Data Driven Approaches to Cybersecurity Governance for Board Decision-Making -- A Systematic Review

Cybersecurity governance influences the quality of strategic decision-making to ensure cyber risks are managed effectively. Board of Directors are the decisions-makers held accountable for managing this risk; however, they lack adequate and efficient information necessary for making such decisions. In addition to the myriad of challenges they face, they are often insufficiently versed in the technology or cybersecurity terminology or not provided with the correct tools to support them to make sound decisions to govern cybersecurity effectively. A different approach is needed to ensure BoDs are clear on the approach the business is taking to build a cyber resilient organization. This systematic literature review investigates the existing risk measurement instruments, cybersecurity metrics, and associated models for supporting BoDs. We identified seven conceptual themes through literature analysis that form the basis of this study's main contribution. The findings showed that, although sophisticated cybersecurity tools exist and are developing, there is limited information for Board of Directors to support them in terms of metrics and models to govern cybersecurity in a language they understand. The review also provides some recommendations on theories and models that can be further investigated to provide support to Board of Directors

Brainwave-based authentication using features fusion

This article investigates the use of human brainwaves for user authentication. We used data collected from 50 volunteers and leveraged the Support Vector Machine (SVM) as a classification algorithm for the case study. User recognition patterns are taken from a combination of blinking, attention concentration, and picture recognition emotion sequences. These actions impact alpha, beta, gamma, and theta brain waves, which are measured using several electrodes. Ten different electrode placement patterns are explored, with varied positioning on the head. For each placement position, four features are examined, for a total of 40 extracts in the learning model. Features are: 1) spectral information, 2) coherence, 3) mutual correlation coefficient, and 4) mutual information. Each feature type is trained by the SVM algorithm, and the 40 weak classifier candidates. Adaptive Boosting (AdaBoost), a type of machine learning, is then used to generate a robust classifier, which is subsequently used to create a model, and select features, used to accurately identify individuals for authentication purposes. Upon verifying the proposed method using 32 legitimate users and 18 intruders, we obtained an authentication error rate (ERR) of 0.52%, and a classification rate of 99.06%

Development of traffic light control algorithm in smart municipal network

This paper presents smart system that bypasses the normal functioning algorithm of traffic lights, triggers a green light when the lights are red or reset the timer of the traffic lights when they are about to turn red. Different pieces of hardware like microcontroller units, transceivers, resistors, diodes, LEDs, a digital compass and accelerometer will be coupled together and programed to create unified complex intelligent system

A combined LIFO-Priority algorithm for overload control of SIP server

In this paper a simulation model of message service procedure in SIP server in the normal conditions and in the congestion state is represented. The paper proposes local overload control for SIP server applied FIFO discipline in normal state and LIFO discipline with priority service model during overload

A combined LIFO-Priority algorithm for overload control of SIP server

In this paper a simulation model of message service procedure in SIP server in the normal conditions and in the congestion state is represented. The paper proposes local overload control for SIP server applied FIFO discipline in normal state and LIFO discipline with priority service model during overload

Development of smart infocommunication networks for intellectual municipal services

Abstract:This paper represents the smart system that bypasses the normal functioning algorithm of traffic lights, triggers a green light when the lights are red or to reset the timer of the traffic lights when they are about to turn red. Different pieces of hardware like microcontroller units, transceivers, resistors, diode, LEDs, digital compass and accelerometer will be coupled together and programmed to create a unified complex intelligent system