Biblio

To preserve anonymity and obfuscate their identity on online platforms users may morph their text and portray themselves as a different gender or demographic. Similarly, a chatbot may need to customize its communication style to improve engagement with its audience. This manner of changing the style of written text has gained significant attention in recent years. Yet these past research works largely cater to the transfer of single style attributes. The disadvantage of focusing on a single style alone is that this often results in target text where other existing style attributes behave unpredictably or are unfairly dominated by the new style. To counteract this behavior, it would be nice to have a style transfer mechanism that can transfer or control multiple styles simultaneously and fairly. Through such an approach, one could obtain obfuscated or written text incorporated with a desired degree of multiple soft styles such as female-quality, politeness, or formalness. To the best of our knowledge this work is the first that shows and attempt to solve the issues related to multiple style transfer. We also demonstrate that the transfer of multiple styles cannot be achieved by sequentially performing multiple single-style transfers. This is because each single style-transfer step often reverses or dominates over the style incorporated by a previous transfer step. We then propose a neural network architecture for fairly transferring multiple style attributes in a given text. We test our architecture on the Yelp dataset to demonstrate our superior performance as compared to existing one-style transfer steps performed in a sequence.

This paper reviews the definitions and characteristics of military effects, the Internet of Battlefield Things (IoBT), and their impact on decision processes in a Multi-Domain Operating environment (MDO). The aspects of contemporary military decision-processes are illustrated and an MDO Effect Loop decision process is introduced. We examine the concept of IoBT effects and their implications in MDO. These implications suggest that when considering the concept of MDO, as a doctrine, the technological advances of IoBTs empower enhancements in decision frameworks and increase the viability of novel operational approaches and options for military effects.

We present a machine-checked proof of security for the domain management protocol of Amazon Web Services' KMS (Key Management Service) a critical security service used throughout AWS and by AWS customers. Domain management is at the core of AWS KMS; it governs the top-level keys that anchor the security of encryption services at AWS. We show that the protocol securely implements an ideal distributed encryption mechanism under standard cryptographic assumptions. The proof is machine-checked in the EasyCrypt proof assistant and is the largest EasyCrypt development to date.

Statistics suggests, proceeding towards IoT generation, is increasing IoT devices at a drastic rate. This will be very challenging for our present-day network infrastructure to manage, this much of data. This may risk, both security and traffic collapsing. We have proposed an infrastructure with Fog Computing. The Fog layer consists two layers, using the concepts of Service oriented Architecture (SOA) and the Agent based composition model which ensures the traffic usage reduction. In order to have a robust and secured system, we have modified the Fog based agent model by replacing the SOA with secured Named Data Network (NDN) protocol. Knowing the fact that NDN has the caching layer, we are combining NDN and with Fog, as it can overcome the forwarding strategy limitation and memory constraints of NDN by the Agent Society, in the Middle layer along with Trust management.

Over the past few years, we have been witnessing the rise of misinformation on the Internet. People fall victims of fake news continuously, and contribute to their propagation knowingly or inadvertently. Many recent efforts seek to reduce the damage caused by fake news by identifying them automatically with artificial intelligence techniques, using signals from domain flag-lists, online social networks, etc. In this work, we present Check-It, a system that combines a variety of signals into a pipeline for fake news identification. Check-It is developed as a web browser plugin with the objective of efficient and timely fake news detection, while respecting user privacy. In this paper, we present the design, implementation and performance evaluation of Check-It. Experimental results show that it outperforms state-of-the-art methods on commonly-used datasets.

This paper introduces complex network into software clone detection and proposes a clone code detection method based on software complex network feature matching. This method has the following properties. It builds a software network model with many added features and codes written with different languages can be detected by a single method. It reduces the space of code comparison, and it searches similar subnetworks to detect clones without knowing any clone codes information. This method can be used in detecting open source code which has been reused in software for security analysis.

This paper considers one of the methods of efficient allocation of limited resources in special-purpose devices (sensors) to monitor complex network unit cybersecurity.

With more than a trillion web pages, there is a plethora of content available for consumption. Search Engine queries invariably lead to overwhelming information, parts of it relevant and some others irrelevant. Often the information provided can be conflicting, ambiguous, and inconsistent contributing to the loss of credibility of the content. In the past, researchers have proposed approaches for credibility assessment and enumerated factors influencing the credibility of web pages. In this work, we detailed a WEBCred framework for automated genre-aware credibility assessment of web pages. We developed a tool based on the proposed framework to extract web page features instances and identify genre a web page belongs to while assessing it's Genre Credibility Score ( GCS). We validated our approach on `Information Security' dataset of 8,550 URLs with 171 features across 7 genres. The supervised learning algorithm, Gradient Boosted Decision Tree classified genres with 88.75% testing accuracy over 10 fold cross-validation, an improvement over the current benchmark. We also examined our approach on `Health' domain web pages and had comparable results. The calculated GCS correlated 69% with crowdsourced Web Of Trust ( WOT) score and 13% with algorithm based Alexa ranking across 5 Information security groups. This variance in correlation states that our GCS approach aligns with human way ( WOT) as compared to algorithmic way (Alexa) of web assessment in both the experiments.

