Demonstrating the Threat of Hardware Trojans in Wireless Sensor Networks

As the demand for cheaper electronic devices has increased, the location of manufacturing foundries has changed, sometimes to untrusted places in foreign countries. Some of these locations have limited oversight of the manufacturing of complicated and sensitive electronic components including integrated circuits (ICs). The integrated circuits are key component in all current electronic devices and can be modified to be malicious or to monitor the functions of their applications. These malicious modifications on the ICs are called hardware trojans (HWTs). HWTs an be designed to quietly monitor, to actively send out sensitive information, or to destroy their host device completely. The idea of hardware trojans in Wireless Sensor Networks (WSNs) has not been investigated before; thus, our goal is to demonstrate the potential threat that hardware trojans pose for sensor networks. This is important to study, given that in WSNs hundreds of sensors are deployed and in most cases left unattended, which gives the opportunity to an attacker to trigger a HWT on the sensors. For our investigation, we used TelosB sensors that have been used for some WSN applications. An attacker in a network can, for example, take advantage of the SPI bus that is used by the radio to eavesdrop messages and even disrupt communications completely. Currently, security breaches through software is given great importance in the WSN academic and research community. Our research shows that the same level of importance must be given to attacks through hardware to ensure a trusted and secure network

Routing and Spectrum Allocation in Spectrum-Sliced Elastic Optical Path Networks: A Primal-Dual Framework

The recent decade has witnessed a tremendous growth of Internet traffic, which is expected to continue climbing for the foreseeable future. As a new paradigm, Spectrum-sliced Elastic Optical Path (SLICE) networks promise abundant (elastic) bandwidth to address the traffic explosion, while bearing other inherent advantages including enhanced signal quality and extended reachability. The fundamental problem in SLICE networks is to route each traffic demand along a lightpath with continuously and consecutively available sub-carriers, which is known as the Routing and Spectrum Allocation (RSA) problem. Given its NP-Hardness, the solutions to the RSA problem can be classified into two categories: optimal solutions using link-based, path-based, and channel-based Integer Linear Programming (ILP) models, which require extensive computational time; and sub-optimal heuristic and meta-heuristic algorithms, which have no guarantee on the solution quality. In this work, inspired by a channel-based ILP model, we propose a novel primal-dual framework to address the RSA problem, which can obtain a near-optimal solution with guaranteed per-instance closeness to the optimal solution

Routing and Spectrum Allocation in Spectrum-Sliced Elastic Optical Path Networks: A Primal-Dual Framework

The recent decade has witnessed a tremendous growth of Internet traffic, which is expected to continue climbing for the foreseeable future. As a new paradigm, Spectrum-sliced Elastic Optical Path (SLICE) networks promise abundant (elastic) bandwidth to address the traffic explosion, while bearing other inherent advantages including enhanced signal quality and extended reachability. The fundamental problem in SLICE networks is to route each traffic demand along a lightpath with continuously and consecutively available sub-carriers, which is known as the Routing and Spectrum Allocation (RSA) problem. Given its NP-Hardness, the solutions to the RSA problem can be classified into two categories: optimal solutions using link-based, path-based, and channel-based Integer Linear Programming (ILP) models, which require extensive computational time; and sub-optimal heuristic and meta-heuristic algorithms, which have no guarantee on the solution quality. In this work, inspired by a channel-based ILP model, we propose a novel primal-dual framework to address the RSA problem, which can obtain a near-optimal solution with guaranteed per-instance closeness to the optimal solution