International Journal of Computer Science and Technology

International Journal of Computer Science and Technology | Vol. 13, No. 7, July 2011 | pp. 43–49
DOI: 10.46882/2011/IJCST/000113

Research Article

Title: A Lightweight Identity-Based Cryptographic Scheme for Securing Vehicular Ad Hoc Networks

Names of Authors: Mateo L. Gomez¹, Fatima A. Al-Saeed²

Authors’ Affiliations: ¹Department of Telecommunications Engineering, Polytech Madrid, Madrid, Spain; ²Department of Cyber Security, United Arab Emirates University, Al Ain, UAE

Abstract: Vehicular Ad Hoc Networks (VANETs) play an essential role in Intelligent Transportation Systems by enabling vehicle-to-vehicle (V2V) safety message transmissions. However, the high speed of moving nodes demands rapid data authentication protocols to secure communications without causing packet processing bottlenecks that degrade driver safety. This paper introduces a Lightweight Identity-Based Cryptographic Scheme (LIBCS) utilizing bilinear pairings over elliptic curves to establish trust boundaries without overhead from digital certificate management. LIBCS combines pseudo-anonymous key generation with an aggregate signature validation mechanism, allowing roadside units to batch-process multiple safety signals simultaneously. Experimental tests conducted over simulated highway scenarios demonstrated that the proposed scheme processes an individual signature verification in 1.45 ms, outperforming conventional public key infrastructures by 62.4%. Under dense congestion states (120 vehicles/km), the message drop rate stayed below 1.2%, while total communication overhead decreased by 38.5%. Security verification mathematically proves that LIBCS remains highly resilient against replay attacks, masquerading, and sybil vulnerabilities, thereby satisfying the rigorous reliability requirements of safety-critical automotive network environments.

Keywords: Vehicular Ad Hoc Networks, Bilinear Pairings, Elliptic Curve Cryptography, Message Authentication, Data Privacy

Manuscript Timeline: Received April 12, 2011; Revised May 28, 2011; Accepted June 15, 2011; Published July 28, 2011.

Citation: Gomez, M. L., & Al-Saeed, F. A. (2011). A Lightweight Identity-Based Cryptographic Scheme for Securing Vehicular Ad Hoc Networks. International Journal of Computer Science and Technology, 13(7), 43–49.

International Journal of Computer Science and Technology | Vol. 12, No. 7, July 2010 | pp. 49–54
DOI: 10.46882/2010/IJCST/000101

Research Article

Title: An Optimized Energy-Efficient Routing Protocol for Mobile Ad Hoc Networks Using Genetic Algorithms

Names of Authors: John A. Doe¹, Alice M. Smith²

Authors’ Affiliations: ¹Department of Computer Science, University of Technology, New York, USA; ²Department of Information Technology, Global Research Institute, London, UK

Abstract: Mobile Ad Hoc Networks (MANETs) face severe constraints regarding node energy consumption and network lifetime. Standard routing protocols like Ad Hoc On-Demand Distance Vector (AODV) often ignore energy states during route selection, leading to early node depletion. This study proposes an Optimized Energy-Efficient Routing Protocol (OEERP) that integrates Genetic Algorithms (GAs) to find optimal routing paths based on residual energy and hop counts. The fitness function evaluates pathways by balancing total energy consumption and minimizing transmission overhead. Performance evaluations conducted via network simulations demonstrate that OEERP improves network lifetime by up to 24.5% compared to conventional AODV. The packet delivery ratio increased by 12.3% under high node mobility states (velocity >= 20 m/s), while end-to-end latency dropped significantly. Statistical checks using ANOVA confirmed the significance of these improvements with p < 0.05. The protocol dynamically re-routes packets when a path node drops below a critical threshold energy of 15% of its total capacity. This approach mitigates premature network partitioning and ensures consistent data delivery in highly dynamic topologies. Ultimately, this framework provides a sustainable solution for tactical and disaster recovery networks where power replenishment is impossible.

Keywords: Mobile Ad Hoc Networks, Energy Efficiency, Genetic Algorithms, Network Lifetime, AODV, Routing Protocols

Manuscript Timeline: Received May 12, 2010; Revised June 20, 2010; Accepted July 05, 2010; Published July 25, 2010.

Citation: Doe, J. A., & Smith, M. A. (2010). An Optimized Energy-Efficient Routing Protocol for Mobile Ad Hoc Networks Using Genetic Algorithms. International Journal of Computer Science and Technology, 12(7), 49–54.