Technological advancements have made smartphones to provide wide range of applications that enable users to perform many of their tasks easily and conveniently, anytime and anywhere. For this reason, many users are tend to store their private data in their smart phones. Since conventional methods for security of smartphones, such as passwords, personal identification numbers, and pattern locks are prone to many attacks, this research paper proposes a novel method for authenticating smartphone users based on performing seven different daily physical activity as behavioral biometrics, using smartphone embedded sensor data. This authentication scheme builds a machine learning model which recognizes users by performing those daily activities. Experimental results demonstrate the effectiveness of the proposed framework.

Cyber attacks on transmission lines are one of the main challenges in security of smart grids. These targeted attacks, if not detected, might cause cascading problems in power systems. This paper proposes a bi-level mixed integer linear programming (MILP) optimization model for false data injection on targeted buses in a power system to overflow targeted transmission lines. The upper level optimization problem outputs the optimized false data injections on targeted load buses to overflow a targeted transmission line without violating bad data detection constraints. The lower level problem integrates the false data injections into the optimal power flow problem without violating the optimal power flow constraints. A few case studies are designed to validate the proposed attack model on IEEE 118-bus power system.

Mitigating the effect of Distributed Denial of Service (DDoS) attacks in wired/wireless networks is a problem of extreme importance. The present paper investigates this problem and proposes a secure AQM to encounter the effects of DDoS attacks on queue's router. The employed method relies on modelling the TCP/AQM system subjected to different DoS attack rate where the resulting closed-loop system is expressed as new Markovian Jump Linear System (MJLS). Sufficient delay-dependent conditions which guarantee the syntheses of a stabilizing control for the closed-loop system with a guaranteed cost J* are derived. Finally, a numerical example is displayed.

The need for performing deep neural network inferences on resource-constrained embedded devices (e.g., Internet of Things nodes) requires specialized architectures to achieve the best trade-off among performance, energy, and cost. One of the most promising architectures in this context is based on massive parallel and specialized cores interconnected by means of a Network-on-Chip (NoC). In this paper, we extensively evaluate NoC-based deep neural network accelerators by exploring the design space spanned by several architectural parameters including, network size, routing algorithm, local memory size, link width, and number of memory interfaces. We show how latency is mainly dominated by the on-chip communication whereas energy consumption is mainly accounted by memory (both on-chip and off-chip). The outcome of the analysis, thus, pushes toward a research line devoted to the optimization of the on-chip communication fabric and the memory subsystem for performance improvement and energy efficiency, respectively.

Mobile Ad-hoc NETwork (MANET) is a collection of mobile devices which interchange information without the use of predefined infrastructures or central administration. It is employed in many domains such as military and commercial sectors, data and sensors networks, low level applications, etc. The important constraints in this network are the limitation of bandwidth, processing capabilities and battery life. The choice of an effective routing protocol is primordial. From many routing protocols developed for MANET, OLSR protocol is a widely-used proactive routing protocol which diffuses topological information periodically. Thus, every node has a global vision of the entire network. The protocol assumes, like the other protocols, that the nodes cooperate in a trusted environment. So, all control messages are transmitted (HELLO messages) to all 1-hop neighbor nodes or broadcasted (TC and MID messages) to the entire network in clear. However, a node, which listens to OLSR control messages, can exploit this property to lead an attack. In this paper, we investigate on MultiPoint Relay (MPR) attack considered like one of the efficient OLSR attacks by using a simulation in progressive size gridMANET.

Mobile ad hoc network (MANET) does not have fixed infrastructure centralized server which manage the connections between the nodes. Rather, the nodes in MANET move randomly. Thus, it is risky to exchange data between nodes because there is a high possibility of having malicious node in the path. In this paper, we will describe a new authentication technique using message digest 5 (MD5), hashing for dynamic MANET on demand protocol (DYMO) based on reinforcement learning. In addition, we will describe an encryption technique that can be used without the need for a third party to distribute a secret key. After implementing the suggested model, results showed a remarkable enhancement in securing the path by increasing the packet delivery ratio and average throughput. On the other hand, there was an increase in end to end delay due to time spent in cryptographic operations.

