Performance evaluation of an efficient counter-based scheme for mobile ad hoc networks based on realistic mobility model

Flooding is the simplest and commonly used mechanism for broadcasting in mobile ad hoc networks (MANETs). Despite its simplicity, it can result in high redundant retransmission, contention and collision in the network, a phenomenon referred to as broadcast storm problem. Several probabilistic broadcast schemes have been proposed to mitigate this problem inherent with flooding. Recently, we have proposed a hybrid-based scheme as one of the probabilistic scheme, which combines the advantages of pure probabilistic and counter-based schemes to yield a significant performance improvement. Despite these considerable numbers of proposed broadcast schemes, majority of these schemes’ performance evaluation was based on random waypoint model. In this paper, we evaluate the performance of our broadcast scheme using a community based mobility model which is based on social network theory and compare it against widely used random waypoint mobility model. Simulation results have shown that using unrealistic movement pattern does not truly reflect on the actual performance of the scheme in terms of saved-rebroadcast, reachability and end to end delay

Acoustic Integrity Codes: Secure Device Pairing Using Short-Range Acoustic Communication

Secure Device Pairing (SDP) relies on an out-of-band channel to authenticate devices. This requires a common hardware interface, which limits the use of existing SDP systems. We propose to use short-range acoustic communication for the initial pairing. Audio hardware is commonly available on existing off-the-shelf devices and can be accessed from user space without requiring firmware or hardware modifications. We improve upon previous approaches by designing Acoustic Integrity Codes (AICs): a modulation scheme that provides message authentication on the acoustic physical layer. We analyze their security and demonstrate that we can defend against signal cancellation attacks by designing signals with low autocorrelation. Our system can detect overshadowing attacks using a ternary decision function with a threshold. In our evaluation of this SDP scheme's security and robustness, we achieve a bit error ratio below 0.1% for a net bit rate of 100 bps with a signal-to-noise ratio (SNR) of 14 dB. Using our open-source proof-of-concept implementation on Android smartphones, we demonstrate pairing between different smartphone models.Comment: 11 pages, 11 figures. Published at ACM WiSec 2020 (13th ACM Conference on Security and Privacy in Wireless and Mobile Networks). Updated reference

Named data networking for efficient IoT-based disaster management in a smart campus

Disasters are uncertain occasions that can impose a drastic impact on human life and building infrastructures. Information and Communication Technology (ICT) plays a vital role in coping with such situations by enabling and integrating multiple technological resources to develop Disaster Management Systems (DMSs). In this context, a majority of the existing DMSs use networking architectures based upon the Internet Protocol (IP) focusing on location-dependent communications. However, IP-based communications face the limitations of inefficient bandwidth utilization, high processing, data security, and excessive memory intake. To address these issues, Named Data Networking (NDN) has emerged as a promising communication paradigm, which is based on the Information-Centric Networking (ICN) architecture. An NDN is among the self-organizing communication networks that reduces the complexity of networking systems in addition to provide content security. Given this, many NDN-based DMSs have been proposed. The problem with the existing NDN-based DMS is that they use a PULL-based mechanism that ultimately results in higher delay and more energy consumption. In order to cater for time-critical scenarios, emergence-driven network engineering communication and computation models are required. In this paper, a novel DMS is proposed, i.e., Named Data Networking Disaster Management (NDN-DM), where a producer forwards a fire alert message to neighbouring consumers. This makes the nodes converge according to the disaster situation in a more efficient and secure way. Furthermore, we consider a fire scenario in a university campus and mobile nodes in the campus collaborate with each other to manage the fire situation. The proposed framework has been mathematically modeled and formally proved using timed automata-based transition systems and a real-time model checker, respectively. Additionally, the evaluation of the proposed NDM-DM has been performed using NS2. The results prove that the proposed scheme has reduced the end-to-end delay up from 2% to 10% and minimized up to 20% energy consumption, as energy improved from 3% to 20% compared with a state-of-the-art NDN-based DMS