Desynchronized Two-Dimensional Round-Robin Scheduler for Input Buffered

We propose a new arbitration algorithm, called the desynchronized two-dimensional round-robin (D2DRR), for input queued packet switches in which each input port maintains a separate logical queue for each output. D2DRR is an enhanced version of 2DRR, and thus improves fairness over 2DRR without a starvation problem. Iterative maximal matching schemes including iSLIP yield better throughput with more iterations. However, since many iterations require much time for arbitration, it is not desirable for high speed switching. Thus, D2DRR attempts to resolve contentions with less iterations, while yielding high throughput. The proposed arbitration algorithm is compared in terms of average cell latency with conventional algorithms, especially iSLIP and wrapped wave front arbitration (WWFA)

Blockchain and Interplanetary File System (IPFS)-Based Data Storage System for Vehicular Networks with Keyword Search Capability

Closed-circuit television (CCTV) cameras and black boxes are indispensable for road safety and accident management. Visible highway surveillance cameras can promote safe driving habits while discouraging moving violations. According to CCTV laws, footage captured by roadside cameras must be securely stored, and authorized persons can access it. Footages collected by CCTV and Blackbox are usually saved to the camera’s microSD card, the cloud, or hard drives locally but there are concerns about security and data integrity. These issues may be addressed by blockchain technology. The cost of storing data on the blockchain, on the other hand, is prohibitively expensive. We can have decentralized and cost-effective storage with the interplanetary file system (IPFS) project. It is a file-sharing protocol that stores and distributes data in a distributed file system. We propose a decentralized IPFS and blockchain-based application for distributed file storage. It is possible to upload various types of files into our decentralized application (DApp), and hashes of the uploaded files are permanently saved on the Ethereum blockchain with the help of smart contracts. Because it cannot be removed, it is immutable. By clicking on the file description, we can also view the file. DApp also includes a keyword search feature to assist us in quickly locating sensitive information. We used Ethers.js’ smart contract event listener and contract.queryFilter to filter and read data from the blockchain. The smart contract events are then written to a text file for our DApp’s keyword search functionality. Our experiment demonstrates that our DApp is resilient to system failure while preserving the transparency and integrity of data due to the immutability of blockchain

Trustworthy Event-Information Dissemination in Vehicular Ad Hoc Networks

In vehicular networks, trustworthiness of exchanged messages is very important since a fake message might incur catastrophic accidents on the road. In this paper, we propose a new scheme to disseminate trustworthy event information while mitigating message modification attack and fake message generation attack. Our scheme attempts to suppress those attacks by exchanging the trust level information of adjacent vehicles and using a two-step procedure. In the first step, each vehicle attempts to determine the trust level, which is referred to as truth-telling probability, of adjacent vehicles. The truth-telling probability is estimated based on the average of opinions of adjacent vehicles, and we apply a new clustering technique to mitigate the effect of malicious vehicles on this estimation by removing their opinions as outliers. Once the truth-telling probability is determined, the trustworthiness of a given message is determined in the second step by applying a modified threshold random walk (TRW) to the opinions of the majority group obtained in the first step. We compare our scheme with other schemes using simulation for several scenarios. The simulation results show that our proposed scheme has a low false decision probability and can efficiently disseminate trustworthy event information to neighboring vehicles in VANET

Decomposed Crossbar Switches with Multiple Input and Output Buffers

Conventional input switches usually employ a single crossbar switch fabric to transfer cells from input buffers to output ports. This type of switches suffer from input and output cell contention problems which cause lower performance than for output buffer switches. However, dividing one crossbar fabric into several smaller crossbar fabrics, we can decrease the input and output contention probabilities. Based on this principle, we propose a new decomposed crossbar switch architecture. Since a decrease in input and output contention probabilities causes an increase in the grant probability for the cells at input buffers, the proposed decomposed crossbar switches yield better performance than conventional input switches. We derive the grant probability for a simple arbitration algorithm and evaluate the performance of the proposed switch architecture in terms of the average cell latency through simulation

Security Issues with In-Vehicle Networks, and Enhanced Countermeasures Based on Blockchain

Modern vehicles are no longer simply mechanical devices. Connectivity between the vehicular network and the outside world has widened the security holes that hackers can use to exploit a vehicular network. Controller Area Network (CAN), FlexRay, and automotive Ethernet are popular protocols for in-vehicle networks (IVNs) and will stay in the industry for many more years. However, these protocols were not designed with security in mind. They have several vulnerabilities, such as lack of message authentication, lack of message encryption, and an ID-based arbitration mechanism for contention resolution. Adversaries can use these vulnerabilities to launch sophisticated attacks that may lead to loss of life and damage to property. Thus, the security of the vehicles should be handled carefully. In this paper, we investigate the security vulnerabilities with in-vehicle network protocols such as CAN, automotive Ethernet, and FlexRay. A comprehensive survey on security attacks launched against in-vehicle networks is presented along with countermeasures adopted by various researchers. Various algorithms have been proposed in the past for intrusion detection in IVNs. However, those approaches have several limitations that need special attention from the research community. Blockchain is a good approach to solving the existing security issues in IVNs, and we suggest a way to improve IVN security based on a hybrid blockchain

Challenges of Future VANET and Cloud-Based Approaches

Vehicular ad hoc networks (VANETs) have been studied intensively due to their wide variety of applications and services, such as passenger safety, enhanced traffic efficiency, and infotainment. With the evolution of technology and sudden growth in the number of smart vehicles, traditional VANETs face several technical challenges in deployment and management due to less flexibility, scalability, poor connectivity, and inadequate intelligence. Cloud computing is considered a way to satisfy these requirements in VANETs. However, next-generation VANETs will have special requirements of autonomous vehicles with high mobility, low latency, real-time applications, and connectivity, which may not be resolved by conventional cloud computing. Hence, merging of fog computing with the conventional cloud for VANETs is discussed as a potential solution for several issues in current and future VANETs. In addition, fog computing can be enhanced by integrating Software-Defined Network (SDN), which provides flexibility, programmability, and global knowledge of the network. We present two example scenarios for timely dissemination of safety messages in future VANETs based on fog and a combination of fog and SDN. We also explained the issues that need to be resolved for the deployment of three different cloud-based approaches

Scanner Detection Based on Connection Attempt Success Ratio with Guaranteed False Positive and False Negative Probabilities

Since the link rate is very high up to 40Gbps these days, scanning packets can spread very fast. At this high speed, only a small chance of missing on-going scanning activity can lead to catastrophic results. Thus, fast and accurate detection of scanners is a very important problem. High-speed packet processing usually requires high-speed memory, SRAM, and the size of SRAM is very limited compared with DRAM. We propose a connection attempt success ratio based scanning detection scheme which guarantees false positive and false negative probabilities under a memory-limited environment. Our scheme can also detect slow scanners with guaranteed performance. A sampling-based extended version can overcome the limitation of short-history-based scanning detection schemes and detects enhanced scanners with a list of pre-acquired IP addresses with guaranteed performance. The proposed scheme reduces the required memory size from O(N2) to O(N), where N is the number of active hosts. We apply Bloom filter in order to further reduce the memory size. We evaluate the performance of the proposed scheme through simulation