Key management is critical for the successful operation of a cryptographic system in wireless networks. Systems based on asymmetric keys require a dedicated infrastructure for key management and authentication which may not be practical for ad-hoc Underwater Acoustic Networks (UANs). In symmetric-key systems, key distribution is not easy to handle when new nodes join the network. In addition, when a key is compromised all nodes that use the same key are not secure anymore. Hence, it is desirable to have a dynamic way to generate new keys without relying on past keys. Physical Layer Security (PLS) uses correlated channel measurements between two underwater nodes to generate a cryptographic key without exchanging the key itself. In this study, we set up a network of two legitimate nodes and one eavesdropper operating in a shallow area off the coast of Portugal. We propose novel features based on the Channel Impulse Response (CIR) of the established acoustic link that could be used as an initial seed for a crypto-key generation algorithm. Our results show that the two nodes can independently generate 306 quantization bits after exchanging 187 probe signals. Furthermore, the eavesdropper fails to generate the same bits from her/his data even if she/he performs exactly the same signal processing steps of the legitimate nodes.

Advances in new Communication and Information innovations has led to a new paradigm known as Internet of Things (IoT). Healthcare environment uses IoT technologies for Patients care which can be used in various medical applications. Patient information is encrypted consistently to maintain the access of therapeutic records by authoritative entities. Healthcare Internet of Things (HIoT) facilitate the access of Patient files immediately in emergency situations. In the proposed system, the Patient directly provides the Key to the Doctor in normal care access. In Emergency care, a Patient shares an Attribute based Key with a set of Emergency Supporting Representatives (ESRs) and access permission to the Doctor for utilizing Emergency key from ESR. The Doctor decrypts the medical records by using Attribute based key and Emergency key to save the Patient's life. The proposed model Secure Information Retrieval using Lightweight Cryptography (SIRLC) reduces the secret key generation time and cipher text size. The performance evaluation indicates that SIRLC is a better option to utilize in Healthcare IoT than Lightweight Break-glass Access Control(LiBAC) with enhanced security and reduced computational complexity.

Based on the Lyapunov stability theory, a novel adaptive synchronization method is proposed for three chaotic systems with different orders. Then the proposed method is applied to secure communication. This paper designs a novel multistage chaotic synchronized secure communication system in which the encrypted information signal is transmitted to the receiver after two chaotic masking, and then recovered at the synchronized receiver. Numerical results show the success in transmitting a continuous signal and a discrete signal through three synchronized systems.

Dependence of the individuals on the Internet for performing the several actions require secure data communication. Thus, the reliable data communication improves the confidentiality. As, enhanced security leads to reliable and faster communication. To improve the reliability and confidentiality, there is dire need of fully secured authentication method. There are several methods of password protections were introduced to protect the confidentiality and reliability. Most of the existing methods are based on alphanumeric approaches, but few methods provide the dual authentication process. In this paper, we introduce improved graphical password authentication using Twofish Encryption and Visual Cryptography (TEVC) method. Our proposed TEVC is unpredictably organized as predicting the correct graphical password and arranging its particles in the proper order is harder as compared to traditional alphanumeric password system. TEVC is tested by using JAVA platform. Based on the testing results, we confirm that proposed TEVC provides secure authentication. TEVC encryption algorithm detected as more prudent and possessing lower time complexity as compared to other known existing algorithms message code confirmation and fingerprint scan with password.

k-anonymity is a popular model in privacy preserving data publishing. It provides privacy guarantee when a microdata table is released. In microdata, sensitive attributes contain high-sensitive and low sensitive values. Unfortunately, study in anonymity for distributing sensitive value is still rare. This study aims to distribute evenly high-sensitive value to quasi identifier group. We proposed an approach called Simple Distribution of Sensitive Value. We compared our method with systematic clustering which is considered as very effective method to group quasi identifier. Information entropy is used to measure the diversity in each quasi identifier group and in a microdata table. Experiment result show our method outperformed systematic clustering when high-sensitive value is distributed.

Users can directly access and share information from portable devices such as a smartphone or an Internet of Things (IoT) device. However, to prevent them from becoming victims to launch cyber attacks, they must allow selective sharing based on roles of the users such as with the Ciphertext-Policy Attribute Encryption (CP-ABE) scheme. However, to match the resource constraints, the scheme must be efficient for storage. It must also protect the device from malicious users as well as allow uninterrupted access to valid users. This paper presents the CCA secure PROxy-based Scalable Revocation for Constant Cipher-text (C-PROSRCC) scheme, which provides scalable revocation for a constant ciphertext length CP-ABE scheme. The scheme has a constant number of pairings and computations. It can also revoke any number of users and does not require re-encryption or redistribution of keys. We have successfully implemented the C-PROSRCC scheme. The qualitative and quantitative comparison with related schemes indicates that C-PROSRCC performs better with acceptable overheads. C-PROSRCC is Chosen Ciphertext Attack (CCA) secure. We also present a case study to demonstrate the use of C-PROSRCC for mobile-based selective sharing of a family car.

