Biblio

Vehicular Ad-hoc Networks (VANETs) is a very fast emerging research area these days due to their contribution in designing Intelligent transportation systems (ITS). ITS is a well-organized group of wireless networks. It is a derived class of Mobile Ad-hoc Networks (MANETs). VANET is an instant-formed ad-hoc network, due to the mobility of vehicles on the road. The goal of using ITS is to enhance road safety, driving comfort, and traffic effectiveness by alerting the drivers at right time about upcoming dangerous situations, traffic jams, road diverted, weather conditions, real-time news, and entertainment. We can consider Vehicular communication as an enabler for future driverless cars. For these all above applications, it is necessary to make a threat-free environment to establish secure, fast, and efficient communication in VANETs. In this paper, we had discussed the overviews, characteristics, securities, applications, and various data dissemination techniques in VANET.

Internet of Battlefield Things (IoBT) is the application of Internet of Things (IoT) to a battlefield environment. IoBT networks operate in difficult conditions due to high mobility and unpredictable nature of battle fields and securing them is a challenge. There is increasing interest to use deception techniques to enhance the security of IoBT networks. A honeypot is a system installed on a network as a trap to attract the attention of an attacker and it does not store any valuable data. In this work, we introduce IoBT dual sensor gateways. We propose a Reinforcement Learning (RL)-assisted scheme, in which the IoBT dual sensor gateways intelligently switch between honeypot and real function based on a threshold. The optimal threshold is determined using reinforcement learning approach that adapts to nodes reputation. To focus on the impact of the mobile and uncertain behavior of IoBT networks on the proposed scheme, we consider the nodes as moving vehicles. We statistically analyze the results of our RL-based scheme obtained using ns-3 network simulation, and optimize value of the threshold.

This paper integrates Software-Defined Networking (SDN) and Information -Centric Networking (ICN) framework to enable low latency-based stateful routing and caching management by leveraging a novel forwarding and caching strategy. The framework is implemented in a clean- slate environment that does not rely on the TCP/IP principle. It utilizes Pending Interest Tables (PIT) instead of Forwarding Information Base (FIB) to perform data dissemination among peers in the proposed IC-SDN framework. As a result, all data exchanged and cached in the system are organized in chunks with the same interest resulting in reduced packet overhead costs. Additionally, we propose an efficient caching strategy that leverages in- network caching and naming of contents through an IC-SDN controller to support off- path caching. The testbed evaluation shows that the proposed IC-SDN implementation achieves an increased throughput and reduced latency compared to the traditional information-centric environment, especially in the high load scenarios.

Smart cities comprise multiple critical infrastructures, two of which are the power grid and communication networks, backed by centralized data analytics and storage. To effectively model the interdependencies between these infrastructures and enable a greater understanding of how communities respond to and impact them, large amounts of varied, real-world data on residential and commercial consumer energy consumption, load patterns, and associated human behavioral impacts are required. The dissemination of such data to the research communities is, however, largely restricted because of security and privacy concerns. This paper creates an opportunity for the development and dissemination of synthetic energy consumption data which is inherently anonymous but holds similarities to the properties of real data. This paper explores a framework using mixture density network (MDN) model integrated with a multi-layered Long Short-Term Memory (LSTM) network which shows promise in this area of research. The model is trained using an initial sample recorded from residential smart meters in the state of Florida, and is used to generate fully synthetic energy consumption data. The synthesized data will be made publicly available for interested users.

Securing wireless communication is significant for privacy and confidentiality of sensing data in Cyber-Physical Systems (CPS). However, due to broadcast nature of radio channels, disseminating sensory data is vulnerable to eavesdropping and message modification. Generating secret keys by extracting the shared randomness in a wireless fading channel is a promising way to improve the communication security. In this poster, we present a novel secret key generation protocol for securing real-time data dissemination in CPS, where the sensor nodes cooperatively generate a shared key by estimating the quantized fading channel randomness. A 2-hop wireless sensor network testbed is built and preliminary experimental results show that the quantization intervals and distance between the nodes lead to a secret bit mismatch.

Cloud-assisted Internet of Vehicles (IoV)which merges the advantages of both cloud computing and Internet of Things that can provide numerous online services, and bring lots of benefits and conveniences to the connected vehicles. However, the security and privacy issues such as confidentiality, access control and driver privacy may prevent it from being widely utilized for message dissemination. Existing attribute-based message encryption schemes still bring high computational cost to the lightweight vehicles. In this paper, we introduce a secure and privacy-preserving dissemination scheme for warning message in cloud-assisted IoV. Firstly, we adopt attribute-based encryption to protect the disseminated warning message, and present a verifiable encryption and decryption outsourcing construction to reduce the computational overhead on vehicles. Secondly, we present a conditional privacy preservation mechanism which utilizes anonymous identity-based signature technique to ensure anonymous vehicle authentication and message integrity checking, and also allows the trusted authority to trace the real identity of malicious vehicle. We further achieve batch verification to improve the authentication efficiency. The analysis indicate that our scheme gains more security properties and reduces the computational overhead on the vehicles.

