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Nasir, N. A., Jeong, S.-H..  2020.  Testbed-based Performance Evaluation of the Information-Centric Network. 2020 International Conference on Information and Communication Technology Convergence (ICTC). :166–169.
Proliferation of the Internet usage is rapidly increasing, and it is necessary to support the performance requirements for multimedia applications, including lower latency, improved security, faster content retrieval, and adjustability to the traffic load. Nevertheless, because the current Internet architecture is a host-oriented one, it often fails to support the necessary demands such as fast content delivery. A promising networking paradigm called Information-Centric Networking (ICN) focuses on the name of the content itself rather than the location of that content. A distinguished alternative to this ICN concept is Content-Centric Networking (CCN) that exploits more of the performance requirements by using in-network caching and outperforms the current Internet in terms of content transfer time, traffic load control, mobility support, and efficient network management. In this paper, instead of using the saturated method of validating a theory by simulation, we present a testbed-based performance evaluation of the ICN network. We used several new functions of the proposed testbed to improve the performance of the basic CCN. In this paper, we also show that the proposed testbed architecture performs better in terms of content delivery time compared to the basic CCN architecture through graphical results.
Marasco, E. O., Quaglia, F..  2020.  AuthentiCAN: a Protocol for Improved Security over CAN. 2020 Fourth World Conference on Smart Trends in Systems, Security and Sustainability (WorldS4). :533–538.
The continuous progress of electronic equipments has influenced car manufacturers, leading to the integration of the latest infotainment technologies and providing connection to external devices, such as mobile phones. Modern cars work with ECUs (Electronic Control Units) that handle user interactions and sensor data, by also sending information to actuators using simple, reliable and efficient networks with fast protocols, like CAN (Controller Area Network). This is the most used vehicular protocol, which allows interconnecting different ECUs, making them interact in a synergic manner. On the down side, there is a security risk related to the exposition of malicious ECU's frames-possibly generated by compromised devices-which can lead to the possibility to remote control all the car equipments (like brakes and others) by an attacker. We propose a solution to this problem, designing an authentication and encryption system above CAN, called AuthentiCAN. Our proposal is tailored for the evolution of CAN called CAN-FD, and avoids the possibility for an attacker to inject malicious frames that are not discarded by the destination ECUs. Also, we avoid the possibility for an attacker to learn the interactions that occur across ECUs, with the objective of maliciously replaying messages-which would lead the actuator's logic to be no longer compliant with the actual data sources. We also present a simulation study of our solution, where we provide an assessment of its overhead, e.g. in terms of reduction of the throughput of data-unit transfer over CAN-FD, caused by the added security features.
Islam, Noman.  2019.  A Secure Service Discovery Scheme for Mobile ad hoc Network using Artificial Deep Neural Network. 2019 International Conference on Frontiers of Information Technology (FIT). :133–1335.

In this paper, an agent-based cross-layer secure service discovery scheme has been presented. Service discovery in MANET is a critical task and it presents numerous security challenges. These threats can compromise the availability, privacy and integrity of service discovery process and infrastructure. This paper highlights various security challenges prevalent to service discovery in MANET. Then, in order to address these security challenges, the paper proposes a cross-layer, agent based secure service discovery scheme for MANET based on deep neural network. The software agents will monitor the intrusive activities in the network based on an Intrusion Detection System (IDS). The service discovery operation is performed based on periodic dissemination of service, routing and security information. The QoS provisioning is achieved by encapsulating QoS information in the periodic advertisements done by service providers. The proposed approach has been implemented in JIST/ SWANS simulator. The results show that proposed approach provides improved security, scalability, latency, packet delivery ratio and service discovery success ratio, for various simulation scenarios.