Specific Security Requirements Research Articles

CARMEN: A framework for the verification and diagnosis of the specification of security requirements in cyber-physical systems

In the last years, cyber-physical systems (CPS) are receiving substantial mainstream attention especially in industrial environments, but this popularity has been accompanied by serious security challenges. A CPS is a complex system that includes hardware and software components, with different suppliers and connection protocols, forcing complex data management and storage. For this reason, the construction, verification and diagnosis of security CPS become a major challenge, which involves a correct specification of security requirements, the verification of the correct system configurations, and if necessary, the diagnosis to detect the features to be modified to obtain a security configuration. In this paper, we propose a framework for the verification and diagnosis of security requirements, according to the possible correct configurations of the CPS. The framework is based on the specification of the security requirements and their analysis supported by Model-Driven Engineering and Software Product Line Engineering (SPLE) approaches. To illustrate the usefulness, the proposal has been applied to the security requirements in an Agriculture 4.0 scenario based on automated hydroponic cultivation.

Anomaly detection in autonomous electric vehicles using AI techniques: A comprehensive survey

AbstractThe next wave in smart transportation is directed towards the design of renewable energy sources that can fuel automobile sector to shift towards the autonomous electric vehicles (AEVs). AEVs are sensor‐driven and driverless that uses artificial intelligence (AI)‐based interactions in Internet‐of‐vehicles (IoV) ecosystems. AEVs can reduce carbon footprints and trade energy with peer AEVs, smart grids (SG), and roadside units (RSUs). It supports green transportation vision. However, the sensor information, energy units, and user data are exchanged through open channels, and thus, are susceptible to various security and privacy attacks. Thus, AEVs can be remotely operated and directed by malicious entities that can propagate false updates to the peer nodes in IoV environment. This can cause the failure of components, congestion, as well as the entire disruption of IoV network. Globally researchers and security analysts have addressed solutions that pertain to specific security requirements, but still, the detection and classification of malicious AEVs is a widely studied topic. Malicious AEVs exhibit an anomaly behavior that differentiates them from normal AEVs, and thereby, the detection of anomalous AEVs and classification of anomaly type is required. Motivated from the aforementioned facts, the survey presents a systematic outlook of AI techniques in anomaly detection of AEVs. A solution taxonomy is proposed based on research gaps in the existing surveys, and the evaluation metrics for AI‐based anomaly detection are discussed. The open challenges and issues in AI deployments are discussed and a case study is presented on anomaly classification through a weighted ensemble technique. Thus, the proposed survey is designed to guide the manufacturing industry, AI practitioners, and researchers worldwide to formulate and design accurate and precise mechanisms to detect anomalies.

Research on RFID authentication Protocol in Internet of Vehicles

With the development of Internet of Vehicles, radio frequency identification technology (RFID) has been widely used in vehicle networks. The classic RFID authentication scheme cannot meet the special security and confidentiality requirements of RFID in Internet of Vehicles. This paper proposes an RFID authentication protocol in the Internet of Vehicles based on the certification center (CA). Through the certification center, you can avoid the Dos attack problem faced by the back-end server and reduce the server's computing burden. At the same time, through the authentication center, the identity authentication of the back-end server, reader and vehicle tag is indirectly achieved, which solves the problems of replay and malicious tracking that are often faced in RFID. The theory of formal logic language GNY proves that the protocol has high security in the Internet of Vehicles.

Threat-Specific Security Risk Evaluation in the Cloud

Existing security risk evaluation approaches (e.g., asset-based) do not consider specific security requirements of individual cloud computing clients in the security risk evaluation. In this paper, we propose a threat-specific risk evaluation approach that uses various security attributes of the cloud (e.g., vulnerability information, the probability of an attack, and the impact of each attack associated with the identified threat(s)) as well as the client-specific security requirements in the cloud. Our approach allows a security administrator of the cloud provider to make fine-grained decisions for selecting mitigation strategies in order to protect the outsourced computing assets of individual clients based on their specific security needs against specific threats. This is different from the existing asset-based approaches where they do not have the functionalities to provide the security evaluation of the cloud with respect to specific threats. On the other hand, the proposed approach enables security administrators to compute a range of more effective client-specific countermeasures with respect to the importance of security requirements and threats. The experimental evaluation results demonstrate that effective security solutions vary due to specific threats prioritized by different clients for an application in the cloud. Further, the proposed approach is not limited to only the cloud-based systems, but can easily be adopted to other networked systems. We have also developed a software tool to support the proposed approach.

