Towards Secure and Safe Appified Automated Vehicles

The advancement in Autonomous Vehicles (AVs) has created an enormous market for the development of self-driving functionalities,raising the question of how it will transform the traditional vehicle development process. One adventurous proposal is to open the AV platform to third-party developers, so that AV functionalities can be developed in a crowd-sourcing way, which could provide tangible benefits to both automakers and end users. Some pioneering companies in the automotive industry have made the move to open the platform so that developers are allowed to test their code on the road. Such openness, however, brings serious security and safety issues by allowing untrusted code to run on the vehicle. In this paper, we introduce the concept of an Appified AV platform that opens the development framework to third-party developers. To further address the safety challenges, we propose an enhanced appified AV design schema called AVGuard, which focuses primarily on mitigating the threats brought about by untrusted code, leveraging theory in the vehicle evaluation field, and conducting program analysis techniques in the cybersecurity area. Our study provides guidelines and suggested practice for the future design of open AV platforms

DEFINING A CYBER OPERATIONS PERFORMANCE FRAMEWORK VIA COMPUTATIONAL MODELING

Cyber operations are influenced by a wide range of environmental characteristics, strategic policies, organizational procedures, complex networks, and the individuals who attack and defend these cyber battlegrounds. While no two cyber operations are identical, leveraging the power of computational modeling will enable decision-makers to understand and evaluate the effect of these influences prior to their impact on mission success. Given the complexity of these influences, this research proposes an agent-based modeling framework that will result in an operational performance dashboard for user analysis. To account for cyber team behavioral characteristics, this research includes the development and validation of the Cyber Operations Self-Efficacy Scales (COSES). The underlying statistics, algorithms, research instruments, and equations to support the overall framework are provided. This research represents the most comprehensive cyber operations agent-based performance analysis tools published to date

A Quantum Algorithm To Locate Unknown Hashes For Known N-Grams Within A Large Malware Corpus

Quantum computing has evolved quickly in recent years and is showing significant benefits in a variety of fields. Malware analysis is one of those fields that could also take advantage of quantum computing. The combination of software used to locate the most frequent hashes and $n$-grams between benign and malicious software (KiloGram) and a quantum search algorithm could be beneficial, by loading the table of hashes and $n$-grams into a quantum computer, and thereby speeding up the process of mapping $n$-grams to their hashes. The first phase will be to use KiloGram to find the top-$k$ hashes and $n$-grams for a large malware corpus. From here, the resulting hash table is then loaded into a quantum machine. A quantum search algorithm is then used search among every permutation of the entangled key and value pairs to find the desired hash value. This prevents one from having to re-compute hashes for a set of $n$-grams, which can take on average $O(MN)$ time, whereas the quantum algorithm could take $O(\sqrt{N})$ in the number of table lookups to find the desired hash values.Comment: IEEE Quantum Week 2020 Conferenc

Next-Gen Security: Leveraging Advanced Technologies for Social Medical Public Healthcare Resilience

The healthcare industry is undergoing a significant change as it incorporates advanced technologies to strengthen its security infrastructure and improve its ability to withstand current challenges and  explores the important overlap between security, technology, and public health. The introductory section presents a thorough overview, highlighting the current status of public healthcare and emphasizing the crucial importance of security in protecting confidential medical data. This statement highlights the current difficulties encountered by social medical public healthcare systems and emphasizes the urgent need to utilize advanced technologies to strengthen their ability to adapt and recover. The systematic literature review explores a wide range of studies, providing insight into the various aspects of healthcare security. This text examines conventional security methods, exposes their constraints, and advances the discussion by examining cutting-edge technologies such as Artificial Intelligence (AI), Machine Learning, Blockchain, Internet of Things (IoT), and Biometric Security Solutions. Every technology is carefully examined to determine its ability to strengthen healthcare systems against cyber threats and breaches, guaranteeing the confidentiality and accuracy of patient data. The methodology section provides a clear explanation of the research design, the process of selecting participants, and the strategies used for analyzing the data. The research seeks to evaluate the present security situation and determine the best methods for incorporating advanced technologies into healthcare systems, using either qualitative or quantitative methods. The following sections elucidate the security challenges inherent in social medical public healthcare, encompassing cyber threats and privacy concerns. Drawing on case studies, the paper illustrates successful implementations of advanced technologies in healthcare security, distilling valuable lessons and best practices. The recommendations section goes beyond the technical domain, exploring the policy implications and strategies for technological implementation. The exploration of regulatory frameworks, legal considerations, and ethical dimensions is conducted to provide guidance for the smooth integration of advanced technologies into healthcare systems. Healthcare professionals are encouraged to participate in training and awareness programs to ensure a comprehensive and efficient implementation. To summarize, the paper combines the results, highlighting the importance of utilizing advanced technologies to strengthen the security framework of social medical public healthcare. The significance of healthcare resilience is emphasized, and potential areas for future research are delineated. This research is an important resource that offers valuable insights and guidance for stakeholders, policymakers, and technologists who are dealing with the intricate field of healthcare security in the age of advanced technologies. DOI: https://doi.org/10.52710/seejph.48

Anonymizing cybersecurity data in critical infrastructures: the CIPSEC approach

Cybersecurity logs are permanently generated by network devices to describe security incidents. With modern computing technology, such logs can be exploited to counter threats in real time or before they gain a foothold. To improve these capabilities, logs are usually shared with external entities. However, since cybersecurity logs might contain sensitive data, serious privacy concerns arise, even more when critical infrastructures (CI), handling strategic data, are involved. We propose a tool to protect privacy by anonymizing sensitive data included in cybersecurity logs. We implement anonymization mechanisms grouped through the definition of a privacy policy. We adapt said approach to the context of the EU project CIPSEC that builds a unified security framework to orchestrate security products, thus offering better protection to a group of CIs. Since this framework collects and processes security-related data from multiple devices of CIs, our work is devoted to protecting privacy by integrating our anonymization approach.Peer ReviewedPostprint (published version