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 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

A Bio-Inspired Trust Framework in Wireless Ad Hoc Networks

Cyber attacks are amongst the most serious threats facing people and organizations. In the face of the increasing complexity and effectiveness of these attacks, creative approaches to defense are required. Groups of insects survive due to their use of collaborative approaches with the unique ability to detect anomalies using primarily local data and very limited computational resources (i.e., limited brain power). These attributes are even more crucial for wireless ad hoc networks where the number of nodes and connections between those nodes are ephemeral. We propose a trust framework inspired by the detection mechanisms exhibited by bee swarms in which a wireless node can only observe and leverage the actions of their neighbors rather than the global knowledge of the network to make a decision. This leveraging of local knowledge is an important aspect of trust in wireless networks in which global state information is difficult to encapsulate. We also utilize models from binary voting to present a straightforward mathematical model for our bee-inspired trust framework in wireless ad hoc networks

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

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

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%

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

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

Traffic-adaptive, flow-specific medium access for wireless networks

In this report, we formally introduce the novel concept of traffic-adaptive, flow-specific medium access control and show that it outperforms contention, non-contention and hybrid medium access schemes. A traffic-adaptive, flow-specific mechanism is proposed that utilizes flow-specific queue size statistics to select between medium access modes. A general model for traffic adaptive, flow-specific medium access control is developed and it is shown that hybrid medium access as well as traditional contention-based and non-contention schemes can be seen as special cases of the more general flow-specific access. The two flow, two-mode case of the general model is developed in detail and it is shown analytically that this queue-based implementation of traffic-adaptive, flow-specific medium access outperforms contention, non-contention, and hybrid approaches. The proposed traffic-adaptive, flow-specific mechanism is applied to Cooperative Wireless Sensor Network Medium Access Control (CWS-MAC) a flow-specific medium access protocol. Performance is evaluated is evaluated and compared to the traditional medium access approaches. Both analytical and simulation results are provided including the development of throughput and delay expressions for slotted ALOHA with periodic server vacations.Approved for public release; distribution is unlimited

Location Privacy in LTE: A Case Study on Exploiting the Cellular Signaling Plane's 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.