A Sensitive Data Access Model in Support of Learning Health Systems

Given the ever-growing body of knowledge, healthcare improvement hinges more than ever on efficient knowledge transfer to clinicians and patients. Promoted initially by the Institute of Medicine, the Learning Health System (LHS) framework emerged in the early 2000s. It places focus on learning cycles where care delivery is tightly coupled with research activities, which in turn is closely tied to knowledge transfer, ultimately injecting solid improvements into medical practice. Sensitive health data access across multiple organisations is therefore paramount to support LHSs. While the LHS vision is well established, security requirements to support them are not. Health data exchange approaches have been implemented (e.g., HL7 FHIR) or proposed (e.g., blockchain-based methods), but none cover the entire LHS requirement spectrum. To address this, the Sensitive Data Access Model (SDAM) is proposed. Using a representation of agents and processes of data access systems, specific security requirements are presented and the SDAM layer architecture is described, with an emphasis on its mix-network dynamic topology approach. A clinical application benefiting from the model is subsequently presented and an analysis evaluates the security properties and vulnerability mitigation strategies offered by a protocol suite following SDAM and in parallel, by FHIR.

Revealing Development Trends in Blockchain-Based 5G Network Technologies through Patent Analysis

The fifth-generation (5G) network has special communication and security requirements including high reliability, low latency, precise automatic control, secure covert transmission, and evidence traceability. The 5G network combined with blockchain technology just meets this demand, so it is driving a rapidly growing volume of patent applications. This study proposes application scenarios, architecture diagrams, and patent analysis methods for blockchain-based 5G network technologies, beginning with a network architecture using mobile edge computing (MEC) and blockchain as independent platform components to solve MEC load pressure. In the patent analysis, a patent cluster map of blockchain-based 5G networks is proposed to analyze the intersection of technical application fields. The bottleneck period of technological development is presented for leading countries and enterprises in the technological development of blockchain-based 5G network, highlighting relative advantages and disadvantages. Specifically, to extract the core international patent classification (IPC) key technologies and their mutual interrelatedness, we use network topology analysis to establish an IPC network topology diagram through node global and local topology characteristics, thus revealing hotspots of IPC technology research and the characteristics of the technology relationship system. The findings provide a very useful reference for the formulation of government strategy to assist in the implementation and development of blockchain-based 5G network technologies for future smart cities.

Heterogeneous identity trust management method based on risk assessment

The cross-trust domain environment in which heterogeneous identity alliances are located often does not have a completely trusted centralized trust root, and different trust domains and entities also have specific security requirements. In view of the above problems, we believe that trust measurement of cross-domain identities based on risk assessment is an effective method to achieve decentralized proof of user identities in heterogeneous cyberspace. There are various risk assessment models. We choose the more mature attack graph theory in the existing research to apply to the new field of cross-trust domain management of heterogeneous identities. We propose an attribute attack graph evaluation model to evaluate cross-domain identities through risk measurement of attributes. In addition, heterogeneous identity alliances also have architectural risks, especially the risk of decentralized underlying structures. In response to this problem, we identify the risk of the identity alliance infrastructure, and combine the risk assessment and presentation system design to verify the principle.

