the contributions of tree palms to biomass estimates and carbon cycling will be particularly crucial in Neotropical forests.
Karlsruhe Institute of Technology1, Universidade Federal de Santa Catarina2, German-Jordanian University3, Sultan Qaboos University4, Bandung Institute of Technology5, Bauhaus University, Weimar6, University of Southampton7, Cardiff University8, Massachusetts Institute of Technology9, Khalifa University10, University of Tehran11, Ahmadu Bello University12, Heidelberg University13, Tsinghua University14, University of Southern California15, Yonsei University16, VU University Amsterdam17, University of Adelaide18, University of Seville19, Wrocław University of Technology20, Indian Institute of Technology Madras21, Eindhoven University of Technology22, University of Cuenca23, International Institute of Information Technology, Hyderabad24, Tabriz Islamic Art University25, Universiti Malaysia Sabah26, Augsburg University of Applied Sciences27, Aalborg University28, University College London29, Chalmers University of Technology30, Coventry University31, University of Sydney32, University of Copenhagen33, Technical University of Denmark34, Malaviya National Institute of Technology, Jaipur35, University of Oregon36, National Taichung University of Science and Technology37, Shahid Bahonar University of Kerman38, University of the Bío Bío39, University of Koblenz and Landau40, Instituto Politécnico Nacional41, University of California, Berkeley42, The Chinese University of Hong Kong43, Imo State University44, Uganda Martyrs University45, Santa Catarina Federal Institute of Education, Science and Technology46, University of Moratuwa47, Kaiserslautern University of Technology48, University of Concepción49, RMIT University50, Tokyo City University51, Shahid Beheshti University52, University of Wollongong53, Xi'an University of Architecture and Technology54
TL;DR: In this article, a large international collaborative questionnaire study was conducted in 26 countries, using 21 different languages, which led to a dataset of 8225 questionnaires, and significant differences appeared between groups of participants in their perception of the scales, both in relation to distances of the anchors and relationships between scales.
TL;DR: This paper presents a secure and efficient authentication protocol based on three-factor authentication by taking advantage of biometrics and uses a honey_list technique to protect against brute force and stolen smartcard attacks.
Abstract: The Internet of Thing (IoT) is useful for connecting and collecting variable data of objects through the Internet, which makes to generate useful data for humanity. An indispensable enabler of IoT is the wireless sensor networks (WSNs). Many environments, such as smart healthcare, smart transportation and smart grid, have adopted WSN. Nonetheless, WSNs remain vulnerable to variety of attacks because they send and receive data over public channels. Moreover, the performance of IoT enabled sensor devices has limitations since the sensors are lightweight devices and are resource constrained. To overcome these problems, many security authentication protocols for WSNs have been proposed. However, many researchers have pointed out that preventing smartcard stolen and off-line guessing attacks is an important security issue, and guessing identity and password at the same time is still possible. To address these weaknesses, this paper presents a secure and efficient authentication protocol based on three-factor authentication by taking advantage of biometrics. Meanwhile, the proposed protocol uses a honey_list technique to protect against brute force and stolen smartcard attacks. By using the honey_list technique and three factors, the proposed protocol can provide security even if two of the three factors are compromised. Considering the limited performance of the sensors, we propose an efficient protocol using only hash functions excluding the public key based elliptic curve cryptography. For security evaluation of the proposed authentication protocol, we perform informal security analysis, and Real-Or-Random (ROR) model-based and Burrows Abadi Needham (BAN) logic based formal security analysis. We also perform the formal verification using the widely-used Automated Validation of Internet Security Protocols and Applications (AVISPA) simulation software. Besides, compared to previous researches, we demonstrate that our proposed authentication protocol for WSNs systems is more suitable and secure than others.
01 Apr 2020
TL;DR: It is observed that Ensemble and Hybrid models with neural networks and SVM are being more adopted for credit scoring, NPA prediction and fraud detection, and lack of comprehensive public datasets continue to be an area of concern for researchers.
Abstract: Credit risk is the risk of financial loss when a borrower fails to meet the financial commitment. While there are many factors that constitute credit risk, due diligence while giving loan (credit scoring), continuous monitoring of customer payments and other behaviour patterns could reduce the probability of accumulating non-performing assets (NPA) and frauds. In the past few years, the quantum of NPAs and frauds have gone up significantly, and therefore it has become imperative that banks and financial institutions use robust mechanisms to predict the performance of loans. The past two decades has seen an immense growth in the area of artificial intelligence, most notably machine learning (ML) with improved access to internet, data, and compute. Whilst there are credit rating agencies and credit scoring companies that provide their analysis of a customer to banks on a fee, the researchers continue to explore various ML techniques to improve the accuracy level of credit risk evaluation. In this survey paper, we performed a systematic literature review on existing research methods and ML techniques for credit risk evaluation. We reviewed a total of 136 papers on credit risk evaluation published between 1993 and March 2019. We studied the implications of hyper parameters on ML techniques being used to evaluate credit risk and, analyzed the limitations of the current studies and research trends. We observed that Ensemble and Hybrid models with neural networks and SVM are being more adopted for credit scoring, NPA prediction and fraud detection. We also realized that lack of comprehensive public datasets continue to be an area of concern for researchers.
23 Aug 2020
TL;DR: In this paper, the authors focus on tables that have complex structures, dense content, and varying layouts with no dependency on meta-features and/or optical character recognition (OCR) models.
