Virtualized network framework solution to collecting private research data NEMESIS: Network Experimentation and Monitoring in Environments Safely In-Situ

The cyber security research realm is plagued with the problem of collecting and using trace data from sources. Methods of anonymizing public data sets have been proven to leak large amounts of private network data. Yet access to private and public trace data is needed, this is the problem that NEMESIS seeks to solve. NEMESIS is a virtual network system level solution to the problem where instead of bringing the data to the experiments one brings the experiments to the data. NEMESIS provides security and isolation that other approaches have not; allowing for filtering and anonymization of trace data as needed. The solution came about from a desire and need to have a system level solution that leveraged and allowed for the usages of the best current technologies, while remaining highly extendible to future needs

Developing a Series of AI Challenges for the United States Department of the Air Force

Through a series of federal initiatives and orders, the U.S. Government has been making a concerted effort to ensure American leadership in AI. These broad strategy documents have influenced organizations such as the United States Department of the Air Force (DAF). The DAF-MIT AI Accelerator is an initiative between the DAF and MIT to bridge the gap between AI researchers and DAF mission requirements. Several projects supported by the DAF-MIT AI Accelerator are developing public challenge problems that address numerous Federal AI research priorities. These challenges target priorities by making large, AI-ready datasets publicly available, incentivizing open-source solutions, and creating a demand signal for dual use technologies that can stimulate further research. In this article, we describe these public challenges being developed and how their application contributes to scientific advances

Challenges in Cybersecurity and Privacy - the European Research Landscape

Cybersecurity and Privacy issues are becoming an important barrier for a trusted and dependable global digital society development. Cyber-criminals are continuously shifting their cyber-attacks specially against cyber-physical systems and IoT, since they present additional vulnerabilities due to their constrained capabilities, their unattended nature and the usage of potential untrustworthiness components. Likewise, identity-theft, fraud, personal data leakages, and other related cyber-crimes are continuously evolving, causing important damages and privacy problems for European citizens in both virtual and physical scenarios. In this context, new holistic approaches, methodologies, techniques and tools are needed to cope with those issues, and mitigate cyberattacks, by employing novel cyber-situational awareness frameworks, risk analysis and modeling, threat intelligent systems, cyber-threat information sharing methods, advanced big-data analysis techniques as well as exploiting the benefits from latest technologies such as SDN/NFV and Cloud systems. In addition, novel privacy-preserving techniques, and crypto-privacy mechanisms, identity and eID management systems, trust services, and recommendations are needed to protect citizens’ privacy while keeping usability levels. The European Commission is addressing the challenge through different means, including the Horizon 2020 Research and Innovation program, thereby financing innovative projects that can cope with the increasing cyberthreat landscape. This book introduces several cybersecurity and privacy research challenges and how they are being addressed in the scope of 15 European research projects. Each chapter is dedicated to a different funded European Research project, which aims to cope with digital security and privacy aspects, risks, threats and cybersecurity issues from a different perspective. Each chapter includes the project’s overviews and objectives, the particular challenges they are covering, research achievements on security and privacy, as well as the techniques, outcomes, and evaluations accomplished in the scope of the EU project. The book is the result of a collaborative effort among relative ongoing European Research projects in the field of privacy and security as well as related cybersecurity fields, and it is intended to explain how these projects meet the main cybersecurity and privacy challenges faced in Europe. Namely, the EU projects analyzed in the book are: ANASTACIA, SAINT, YAKSHA, FORTIKA, CYBECO, SISSDEN, CIPSEC, CS-AWARE. RED-Alert, Truessec.eu. ARIES, LIGHTest, CREDENTIAL, FutureTrust, LEPS. Challenges in Cybersecurity and Privacy - the European Research Landscape is ideal for personnel in computer/communication industries as well as academic staff and master/research students in computer science and communications networks interested in learning about cyber-security and privacy aspects

Privacy in characterizing and recruiting patients for IoHT-aided digital clinical trials