Secure and scalable access control protocol for IoT environment

Smart applications based on IoT has gained huge momentum in recent times. Typically, these applications involve the deployment of smart devices within the perception layer of three-tier IoT architecture. The smart devices may be required to be re-deployed due to adversary attacks, or outage of power. Deployment of new smart devices within the perception layer of IoT based applications is a significant security concern. The deployed smart device can be a malicious node that can disrupt the complete network operations. An access control protocol regulates the deployment of smart devices within the perception layer. Besides obliging the resource constraint nature of smart devices, an access control protocol must also fulfill specific security and functional requirements for its practical consideration. In this paper, an access control protocol based on Elliptical Curve Cryptography (ECC) has been presented. Besides sufficing to all other major security and functional requirements, the proposed protocol is also scalable and independent of clock synchronization issues. The correctness and the soundness of the proposed protocol has been validated using BAN logic. The proposed protocol has also been formally validated using automated validation of internet security protocols and applications (AVISPA) and Scyther tools. The proposed protocol has been compared with relevant existing schemes on various security and functional requirements. The comparison suggests that the proposed protocol has a better trade-off as compared to relevant existing schemes.

Abstract IA04: Data-driven recruitment: Implementation of digital marketing strategies for improved participant response rates and retention

Abstract Background: Decline in epidemiology cohort response rates has been documented over decades, with precipitous declines in recent years. Incentives and repeated contact attempts have been shown to increase retention to varying degrees, but the effects of the different types of incentives and methods of contact—details necessary for reliable replication—remain poorly understood. Numerous factors related to study implementation and participant characteristics likely affect response rates, but few cohort studies have published the detailed empirical data that would be necessary to assess their effect. The small number of cohort studies that have published analyses of their recruitment protocols raises the question of how many studies are systematically and rigorously examining their methods. A 2011 review suggested that cohort studies may be less likely to engage in these activities due to concerns of risk to participant loyalty and the cost of assessment. Epidemiology cohorts often involve many concurrent activities and overlapping projects, which may also contribute to the complexity of the task. Considering the long duration of cohort studies, some may perceive that study staff can accurately intuit best practices. However, these challenges are not unique to epidemiology cohorts. The private sector is also concerned with attracting and retaining customers, and as such, companies have developed tools that enable rapid, low-cost reporting on their methods. In the field of marketing, customer relationship management (CRM) systems facilitate both the desired outcome (a customer buying a product) and the collection of data to identify factors that influenced the outcome. Aspects of these targeted marketing approaches and their related software tools provide both a model and a means by which epidemiology cohorts can better understand the constellation of factors that affect attrition among their own populations. Methods: The California Teachers Study (CTS) is a large prospective cancer epidemiology cohort that began in 1995. Since 2013, the CTS has used a commercially available CRM platform, modified with a variety of native applications (apps) and integrations, to manage participant recruitment and data collection for multiple projects. To manage a large-scale biobanking project and multiple tissue collection projects, we began with the platform’s standard contact data management and activity tracking features. We added an app for geolocation fieldwork management and a custom mobile app for surveys and biospecimen chain-of-custody tracking. To manage two follow-up questionnaires, we used available integrations for survey development, email marketing automation, a cloud-based call center with automated activity logging, and a web form for participants to submit information securely from our study website. Central features of all projects have included native reports and dashboards, workflow automations that reduce data entry, and data security measures. Results: The CRM platform has scaled to meet the needs of multiple concurrent projects with highly varied study designs and staffing requirements. By conducting our recruitment activities within the CRM, each interaction with the system (an incoming call from a participant, a blood collection, an automated survey reminder) passively generates useful metadata. These metadata, in concert with structured and unstructured data from participants and staff, enable timely monitoring and retrospective analysis using native reporting tools within the system. The ability to view and analyze clean data from the outset of each project revealed key—and sometimes unexpected—factors that were influencing response. Analysis of data across projects has revealed that characteristics of participants, staff, protocol decisions, technology, and equipment all influence outcomes in distinct ways. Conclusion: Existing commercially available tools, such as a CRM system, can be readily configured to meet the specific research, process, and security requirements of population sciences research. In the CTS, using a CRM system helped reveal that different factors affected participation differently, even within the same project. This presentation will discuss these factors, the approaches studies can use to collect data about these factors, and lessons learned about ways to further improve response rates. Broader adoption of CRM tools could enable the type of data collection and analysis necessary to more precisely define the factors that affect participation and develop more targeted and successful recruitment methods. Citation Format: Jennifer Benbow. Data-driven recruitment: Implementation of digital marketing strategies for improved participant response rates and retention [abstract]. In: Proceedings of the AACR Special Conference on Modernizing Population Sciences in the Digital Age; 2019 Feb 19-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(9 Suppl):Abstract nr IA04.

