Biblio

Data Protection and Consenting Communication Mechanisms (DPCCMs) enable users to express their privacy decisions and manage their online consent. Thus, they can become a crucial means of protecting individuals' online privacy and agency, thereby replacing the current problematic practices such as “consent dialogues”. Based on an in-depth analysis of different DPCCMs, we propose an interdisciplinary set of factors that can be used for a comparison of such mechanisms. Moreover, we use the results from a qualitative expert study to identify some of the main multidisciplinary challenges that DPCCMs should address to become widely adopted data privacy mechanisms. We leverage both the factors and the challenges to compare two current open specifications, i.e. the Advanced Data Protection Control (ADPC) and the Global Privacy Control (GPC), and discuss future work.

In the deep nano-scale regime, reliability has emerged as one of the major design issues for high-density integrated systems. Among others, key reliability-related issues are soft errors, high temperature, and aging effects (e.g., NBTI-Negative Bias Temperature Instability), which jeopardize the correct applications' execution. Tremendous amount of research effort has been invested at individual system layers. Moreover, in the era of growing cyber-security threats, modern computing systems experience a wide range of security threats at different layers of the software and hardware stacks. However, considering the escalating reliability and security costs, designing a highly reliable and secure system would require engaging multiple system layers (i.e. both hardware and software) to achieve cost-effective robustness. This talk provides an overview of important reliability issues, prominent state-of-the-art techniques, and various hardwaresoftware collaborative reliability modeling and optimization techniques developed at our lab, with a focus on the recent works on ML-based reliability techniques. Afterwards, this talk will also discuss how advanced ML techniques can be leveraged to devise new types of hardware security attacks, for instance on logic locked circuits. Towards the end of the talk, I will also give a quick pitch on the reliability and security challenges for the embedded machine learning (ML) on resource/energy-constrained devices subjected to unpredictable and harsh scenarios.

In Indonesia, there have been many certificates forgery happened. The lack of security system for the certificate and the difficulty in verification process toward the authenticity certificate become the main factor of the certificate forgery cases happen. The aim of this research is to improve the security system such digital signature and QR code to authenticate the authenticity certificate and to facilitate the user in verify their certificate and also to minimize the certificate forgery cases. The aim of this research is to improve the security system such digital signature and QR code to authenticate the authenticity certificate and to facilitate the user in verify their certificate and also to minimize the certificate forgery cases. The application is built in web system to facilitate the user to access it everywhere and any time. This research uses Research and Development method for problem analysis and to develop application using Software Development Life Cycle method with waterfall approach. Black box testing is chosen as testing method for each function in this system. The result of this research is creatcate application that’s designed to support the publishing and the verification of the electronic authenticity certificate by online. There are two main schemes in system: the scheme in making e-certificate and the scheme of verification QR Code. There is the electronic professional certificate application by applying digital signature and QR Code. It can publish e-certificate that can prevent from criminal action such certificate forgery, that’s showed in implementation and can be proven in test.

Because Bitcoin P2P networking is permissionless by the application requirement, it is vulnerable against networking threats based on identity/credential manipulations such as Sybil and spoofing attacks. The current Bitcoin implementation keeps track of its peer's networking misbehaviors through ban score. In this paper, we investigate the security problems of the ban-score mechanism and discover that the ban score is not only ineffective against the Bitcoin Message-based DoS attacks but also vulnerable to a Defamation attack. In the Defamation attack, the network adversary can exploit the ban-score mechanism to defame innocent peers.

Internet of Things (IoT) devices are ubiquitous, with web cameras, smart refrigerators, and digital assistants appearing in homes, offices, and public spaces. However, these devices are lacking in security measures due to their low time to market and insufficient funding for security research and development. In order to improve the security of IoTs, we have defined novel security metrics based on generic IoT characteristics. Furthermore, we have developed automation for experimentation with IoT devices that results to repeatable and reproducible calculations of security metrics within a realistic IoT testbed. Our results demonstrate that repeatable IoT security measurements are feasible with automation. They prove quantitatively intuitive hypotheses. For example, an large number of inbound / outbound network connections contributes to higher probability of compromise or measuring password strength leads to a robust estimation of IoT security.

The internal laboratory directed research and development (LDRD) project Infrastructure eXpression (IX) at the Idaho National Laboratory (INL), is based on codifying infrastructure to support automatic applicability to emerging cyber issues, enabling automated cyber responses, codifying attack surfaces, and analysis of cyber impacts to our nation's most critical infrastructure. IX uses the Structured Threat Information eXpression (STIX) open international standard version 2.1 which supports STIX Cyber Observable (SCO) to codify infrastructure characteristics and exposures. Using these codified infrastructures, STIX Relationship Objects (SRO) connect to STIX Domain Objects (SDO) used for modeling cyber threat used to create attack surfaces integrated with specific infrastructure. This IX model creates a shareable, actionable and implementable attack surface that is updateable with emerging threat or infrastructure modifications. Enrichment of cyber threat information includes attack patterns, indicators, courses of action, malware and threat actors. Codifying infrastructure in IX enables creation of software and hardware bill of materials (SBoM/HBoM) information, analysis of emerging cyber vulnerabilities including supply chain threat to infrastructure.