Nowadays there is a tremendous amount of smart and connected devices that produce data. The so-called IoT is so pervasive that its devices (in particular the ones that we take with us during all the day - wearables, smartphones...) often provide some insights on our lives to third parties. People habitually exchange some of their private data in order to obtain services, discounts and advantages. Sharing personal data is commonly accepted in contexts like social networks but individuals suddenly become more than concerned if a third party is interested in accessing personal health data. The healthcare systems worldwide, however, begun to take advantage of the data produced by eHealth solutions. It is clear that while on one hand the technology proved to be a great ally in the modern medicine and can lead to notable benefits, on the other hand these processes pose serious threats to our privacy. The process of testing, validating and putting on the market a new drug or medical treatment is called clinical trial. These trials are deeply impacted by the technological advancements and greatly benefit from the use of eHealth solutions. The clinical research institutes are the entities in charge of leading the trials and need to access as much health data of the patients as possible. However, at any phase of a clinical trial, the personal information of the participants should be preserved and maintained private as long as possible. During this thesis, we will introduce an architecture that protects the privacy of personal data during the first phases of digital clinical trials (namely the characterization phase and the recruiting phase), allowing potential participants to freely join trials without disclosing their personal health information without a proper reward and/or prior agreement. We will illustrate what is the trusted environment that is the most used approach in eHealth and, later, we will dig into the untrusted environment where the concept of privacy is more challenging to protect while maintaining usability of data. Our architecture maintains the individuals in full control over the flow of their personal health data. Moreover, the architecture allows the clinical research institutes to characterize the population of potentiant users without direct access to their personal data. We validated our architecture with a proof of concept that includes all the involved entities from the low level hardware up to the end application. We designed and realized the hardware capable of sensing, processing and transmitting personal health data in a privacy preserving fashion that requires little to none maintenance

Challenges in Cybersecurity and Privacy - the European Research Landscape

Cybersecurity and Privacy issues are becoming an important barrier for a trusted and dependable global digital society development. Cyber-criminals are continuously shifting their cyber-attacks specially against cyber-physical systems and IoT, since they present additional vulnerabilities due to their constrained capabilities, their unattended nature and the usage of potential untrustworthiness components. Likewise, identity-theft, fraud, personal data leakages, and other related cyber-crimes are continuously evolving, causing important damages and privacy problems for European citizens in both virtual and physical scenarios. In this context, new holistic approaches, methodologies, techniques and tools are needed to cope with those issues, and mitigate cyberattacks, by employing novel cyber-situational awareness frameworks, risk analysis and modeling, threat intelligent systems, cyber-threat information sharing methods, advanced big-data analysis techniques as well as exploiting the benefits from latest technologies such as SDN/NFV and Cloud systems. In addition, novel privacy-preserving techniques, and crypto-privacy mechanisms, identity and eID management systems, trust services, and recommendations are needed to protect citizens’ privacy while keeping usability levels. The European Commission is addressing the challenge through different means, including the Horizon 2020 Research and Innovation program, thereby financing innovative projects that can cope with the increasing cyberthreat landscape. This book introduces several cybersecurity and privacy research challenges and how they are being addressed in the scope of 15 European research projects. Each chapter is dedicated to a different funded European Research project, which aims to cope with digital security and privacy aspects, risks, threats and cybersecurity issues from a different perspective. Each chapter includes the project’s overviews and objectives, the particular challenges they are covering, research achievements on security and privacy, as well as the techniques, outcomes, and evaluations accomplished in the scope of the EU project. The book is the result of a collaborative effort among relative ongoing European Research projects in the field of privacy and security as well as related cybersecurity fields, and it is intended to explain how these projects meet the main cybersecurity and privacy challenges faced in Europe. Namely, the EU projects analyzed in the book are: ANASTACIA, SAINT, YAKSHA, FORTIKA, CYBECO, SISSDEN, CIPSEC, CS-AWARE. RED-Alert, Truessec.eu. ARIES, LIGHTest, CREDENTIAL, FutureTrust, LEPS. Challenges in Cybersecurity and Privacy - the European Research Landscape is ideal for personnel in computer/communication industries as well as academic staff and master/research students in computer science and communications networks interested in learning about cyber-security and privacy aspects

