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The article focuses on the history and development of the strategic approach to cybersecurity known as "zero trust." The authors discuss the use of firewalls and how they are no longer sufficient, examine data breaches at credit reporting company Equifax and financial company Capital One, and explore how zero trust can impact people, process, and technology (PPT).

A conversation about the strategic approach to cybersecurity known as "zero trust" is presented between Michael Loftus, an information technology (IT) consultant, Rick Doten, the vice president (VP) of information security at Centene Corporation and chief internet security officer (CISO) of Carolina Complete Health, Atefeh Mashatan, founder and director of the Cybersecurity Research Lab at Toronto Metropolitan University (TMU), and Andrew Vezina, the CISO at Equitable (EQ) Bank.

ABSTRACTOne modern strategy to anticipate consumer reaction to new products and services involves looking towards social media sites to explore consumer opinions. A rich body of literature on social media marketing suggests that an effective way to leverage social media platforms is the empirical analysis of electronic word-of-mouth (eWOM), particularly through sentiment analysis (SA). We propose a novel method for innovators to leverage social media by exploring how breaking media attention on notable corporate events impacts the general public sentiment surrounding a pre-introduced, potentially disruptive innovation(PPDI). Twitter conversations surrounding Facebook’s pre-introducedpayment system called Libra, a permissioned blockchain-based cryptocurrency, were analysed as a case study. The analysis suggests that breaking media attention leads to a significant change in sentiment polarity. An event with a preannouncement leads to an emotional momentum effect whereby sentiment polarity accumulates across an anticipation period. Implications for how managers may leverage these insights are discussed.

THERE IS A new technology on the horizon that will forever change the information security and privacy industry landscape. Quantum computing, together with quantum communication, will have many beneficial applications but will also be capable of breaking many of today's most popular cryptographic techniques that help ensure data protection--in particular, confidentiality and integrity of sensitive information. These techniques are ubiquitously embedded in today's digital fabric and implemented by many industries such as finance, health care, utilities, and the broader information communication technology (ICT) community. It is therefore imperative for ICT executives to prepare for the transition from quantum-vulnerable to quantum-resistant technologies. [ABSTRACT FROM AUTHOR]

THE THEORY OF quantum computing has been with us for nearly three decades, courtesy of a quantum mechanical model of the Turing machine proposed by physicist Paul Benioff in the early 1980s. For most of that time, the notion has seemed more a far-off vision than an impending reality. That changed abruptly with a 2019 claim by Google AI, in conjunction with NASA, that it had managed to perform a quantum computation infeasible on a conventional computer. [ABSTRACT FROM AUTHOR]

This paper discusses the problem of double-ending fraud in real estate transactions – a type of transactional fraud wherein agents handling real estate transactions unfairly benefit (e.g., by simultaneously representing both the buy and sell side of a real estate transaction in a manner that unfairly boosts the commission they receive, or colluding to increase their commission in a real estate transaction at the expense of the buyer and/or seller of the real property). The paper proposes a unique blockchain solution design that leverages blockchain's properties of transparency and ability to create tamper-resistant audit trails to reduce opportunities for double-ending fraud and increase real estate market participants' trust in the handling of their transactions. The paper discusses the implementation of a prototype of the solution based on hyperledger fabric and sails; it presents the results of an agent-based modelling simulation validating that the inherent transparency of the proposed design offers optimal allocation for both sellers and buyers.

Internet of Things (IoT) systems in different areas, such as manufacturing, transportation, and healthcare, are the convergence of several technologies. There are many concerns about security and privacy drawbacks in IoT systems. Apart from confidentiality supported by encryption primitives, authenticity and non-repudiation are of utmost importance. IoT entities generally use conventional digital signature schemes to achieve imperative goals. However, there are some state-of-the-art digital signatures with more functionalities, IoT-friendly properties, and privacy-preserving features.

We look at message recognition protocols (MRPs) and prove that there is a one-to-one correspondence between stateless non-interactive MRPs and digital signature schemes. Next, we examine the Jane Doe protocol and note its inability to recover in case of a certain adversarial disruption. We propose a variant of this protocol which is equipped with a resynchronisation technique that allows users to resynchronise whenever they wish. Moreover, we propose another protocol which self-recovers in case of an intrusion. This protocol incorporates the resynchronisation technique within itself. Further, we enumerate all possible attacks against this protocol and show that none of the attacks can occur. Finally, we prove the security of the new protocol and its ability to self-recover once the disruption has stopped. Finally, we propose an MRP which provides explicit confirmation to the sender on whether or not the message was accepted by the receiver.

In this paper, we consider the problem of increasing efficiency of a transportation system through optimizing the behavior of commuters. The assumption is that the time spent in the traffic can be represented by a monetary value and hence introduction of monetary compensations can lead to a more efficient organization of the transportation system. In our model, heterogeneous travelers differently assess the value of their time spent in congestion, hence it is presumably viable to reduce traffic in the most congested streets by introducing a bidding mechanism that will allow the participants who have a lower monetary value of time to receive a compensation financed by the group of commuters that have a higher value of time spend in congestion. We start by presenting a design of a bidding system for optimal allocation of traffic. We analyze the properties of the proposed algorithm and show that it leads to a more efficient allocation of vehicles than the theoretical allocation that could be achieved in the Nash Equilibrium of an uncontrolled transportation network. Subsequently, we verify the proposed auction design via an agent-based simulation model representing the Manhattan area of New York City. The results of our simulation confirm theoretical findings that the introduction of the proposed auction mechanism in a real city settings leads to a more efficient allocation of routes or means of transportation chosen by commuters.