Vehicular ad hoc network (VANET) has recently become one of the highly active research areas for wireless networking. Since VANET is a multi-hop wireless network with very high mobility and intermittent connection lifetime, it is important to effectively handle the data dissemination issue in this rapidly changing environment. However, the existing TCP/IP implementation may not fit into such a highly dynamic environment because the nodes in the network must often perform rerouting due to their inconsistency of connectivity. In addition, the drivers in the vehicles may want to acquire some data, but they do not know the address/location of such data storage. Hence, the named data networking (NDN) approach may be more desirable here. The NDN architecture is proposed for the future Internet, which focuses on the delivering mechanism based on the message contents instead of relying on the host addresses of the data. In this paper, a new protocol named roadside unit (RSU) assisted of named data network (RA-NDN) is presented. The RSU can operate as a standalone node [standalone RSU (SA-RSU)]. One benefit of deploying SA-RSUs is the improved network connectivity. This study uses the NS3 and SUMO software packages for the network simulator and traffic simulator software, respectively, to verify the performance of the RA-NDN protocol. To reduce the latency under various vehicular densities, vehicular transmission ranges, and number of requesters, the proposed approach is compared with vehicular NDN via a real-world data set in the urban area of Sathorn road in Bangkok, Thailand. The simulation results show that the RA-NDN protocol improves the performance of ad hoc communications with the increase in data received ratio and throughput and the decrease in total dissemination time and traffic load.

One of the challenges in supplying the communities with wider access to scientific databases is the need for knowledge of database languages like Structured Query Language (SQL). Although the SQL language has been published in many forms, not everybody is able to write SQL queries. Another challenge is that it might not be practical to make the public aware of the structure of databases. There is a need for novice users to query relational databases using their natural language. To solve this problem, many natural language interfaces to structured databases have been developed. The goal is to provide a more intuitive method for generating database queries and delivering responses. Through social media, which makes it possible to interact with a wide section of the population, and with the help of natural language processing, researchers at the Atmospheric Radiation Measurement (ARM) Data Center at Oak Ridge National Laboratory (ORNL) have developed a concept to enable easy search and retrieval of data from several environmental data centers for the scientific community through social media.Using a machine learning framework that maps natural language text to thousands of datasets, instruments, variables, and data streams, the prototype system would allow users to request data through Twitter and receive a link (via tweet) to applicable data results on the project's search catalog tailored to their key words. This automated identification of relevant data from various petascale archives at ORNL could increase convenience, access, and use of the project's data by the broader community. In this paper we discuss how some data-intensive projects at ORNL are using innovative ways to help in data discovery.

The internet paradigm was designed to forward packets from host-to-host. But nowadays the focal point has moved to data. The Internet Centric Network (ICN) provides architectures to meet this requirement. The Content Centric Network (CCN) is the most widely used ICN architecture. Information Centric Network's ability to perform in-network caching lead to faster retrieval of data on subsequent request. Although latency is solved, caching in a router makes it vulnerable to attacks that focus on the cache. One such attack is content poisoning, that will fill the router with poisoned content making the end user difficult to retrieve original valid data. In this paper, we propose a solution to mitigate content poisoning attack that will consume minimum time and require minimal storage overhead during the verification process.

Automation of real time car parking system (RTCPS) using mobile cloud computing (MCC) and vehicular networking (VN) has given rise to a novel concept of integrated communication-computing platforms (ICCP). The aim of ICCP is to evolve an effective means of addressing challenges such as improper parking management scheme, traffic congestion in parking lots, insecurity of vehicles (safety applications), and other Infrastructure-to-Vehicle (I2V) services for providing data dissemination and content delivery services to connected Vehicular Clients (VCs). Edge (parking lot based) Fog computing (EFC) through road side sensor based monitoring is proposed to achieve ICCP. A real-time cloud to vehicular clients (VCs) in the context of smart car parking system (SCPS) which satisfies deterministic and non-deterministic constraints is introduced. Vehicular cloud computing (VCC) and intra-Edge-Fog node architecture is presented for ICCP. This is targeted at distributed mini-sized self-energized Fog nodes/data centers, placed between distributed remote cloud and VCs. The architecture processes data-disseminated real-time services to the connected VCs. The work built a prototype testbed comprising a black box PSU, Arduino IoT Duo, GH-311RT ultrasonic distance sensor and SHARP 2Y0A21 passive infrared sensor for vehicle detection; LinkSprite 2MP UART JPEG camera module, SD card module, RFID card reader, RDS3115 metal gear servo motors, FPM384 fingerprint scanner, GSM Module and a VCC web portal. The testbed functions at the edge of the vehicular network and is connected to the served VCs through Infrastructure-to-Vehicular (I2V) TCP/IP-based single-hop mobile links. This research seeks to facilitate urban renewal strategies and highlight the significance of ICCP prototype testbed. Open challenges and future research directions are discussed for an efficient VCC model which runs on networked fog centers (NetFCs).