Mitigation of dangers posed by authorized and trusted insiders to the organization is a challenging Cyber Security issue. Despite state-of-the-art cyber security practices, malicious insiders present serious threat for the enterprises due to their wider access to organizational resources (Physical, Cyber) and good knowledge of internal processes with potential vulnerabilities. The issue becomes particularly important for isolated (air-gapped) computer networks, normally used by security sensitive organizations such as government, research and development, critical infrastructure (e.g. power, nuclear), finance, and military. Such facilities are difficult to compromise from outside; however, are quite much prone to insider threats. Although many insider threat taxonomies exist for generic computer networks; yet, the existing taxonomies do not effectively address the issue of Insider Threat in isolated computer networks. Thereby, we have developed an insider threat taxonomy specific to isolated computer networks focusing on actions performed by the trusted individual(s), Our methodology is to identify limitations in existing taxonomies and map real world insider threat cases on proposed taxonomy. We argue that for successful attack in an isolated computer network, the attack must manifest in both Physical and Cyber world. The proposed taxonomy systematically classifies different aspects of the problem into separate dimensions and branches out these dimensions into further sub-categories without loss of general applicability. Our multi-dimensional hierarchical taxonomy provides comprehensive treatment of the insider threat problem in isolated computer networks; thus, improving situational awareness of the security analyst and helps in determining proper countermeasures against perceived threats. Although many insider threat taxonomies exist for generic computer networks; yet, the existing taxonomies do not effectively address the issue of Insider Threat in isolated computer networks. Thereby, we have developed an insider threat taxonomy specific to isolated computer networks focusing on actions performed by the trusted individual(s), Our methodology is to identify limitations in existing taxonomies and map real world insider threat cases on proposed taxonomy. We argue that for successful attack in an isolated computer network, the attack must manifest in both Physical and Cyber world. The proposed taxonomy systematically classifies different aspects of the problem into separate dimensions and branches out these dimensions into further sub-categories without loss of general applicability. Our multi-dimensional hierarchical taxonomy provides comprehensive treatment of the insider threat problem in isolated computer networks; thus, improving situational awareness of the security analyst and helps in determining proper countermeasures against perceived threats. The proposed taxonomy systematically classifies different aspects of the problem into separate dimensions and branches out these dimensions into further sub-categories without loss of general applicability. Our multi-dimensional hierarchical taxonomy provides comprehensive treatment of the insider threat problem in isolated computer networks; thus, improving situational awareness of the security analyst and helps in determining proper countermeasures against perceived threats.

As the core of the third information revolution, the Internet of things plays an important role in the development of the times. According to the relevant investigation and research, we can find that the research on the Internet of things is still in the stage of LAN and private network, and its open advantages have not been fully utilized[1]. In this context, RFID technology as the core technology of the Internet of things, the security protocol plays an important role in the normal use of the technology. With the continuous development of Internet information technology, the disadvantages of security protocol become more and more obvious. These problems seriously affect the popularity of Internet of things technology. Therefore, in the future work, the relevant staff need to continue to strengthen research, according to the future development plan, effectively play the advantages of technology, and further promote its development.

The aim of this work is to perform an analysis on Technology Transfer strategies for the development of Serious Games at Public National Universities. The results can be extrapolated to other research topics and institutions. First of all, the University role as a producer of knowledge is studied, and possible scenarios for Technology Transfer to third-parties are considered. Moreover, the actors involved in the research and development processes and their corresponding Intellectual Property rights on the Research Results are identified and analysed. Finally, an Intellectual Property Rights protection analysis is undertaken to the different components of a Serious Game type of product, through the modalities of invention patents, utility models, industrial models and designs, brands and author rights. The work concludes that public universities are best fitted as knowledge factories, and the most promising scenario in Technology Transfer is that universities manage their Intellectual Property Rights and licence them to third-party institutions to handle commercialization, while keeping favorable conditions to finance subsequent research and ensuring that products derived from Research Results will be reachable by the society.

This paper describes the goals of the ATMOSPHERE project, which is a multi-institutional research and development (R&D) effort aiming at designing and implementing a framework and platform to develop, build, deploy, measure and evolve trustworthy, cloud-enabled applications. The proposed system addresses the federation of geographically distributed cloud computing providers that rely on lightweight virtualization, and provide access to heterogeneous sets of resources. In addition, the system also considers both classic trustworthiness properties from the systems community, such as dependability and security, and from the machine learning community, such as fairness and transparency. We present the architecture that has been proposed to address these challenges and discuss some preliminary results.

The elusive science of security. Science advances when research results build upon prior findings through the evolution of hypotheses and theories about the fundamental relationships among variables within a context and considering the threats and limitations of the work. Some hypothesize that, through this science of security, the industry can take a more principled and systematic approach to securing systems, rather than reacting to the latest move by attackers. Others debate the utility of a science of security.

Stealing confidential information from a database has become a severe vulnerability issue for web applications. The attacks can be prevented by defining a whitelist of SQL queries issued by web applications and detecting queries not in list. For large-scale web applications, automated generation of the whitelist is conducted because manually defining numerous query patterns is impractical for developers. Conventional methods for automated generation are unable to detect attacks immediately because of the long time required for collecting legitimate queries. Moreover, they require application-specific implementations that reduce the versatility of the methods. As described herein, we propose a method to generate a whitelist automatically using queries issued during web application tests. Our proposed method uses the queries generated during application tests. It is independent of specific applications, which yields improved timeliness against attacks and versatility for multiple applications.

Generative policies enable devices to generate their own policies that are validated, consistent and conflict free. This autonomy is required for security policy generation to deal with the large number of smart devices per person that will soon become reality. In this paper, we discuss the research issues that have to be addressed in order for devices involved in security enforcement to automatically generate their security policies - enabling policy-based autonomous security management. We discuss the challenges involved in the task of automatic security policy generation, and outline some approaches based om machine learning that may potentially provide a solution to the same.