This study proposed a biometric-based digital signature scheme proposed for facial recognition. The scheme is designed and built to verify the person’s identity during a registration process and retrieve their public and private keys stored in the database. The RSA algorithm has been used as asymmetric encryption method to encrypt hashes generated for digital documents. It uses the hash function (SHA-256) to generate digital signatures. In this study, local binary patterns histograms (LBPH) were used for facial recognition. The facial recognition method was evaluated on ORL faces retrieved from the database of Cambridge University. From the analysis, the LBPH algorithm achieved 97.5% accuracy; the real-time testing was done on thirty subjects and it achieved 94% recognition accuracy. A crypto-tool software was used to perform the randomness test on the proposed RSA and SHA256.

While recent studies have shed light on the expressivity, complexity and compositionality of convolutional networks, the real inductive bias of the family of functions reachable by gradient descent on natural data is still unknown. By exploiting symmetries in the preactivation space of convolutional layers, we present preliminary empirical evidence of regularities in the preimage of trained rectifier networks, in terms of arrangements of polytopes, and relate it to the nonlinear transformations applied by the network to its input.

Wireless Mesh Networks (WMN) are becoming inevitable in this world of high technology as it provides low cost access to broadband services. Moreover, the technologists are doing research to make WMN more reliable and secure. Subsequently, among wireless ad-hoc networking technologies, Bluetooth Low Energy (BLE) is gaining high degree of importance among researchers due to its easy availability in the gadgets and low power consumption. BLE started its journey from version 4.0 and announced the latest version 5 with mesh support capability. BLE being a low power and mesh supported technology is nowadays among the hot research topics for the researchers. Many of the researchers are working on BLE mesh technology to make it more efficient and smart. Apart from other variables of efficiency, like all communication networks, mesh network security is also of a great concern. In view of the aforesaid, this paper provides a comprehensive review on several works associated to the security in WMN and BLE mesh networks and the research related to the BLE security protocols. Moreover, after the detailed research on related works, this paper has discussed the pros and cons of the present developed mesh security mechanisms. Also, at the end after extracting the curx from the present research on WMN and BLE mesh security, this research study has devised some solutions as how to mitigate the BLE mesh network security lapses.

Over the past few years, virtual and mixed reality systems have evolved significantly yielding high immersive experiences. Most of the metaphors used for interaction with the virtual environment do not provide the same meaningful feedback, to which the users are used to in the real world. This paper proposes a cyber-glove to improve the immersive sensation and the degree of embodiment in virtual and mixed reality interaction tasks. In particular, we are proposing a cyber-glove system that tracks wrist movements, hand orientation and finger movements. It provides a decoupled position of the wrist and hand, which can contribute to a better embodiment in interaction and manipulation tasks. Additionally, the detection of the curvature of the fingers aims to improve the proprioceptive perception of the grasping/releasing gestures more consistent to visual feedback. The cyber-glove system is being developed for VR applications related to real estate promotion, where users have to go through divisions of the house and interact with objects and furniture. This work aims to assess if glove-based systems can contribute to a higher sense of immersion, embodiment and usability when compared to standard VR hand controller devices (typically button-based). Twenty-two participants tested the cyber-glove system against the HTC Vive controller in a 3D manipulation task, specifically the opening of a virtual door. Metric results showed that 83% of the users performed faster door pushes, and described shorter paths with their hands wearing the cyber-glove. Subjective results showed that all participants rated the cyber-glove based interactions as equally or more natural, and 90% of users experienced an equal or a significant increase in the sense of embodiment.

Cyber-physical systems (CPS) are state-of-the-art communication environments that offer various applications with distinct requirements. However, security in CPS is a nonnegotiable concept, since without a proper security mechanism the applications of CPS may risk human lives, the privacy of individuals, and system operations. In this paper, we focus on PHY-layer security approaches in CPS to prevent passive eavesdropping attacks, and we propose an integration of physical layer operations to enhance security. Thanks to the McEliece cryptosystem, error injection is firstly applied to information bits, which are encoded with the forward error correction (FEC) schemes. Golay and Hamming codes are selected as FEC schemes to satisfy power and computational efficiency. Then obtained codewords are transmitted across reliable intermediate relays to the legitimate receiver. As a performance metric, the decoding frame error rate of the eavesdropper is analytically obtained for the fragmentary existence of significant noise between relays and Eve. The simulation results validate the analytical calculations, and the obtained results show that the number of low-quality channels and the selected FEC scheme affects the performance of the proposed model.