Implementing ChaCha based crypto primitives on programmable SmartNICs

Control and management plane applications such as serverless function orchestration and 4G/5G control plane functions are offloaded to smartNICs to reduce communication and processing latency. Such applications involve multiple inter-host interactions that were traditionally secured using SSL/TLS gRPC-based communication channels. Offloading the applications to smartNIC implies that we must also offload the security algorithms. Otherwise, we need to send the application messages to the host VM/container for crypto operations, negating offload benefits. We propose crypto externs for Netronome Agilio smartNICs that implement authentication and confidentiality (encryption/decryption) using the ChaCha stream cipher algorithm. AES and ChaCha are two popular cipher suites, but we chose ChaCha since none of the smartNICs have ChaCha-based crypto accelerators. However, smartNICs have restricted instruction set, and limited memory, making it difficult to implement security algorithms. This paper identifies and addresses several challenges to implement ChaCha crypto primitives successfully. Our evaluations show that our crypto extern implementation satisfies the scalability requirement of popular applications such as serverless management functions and host in-band network telemetry. © 2022 ACM

Evaluation of MRI-only based online adaptive radiotherapy of abdominal region on MR-linac

Purpose A hybrid magnetic resonance linear accelerator (MRL) can perform magnetic resonance imaging (MRI) with high soft-tissue contrast to be used for online adaptive radiotherapy (oART). To obtain electron densities needed for the oART dose calculation, a computed tomography (CT) is often deformably registered to MRI. Our aim was to evaluate an MRI-only based synthetic CT (sCT) generation as an alternative to the deformed CT (dCT)-based oART in the abdominal region. Methods The study data consisted of 57 patients who were treated on a 0.35 T MRL system mainly for abdominal tumors. Simulation MRI-CT pairs of 43 patients were used for training and validation of a prototype convolutional neural network sCT-generation algorithm, based on HighRes3DNet, for the abdominal region. For remaining test patients, sCT images were produced from simulation MRIs and daily MRIs. The dCT-based plans were re-calculated on sCT with identical calculation parameters. The sCT and dCT were compared in terms of geometric agreement and calculated dose. Results The mean and one standard deviation of the geometric agreement metrics over dCT-sCT-pairs were: mean error of 8 +/- 10 HU, mean absolute error of 49 +/- 10 HU, and Dice similarity coefficient of 55 +/- 12%, 60 +/- 5%, and 82 +/- 15% for bone, fat, and lung tissues, respectively. The dose differences between the sCT and dCT-based dose for planning target volumes were 0.5 +/- 0.9%, 0.6 +/- 0.8%, and 0.5 +/- 0.8% at D-2%, D-50%, and D-98% in physical dose and 0.8 +/- 1.4%, 0.8 +/- 1.2%, and 0.6 +/- 1.1% in biologically effective dose (BED). For organs-at-risk, the dose differences of all evaluated dose-volume histogram points were within [-4.5%, 7.8%] and [-1.1 Gy, 3.5 Gy] in both physical dose and BED. Conclusions The geometric agreement metrics were within typically reported values and most average relative dose differences were within 1%. Thus, an MRI-only sCT-based approach is a promising alternative to the current clinical practice of the abdominal oART on MRL.Peer reviewe

A Study of Automotive Security : CAN Bus Intrusion detection Systems, Attack Surface, and Regulations

The innovation in the automotive sector enhanced the technology implemented in vehicles by the manufacturers. Consequently, the overall driving experience improved, thanks to the introduction of better safety, utility, and entertainment systems. Moreover, automobiles began collecting and exchanging data with the external world through different communication protocols. However, these additions have started to attract attention from security experts. More importantly, malevolent attackers have exploited the technologies and their related attack points to carry out malicious activities to cause data security and safety issues. These issues have led to establishing standards and regulations (ISO 21434, UNECE 155, etc.) that redefine vehicle design and development by incorporating security protocols and requirements necessary to create secure automobiles. However, these documents analyze the problem at a high level and do not dwell on practical solutions implementation analysis. This work presents an in-depth study of in-vehicle communication concerns via Controller Area Network (CAN) bus safety problems analysis with different proposed solutions. Specifically, a survey of Intrusion Detection Systems developed in the literature is brought up: simulation of three CAN bus intrusion detection systems against various attacks. The results show effectiveness against disruptive attacks, i.e., with numerous messages sent in a short period of time, but conversely have difficulty detecting more targeted attacks with few transmitted packets. The solutions analysis is an excellent starting point for security engineers to be able to develop Intrusion Detection Systems for the CAN bus capable of detecting attacks that will become increasingly complex and difficult to counter over time