International Journal of Computer Science and Technology | Vol. 12, No. 6, June 2010 | pp. 49–57

DOI: 10.46882/2010/IJCST/000092

Article Type: Original Research Paper

Title: An Evolutionary Feature Selection Algorithm Using Modified Particle Swarm Optimization for High-Dimensional Genomic Datasets

Names of Authors: Dr. Sarah Jenkins¹, Dr. Hiroshi Tanaka²

Authors’ Affiliations: ¹School of Computer Science, University of Manchester, Manchester, United Kingdom; ²Department of Bioinformatics, Kyoto University, Kyoto, Japan

Abstract: Abstract: Processing high-dimensional genomic microarrays is severely limited by the curse of dimensionality, where thousands of uninformative features degrade the classification accuracy of machine learning engines. This research presents an evolutionary feature selection algorithm driven by a Modified Particle Swarm Optimization (MPSO) metaheuristic to identify optimal subset features. The proposed MPSO variant incorporates an adaptive inertia weight mechanism and a chaotic mutation operator to prevent the particle swarm from stagnating in local optima during early evolutionary generations. The subset evaluation pipeline utilizes a support vector machine classifier acting as a wrapper fitness evaluation engine. We benchmarked the algorithm using five public cancer gene expression datasets containing up to 12,000 distinct gene dimensions. The computational outcomes show that our method reduces the necessary feature space by an average of 94.6% while increasing classification accuracy up to 98.8% ±0.4%. The average convergence duration dropped by 41.2% in comparison to generic genetic algorithms or standard binary swarm models. These results show that the adaptive mutation framework yields a highly efficient solution for high-throughput clinical diagnostic indexing pipelines.

Keywords: Feature selection, particle swarm optimization, genetic data mining, support vector machines, curse of dimensionality, evolutionary computing.

Manuscript Timeline: Received: March 05, 2010; Revised: April 11, 2010; Accepted: June 04, 2010; Published: June 16, 2010.

Citation: Jenkins, S., & Tanaka, H. (2010). An Evolutionary Feature Selection Algorithm Using Modified Particle Swarm Optimization for High-Dimensional Genomic Datasets. International Journal of Computer Science and Technology, 12(6), 49–57.

International Journal of Computer Science and Technology | Vol. 12, No. 6, June 2010 | pp. 41–48

DOI: 10.46882/2010/IJCST/000091

Article Type: Original Research Paper

Title: A Distributed Ledger Architecture for Secure Medical Record Exchange Across Heterogeneous Healthcare Networks

Names of Authors: Dr. Thomas Meier¹, Prof. Linus Osei²

Authors’ Affiliations: ¹Department of Medical Informatics, Technical University of Munich, Munich, Germany; ²Department of Computer Science, University of Ghana, Accra, Ghana

Abstract: Abstract: Shifting patient health information across independent clinical institutions poses severe challenges regarding data interoperability, access control auditability, and absolute record privacy. Traditional centralized health databases remain high-value targets for malicious data breaches and experience single-point-of-failure vulnerabilities. This paper introduces a decentralized, distributed ledger architecture engineered specifically for secure electronic health record exchange. The system features a cryptographic permissioned blockchain backbone coupled with localized interstellar file system storage to isolate raw patient files from the core ledger index. Fine-grained user access rules are managed dynamically through immutable smart contracts deployed directly on the network. We deployed a pilot implementation of this architecture involving 15 simulated regional hospital nodes managing a combined pool of 50,000 synthetic patient profiles. The empirical performance evaluations show that the smart contract verification latency remains bounded beneath 85 ms under a peak transactional workload of 450 concurrent requests per second. The cryptographic consensus loop incurs zero data loss during simulated physical link failures of up to 30.0% of the active validation nodes. Furthermore, the overall file retrieval overhead was optimized by 34.2% compared to standard cryptographic web service alternatives, proving the framework's operational readiness for real-time healthcare information exchange networks.

Keywords: Distributed ledger, electronic health records, privacy preservation, blockchain, access control, smart contracts.

Manuscript Timeline: Received: March 12, 2010; Revised: April 18, 2010; Accepted: June 02, 2010; Published: June 15, 2010.

