Introduction to the Minitrack on Wireless Networks

Proceedings of the 51st Hawaii International Conference on System Sciences | 2018The article of record as published may be found at https://doi.org/10.24251/HICSS.2018.72

Introduction to the Minitrack on Cellular and Wireless Networks

Proceedings of the 53rd Hawaii International Conference on System Sciences | 2021The article of record as published may be found at https://doi.org/10.24251/HICSS.2021.82

Capacity Estimation for Error Correction Code-based Embedding in Adaptive Rate Wireless Communication Systems

In this paper, we explore the performance of error correction code-based embedding in adaptive rate wireless communication systems. We first develop a model to illustrate the relationship between the selected modulation and coding scheme index, the current channel state, and the embedding capacity. Extensive simulations facilitate the development of expressions to describe the estimated embedding capacity for the proposed scheme when implemented within the single carrier physical layer of the IEEE 802.11ad, directional multi-Gigabit standard. We further identify and characterize various types of distortion and describe additional constraints that may serve to reduce the available embedding margin and overall embedding capacity

Introduction to the Wireless Networks minitrack

Proceedings of the 50th Hawaii International Conference on System Sciences | 2017The article of record as published may be found at https://doi.org/10.24251/HICSS.2017.75

The use of partially observable Markov decision processes to optimally implement moving target defense

For moving target defense (MTD) to shift advantage away from cyber attackers, we need techniques which render systems unpredictable but still manageable. We formulate a partially observable Markov decision process (POMDP) which facilitates optimized MTD capable of thwarting cyber attacks without excess overhead. This paper describes POMDP formulation including the use of an absorbing final state and attack penalty scaling factor to abstract defender-defined priorities into the model. An autonomous agent leverages the POMDP to select the optimal defense based on assessed cyber-attack phase. We offer an example formulation wherein attack suppression of greater than 99% and system availability of greater than 94% were maintained even as probability of detection of attack phase dropped to 74%

Military Intelligence Applications for Blockchain Technology

In this paper, the authors review documented problems in military intelligence that appear well suited for improvement via blockchain technology. We review guidance from the literature related to determining blockchain technology applicability and propose a decision aid tailored to military intelligence perspectives. We also propose applying batch queueing theory to enable initial feasibility studies and present analysis toward the first known case study of military intelligence incorporation of blockchain technology, a project reviewing blockchain applicability to an intelligence database that stores geographic locations of units of interest

Spectral Graph-based Cyber Worm Detection Using Phantom Components and Strong Node Concept

Innovative solutions need to be developed to defend against the continued threat of computer worms. We propose the spectral graph theory worm detection model that utilizes traffic dispersion graphs, the strong node concept, and phantom components to create detection thresholds in the eigenspectrum of the dual basis. This detection method is employed in our proposed model to quickly and accurately detect worm attacks with different attack characteristics. It also intrinsically identifies infected nodes, potential victims, and estimates the worm scan rate. We test our model against the worm-free NPS2013 dataset, a modeled Blaster worm, and the WannaCry CTU-Malware-Capture-Botnet-284-1 and CTU-Malware-Capture-Botnet-285-1 datasets. Our results show that the spectral graph theory worm detection model has better performance rates compared to other models reviewed in literature

Quantifying Location Privacy in Urban Next-Generation Cellular Networks

With urbanization and cellular subscribership rising sharply, cellular use in urban locales has become a normative behavior for the majority of the world’s population. As the research community pushes the limits of what is possible in the next generation cellular arena, it is prudent to simultaneously hold in tension the responsibility to provide appropriate protections to the ultimate end users of such technology. To this end, this research illustrates a location-based attack in modern cellular networks. This attack leverages control information sent over the radio access network without the benefit of encryption. We show how this attack is particularly potent in urban localization where it is important to infer location in three dimensions. We quantify the efficacy of such an attack, and therefore the associated location privacy, through simulation both in a generic cellular environment and in an environment modeled after downtown Honolulu. Our results show that accuracy on the order of 15 meters is possible

A Comparison of Optimized Link State Routing with Traditional Ad-hoc Routing Protocols

The performance of mobile ad-hoc networks (MANET) is related to the efficiency of the routing protocols in adapting to frequently changing network topology and link status. This paper addresses the issue by comparing the relative performance of three key ad-hoc routing protocols: Destination-sequenced Distance Vector (DSDV), Ad-hoc Ondemand Distance Vector (AODV) and Optimized Link State Routing (OLSR). The protocols are tested based on two scenarios, namely, tactical networks for ships and sensor-based network nodes. Four performance metrics were measured by varying the maximum speed of mobile hosts, network size and traffic load, to assess the routing capability and protocol efficiency. The simulation results indicate that AODV performs better than OSLR and DSDV in the first scenario. Although OLSR also performed relatively well, the associated high routing overhead is the dominant reason for not choosing it. On the other hand, OLSR emerged as the protocol of choice for sensor networks, where the high routing overhead is counteracted by consistently better performance in all other metrics. Due to the slow evolution of the sensor network topology, OLSR performed satisfactorily for best effort traffic but needed subtle adjustments to balance between latency and bandwidth to meet the requirements of delay-sensitive applications

Location Privacy in LTE: A Case Study on Exploiting the Cellular Signaling Plane\u27s Timing Advance

Location privacy is an oft-overlooked, but exceedingly important niche of the overall privacy macrocosm. An ambition of this work is to raise awareness of concerns relating to location privacy in cellular networks. To this end, we will demonstrate how user location information is leaked through a vulnerability, viz. the timing advance (TA) parameter, in the Long Term Evolution (LTE) signaling plane and how the position estimate that results from that parameter can be refined through a previously introduced method called Cellular Synchronization Assisted Refinement (CeSAR) [1]. With CeSAR, positioning accuracies that meet or exceed the FCC’s E-911 mandate are possible making CeSAR simultaneously a candidate technology for meeting the FCC’s wireless localization requirements and a demonstration of the alarming level of location information sent over the air. We also introduce a geographically diverse data set of TAs collected from actual LTE network implementations utilizing different cell phone chipsets. With this data set we show the appropriateness of modeling the error associated with a TA as normally distributed.