Abstract: Tables are information-rich structured objects in document images. While significant work has been done in localizing tables as graphic objects in document images, only limited attempts exist on table structure recognition. Most existing literature on structure recognition depends on extraction of meta-features from the pdf document or on the optical character recognition (ocr) models to extract low-level layout features from the image. However, these methods fail to generalize well because of the absence of meta-features or errors made by the ocr when there is a significant variance in table layouts and text organization. In our work, we focus on tables that have complex structures, dense content, and varying layouts with no dependency on meta-features and/or ocr.
TL;DR: A secure authentication protocol for a cloud-assisted TMIS with access control using blockchain is proposed and it is shown that the proposed protocol provides more security and has better efficiency compared to related protocols.
Abstract: Telecare medical information system (TMIS) implemented in wireless body area network (WBAN) is convenient and time-saving for patients and doctors. TMIS is realized using wearable devices worn by a patient, and wearable devices generate patient health data and transmit them to a server through a public channel. Unfortunately, a malicious attacker can attempt performing various attacks through such a channel. Therefore, establishing a secure authentication process between a patient and a server is essential. Moreover, wearable devices have limited storage power. Cloud computing can be considered to resolve this problem by providing a storage service in the TMIS environment. In this environment, access control of the patient health data is essential for the quality of healthcare. Furthermore, the database of the cloud server is a major target for an attacker. The attacker can try to modify, forge, or delete the stored data. To resolve these problems, we propose a secure authentication protocol for a cloud-assisted TMIS with access control using blockchain. We employ ciphertext-policy attribute-based encryption (CP-ABE) to establish access control for health data stored in the cloud server, and apply blockchain to guarantee data integrity. To prove robustness of the proposed protocol, we conduct informal analysis and Burrows-Adabi-Needham (BAN) logic analysis, and we formally validate the proposed protocol using automated validation of internet security protocols and applications (AVISPA). Consequently, we show that the proposed protocol provides more security and has better efficiency compared to related protocols. Therefore, the proposed protocol is proper for a practical TMIS environment.
TL;DR: In this paper, the authors investigated an SO(10) grand unification scenario where a charge -1/3 scalar leptoquark (S-1) remains as the only new physics candidate at the TeV scale.
Abstract: Motivated by the R-D(*) anomalies, we investigate an SO(10) grand unification scenario where a charge -1/3 scalar leptoquark (S-1) remains as the only new physics candidate at the TeV scale. This l ...
TL;DR: A secure and efficient message authentication protocol for IoV in a smart city environment, called IoV-SMAP, which can resist security drawbacks and provide user anonymity, and mutual authentication is designed.
Abstract: With the emergence of the concept of smart city and the increasing demands for a range of vehicles, Internet of Vehicles (IoV) has achieved a lot of attention by providing multiple benefits, including vehicle emergence, accidents, levels of pollution, and traffic congestion. Moreover, IoV provides various services by combining vehicular ad-hoc networks (VANET) with the Internet of Things (IoT) in smart cities. However, the communication among vehicles is susceptible to various security threats because the sensitive message is transmitted via a insecure channel in the IoV-based smart city environment. Thus, a secure message authentication protocol is indispensable to ensure various services for IoV in a smart city environment. In 2020, a secure message authentication protocol for IoV communication in smart cities has been proposed. However, we discover that the analyzed scheme suffers from various potential attacks such as impersonation, secret key disclosure, and off-line guessing attacks, and also does not ensure authentication. To solve the security threats of the analyzed scheme, we design a secure and efficient message authentication protocol for IoV in a smart city environment, called IoV-SMAP. The proposed IoV-SMAP can resist security drawbacks and provide user anonymity, and mutual authentication. We demonstrate the security of IoV-SMAP by performing informal and formal analyses such as the Real-or-Random (ROR) model, and Automated Validation of Internet Security Protocols and Application (AVISPA) simulations. In addition, we compare the performance of IoV-SMAP with related existing competing authentication schemes. We demonstrate that IoV-SMAP provides better security along with efficiency than related competing schemes and is suitable for the IoV-based smart city environment.
TL;DR: LipGAN as discussed by the authors generates realistic talking faces from the translated audio, which can significantly improve the overall user experience for consuming and interacting with multimodal content across languages. But it is not suitable for the task of face-to-face translation.
Abstract: In light of the recent breakthroughs in automatic machine translation systems, we propose a novel approach that we term as "Face-to-Face Translation". As today's digital communication becomes increasingly visual, we argue that there is a need for systems that can automatically translate a video of a person speaking in language A into a target language B with realistic lip synchronization. In this work, we create an automatic pipeline for this problem and demonstrate its impact on multiple real-world applications. First, we build a working speech-to-speech translation system by bringing together multiple existing modules from speech and language. We then move towards "Face-to-Face Translation" by incorporating a novel visual module, LipGAN for generating realistic talking faces from the translated audio. Quantitative evaluation of LipGAN on the standard LRW test set shows that it significantly outperforms existing approaches across all standard metrics. We also subject our Face-to-Face Translation pipeline, to multiple human evaluations and show that it can significantly improve the overall user experience for consuming and interacting with multimodal content across languages. Code, models and demo video are made publicly available.
Demo video: this https URL
Code and models: this https URL