A novel lightweight authentication and privacy-preserving protocol for vehicular ad hoc networks

Vehicular ad hoc network (VANET) is commonly employed in intelligent transportation system (ITS) that allows the exchange of traffic data among vehicles and nearby environment to accomplish effective driving experience. Privacy and security are the challenging issues that exist in the safety needs of the VANET. Any particular leakage of the vehicle details such as route data might result in serious impacts, and therefore, authentication and privacy-preserving protocols are needed to enhance safety in VANET. With this motivation, this paper presents a new lightweight authentication and privacy-preserving protocol using improved timed efficient stream loss-tolerant authentication with cuckoo filter (ITESLA-CF) for VANETs. The proposed model encompasses different stages of operations such as initialization, registration, mutual authentication, broadcast and verification, and vehicle revocation phases. In addition, the ITESLA-CF technique has effective broadcast authentication as TESLA with minimal memory requirement. Besides, the ITESLA-CF technique includes a cuckoo filter to save the authentic information of vehicles that exist in the RSU’s range. The proposed model has lightweight mutual authentication among the parties and it offers robust anonymity to accomplish privacy and resists ordinary attacks. To ensure the better performance of the ITESLA-CF technique, an extensive set of simulations take place and the results are assessed in terms of different measures. The resultant experimental values pointed out the supremacy of the ITESLA-CF technique over the recent state of art methods.

BionetBF: A Novel Bloom Filter for Faster Membership Identification of Paired Biological Network Data

Biological network represents the interaction or relationship between the biological entities such as proteins and genes of a biological process. A biological network with thousands of millions of vertices makes its processing complex and challenging. In this article, we have proposed a novel Bloom Filter for biological networks, called BionetBF, to provide fast membership identification of the biological network edges or paired biological data. BionetBF is capable of executing millions of operations within a second on datasets having millions of paired biological data while occupying tiny amount of main memory. We have conducted rigorous experiments to prove the performance of BionetBF with large datasets. The experiment is conducted using 12 generated datasets and three biological network datasets. BionetBF demonstrates higher performance while maintaining a 0.001 false positive probability. BionetBF is also compared with other filters: Cuckoo Filter and Libbloom, where BionetBF proves its supremacy by exhibiting higher performance with a smaller sized memory compared with large sized filters of Cuckoo Filter and Libbloom.

Improving Lookup and Query Execution Performance in Distributed Big Data Systems using Cuckoo Filter

Performance is a critical concern when reading and writing data from billions of records stored in Big Data warehouse. We introduce two scopes for query performance improvement. One is to improve performance of lookup queries after data deletion in Big Data systems that use Eventual Consistency. We propose a scheme to improve lookup performance after data deletion by using Cuckoo Filter. Another scope for improvement is to avoid unnecessary network round-trip for querying in remote nodes in a distributed Big Data cluster when it is known that the nodes do not have requested partition of data. We propose a scheme using probabilistic filters that are looked up before querying remote nodes, so that queries resulting in no data can be skipped from passing through the network. We evaluate our schemes with Cassandra using real dataset and show that each scheme can improve performance of lookup queries for up to 100%.

Blockchain-Based Cloud Data Integrity Verification Scheme with High Efficiency

With the large-scale application of cloud storage, how to ensure cloud data integrity has become an important issue. Although many methods have been proposed, they still have their limitations. This paper improves some defects of the previous methods and proposes an efficient cloud data integrity verification scheme based on blockchain. In this paper, we proposed a lattice signature algorithm to resist quantum computing and introduced cuckoo filter to simplify the computational overhead of the user verification phase. Finally, the decentralized blockchain network is introduced to replace traditional centralized audit to publicize and authenticate the verification results, which improves the transparency and the security of this scheme. Security analysis shows that our scheme can resist malicious attacks and experimental results show that our scheme has high efficiency, especially in the user verification phase.

Designing Cuckoo Based Pending Interest Table for CCN Networks

<p class="JESTECAbstract">Content Centric Networking (CCN) is a modern architecture that got wide attention in the current researches as a substitutional for the current IP-based architecture. Many studies have been investigated on this novel architecture but only little of them focused on Pending Interest Table (PIT) which is very important component in every CCN router. PIT has fundamental role in packet processing in both upstream process (Interest packets) and downstream process (Data packets). PIT must be fast enough in order to not become an obstruction in the packet processing and also it must be big enough to save a lot of incoming information. In this paper, we suggest a new PIT design and implementation named CF-PIT for CCN router. Our PIT design depends on modifying and utilizing an approximate data structure called Cuckoo filter (CF). Cuckoo filter has ideal characteristics like: high insertion/query/deletion performance, acceptable storage demands and false positive probability which make it with our modification convenient for PIT implementation. The experimental results showed that our CF-PIT design has high performance in different side of views which make it very suitable to be implemented on CCN routers.</p>