A literature review on collaborative caching techniques in MANETs: issues and methods used in serving queries

Collaborative cache management in Mobile Ad Hoc Networks (MANETs) environment is considered as an efficient technique to increase data accessibility and availability, by sharing and coordination among mobile nodes. Due to nodes’ mobility, limited battery power and insufficient bandwidth, researchers addressed these challenges by developing many different collaborative caching schemes. The objective of this paper is to review various collaborative caching techniques in MANETs. Collaborative caching techniques are classified by methods used in serving queries, such as: hop-by-hop discovering, broadcasting messages, flooding, and query service differentiation. This review reveals that techniques utilizing hop-by-hop methods have better performance compared to others, especially techniques using additional strategies

Lightweight and Secure IoT-Based Payment Protocols from an Identity-Based Signature Scheme

After the great success of mobile wallets, the Internet of Things (IoT) leaves the door wide open for consumers to use their connected devices to access their bank accounts and perform routine banking activities from anywhere, anytime, and with any device. However, consumers need to feel safe when interacting with IoT-based payment systems, and their personal information should be protected as much as possible. Unlike what is usually found in the literature, in this paper, we introduce two lightweight and secure IoT-based payment protocols based on an identity-based signature scheme. We adopt a server-aided verification technique to construct the first scheme. This technique allows to outsource the heavy computation overhead on the sensor node to a cloud server while maintaining the user’s privacy. The second scheme is built upon a pairing-free ECC-based security protocol to avoid the heavy computational complexity of bilinear pairing operations. The security reduction results of both schemes are held in the Random Oracle Model (ROM) under the discrete logarithm and computational Diffie–Hellman assumptions. Finally, we experimentally compare the proposed schemes against each other and against the original scheme on the most commonly used IoT devices: a smartphone, a smartwatch, and the embedded device Raspberry Pi. Compared with existing schemes, our proposed schemes achieve significant efficiency in terms of communication, computational and storage overheads