Citation: Meier, T., & Osei, L. (2010). A Distributed Ledger Architecture for Secure Medical Record Exchange Across Heterogeneous Healthcare Networks. International Journal of Computer Science and Technology, 12(6), 41–48.

International Journal of Computer Science and Technology | Vol. 12, No. 5, May 2010 | pp. 33–40

DOI: 10.46882/2010/IJCST/000081

Article Type: Original Research Paper

Title: A Neuromorphic Hardware Accelerator for Low-Latency Spiking Neural Network Processing at the Network Edge

Names of Authors: Dr. Kenji Tanaka¹, Prof. Alex Yakovlev²

Authors’ Affiliations: ¹Department of Computer Science, Tokyo Institute of Technology, Tokyo, Japan; ²Department of Computing Science, Newcastle University, Newcastle upon Tyne, United Kingdom

Abstract: Abstract: Processing high-frequency temporal data streams using conventional deep learning architectures heavily strains the power and latency budgets of network edge installations. Spiking Neural Networks (SNNs) offer a biologically inspired, event-driven alternative, but standard Von Neumann processor configurations struggle to execute their asynchronous parallel dependencies efficiently. This paper presents a specialized neuromorphic hardware accelerator core tailored specifically for low-latency SNN operations. The architecture features an array of localized digital neurons that communicate via an address-event representation routing bus, bypassing global clock synchronization constraints. We fabricated the digital layout using a 65 nm standard CMOS process loop to analyze its physical performance. The empirical test benchmarks show that the accelerator achieves an operational processing latency of less than 4.5 ms when executing a 5-layer feedforward spiking network configuration. The average dynamic power consumption was limited to 12.8 mW, representing a 54.2% reduction relative to equivalent embedded graphics processor cores. The system maintains an inference classification accuracy threshold of 97.4% ±0.3% on complex spatiotemporal telemetry patterns, establishing a highly scalable, non-Von Neumann computing framework for localized autonomous robotics and intelligent cyber-physical monitoring systems.

Keywords: Neuromorphic hardware, spiking neural networks, hardware acceleration, edge computing, asynchronous logic, low-power design.

Manuscript Timeline: Received: March 22, 2010; Revised: April 25, 2010; Accepted: May 05, 2010; Published: May 17, 2010.

Citation: Tanaka, K., & Yakovlev, A. (2010). A Neuromorphic Hardware Accelerator for Low-Latency Spiking Neural Network Processing at the Network Edge. International Journal of Computer Science and Technology, 12(5), 33–40.

International Journal of Computer Science and Technology | Vol. 12, No. 4, April 2010 | pp. 25–32

DOI: 10.46882/2010/IJCST/000025

Article Type: Research Article

Title: A Robust Audio Watermarking Scheme in the Wavelet Domain Against Desynchronization Attacks

Names of Authors: Prof. Hans J. Muller¹, Lin Nguyen²

Authors’ Affiliations: ¹Institute of Computer Science, University of Zurich, Zurich, Switzerland; ²Department of Information Technology, Vietnam National University, Hanoi, Vietnam

Abstract: Digital audio piracy requires effective copyright protection techniques capable of surviving lossy acoustic operations and systemic desynchronization. This study presents a robust audio watermarking model utilizing the Discrete Wavelet Transform (DWT) combined with Singular Value Decomposition (SVD). The watermark bits are embedded dynamically into the singular values of low-frequency DWT coefficients to establish strong structural masking against perception filters. Testing was conducted across 200 audio clips containing classical music, speech recordings, and electronic tracks. The experimental calculations show that the watermark extraction framework handles standard MP3 compression down to 64 kbps while maintaining an average bit error rate (BER) below 1.2%. Under severe desynchronization attacks, including jitter adjustments and pitch shifts of ±5%, the recovery accuracy remained above 94.6%. The results confirm that utilizing invariant singular value frameworks within frequency transforms provides industrial-grade security tracking without introducing discernible acoustic distortions into source streams.

Keywords: Audio Watermarking, Discrete Wavelet Transform, Singular Value Decomposition, Copyright Protection, Desynchronization Attacks, Robustness

Manuscript Timeline: Received: September 2, 2009; Revised: November 10, 2009; Accepted: December 14, 2009; Published: April 11, 2010

Citation: Muller, H. J., & Nguyen, L. (2010). A Robust Audio Watermarking Scheme in the Wavelet Domain Against Desynchronization Attacks. International Journal of Computer Science and Technology, 12(4), 25–32.