Secure and practical access control mechanism for WSN with node privacy

An access control mechanism plays a critical role in new node deployment within a resource-constrained Wireless Sensor Networks. The deployment of a new node is inevitable either due to the outage of power or nodes getting compromised due to the adversary’s attacks. The access control scheme prevents malicious node deployment and also allows a new node to establish a shared key with its neighbors for secure communication. Besides having low communication and computational overheads, an access control mechanism must suffice to specific security and functional requirements for their practical implementations. In this paper, a provable and practical access control scheme based on Elliptical Curve Cryptography (ECC) has been presented. The proposed access control scheme supports node privacy while addressing all other major functional and security requirements. The formal validation of the proposed scheme has been carried out using automated validation of internet security protocols and applications (AVISPA) and Scyther tools. A comparative study of the proposed scheme with the existing schemes has been carried out on various security and functional requirements suggesting a better trade-off. Finally, practical experimentation on TinyOS and MICAz motes has been carried out to provide detailed energy analysis and test-bed implementation of the proposed scheme.

Model-based security analysis of feature-oriented software product lines

Today's software systems are too complex to ensure security after the fact – security has to be built into systems by design. To this end, model-based techniques such as UMLsec support the design-time specification and analysis of security requirements by providing custom model annotations and checks. Yet, a particularly challenging type of complexity arises from the variability of software product lines. Analyzing the security of all products separately is generally infeasible. In this work, we propose SecPL, a methodology for ensuring security in a software product line. SecPL allows developers to annotate the system design model with product-line variability and security requirements. To keep the exponentially large configuration space tractable during security checks, SecPL provides a family-based security analysis. In our experiments, this analysis outperforms the naive strategy of checking all products individually. Finally, we present the results of a user study that indicates the usability of our overall methodology.

Recent Developments on Security and Privacy of V2V & V2I Communications: A Literature Review

In the recent years Intelligent Transportation Systems and associated technologies have progressed significantly, including services based on wireless communications between vehicles (V2V) and infrastructure (V2I). In order to increase the trustworthiness of these communications, and convince drivers to adopt the new technologies, specific security and privacy requirements need to be addressed, using Vehicular Ad Hoc Networks (VANETs). To maintain VANET′s security and eliminate possible attacks, mechanisms are to be developed. In this paper, previous researches are reviewed aiming to provide information concerning matches between an attack and a solution in a VANET environment.

Design of Multimedia Education Network Security and Intrusion Detection System

The existing multimedia wireless network security detection technology cannot meet the requirements of wireless network security detection. Therefore, based on the special security requirements of multimedia wireless networks, this paper constructed a multimedia wireless network security detection system that meets the actual situation of the organization. The system was designed using the B/S architecture and used Django as the framework for system development. The system presentation layer mainly presents the system page to the user and passes the user request. Simultaneously, in this paper, the application of PrefixSpan algorithm in anomaly detection was studied and experimental analysis was carried out. The experimental results are in line with expectations. This verifies the effectiveness of the proposed system and provides a theoretical reference for subsequent related research.

A topology and risk-aware access control framework for cyber-physical space

Cyber-physical space is a spatial environment that integrates the cyber world and the physical world, aiming to provide an intelligent environment for users to conduct their day-to-day activities. The interplay between the cyber space and physical space proposes specific security requirements that are not captured by traditional access control frameworks. On one hand, the security of the physical space and the cyber space should be both concerned in the cyber-physical space. On the other hand, the bad results caused by failure in providing secure policy enforcement may directly affect the controlled physical world. In this paper, we propose an effective access control framework for the cyber-physical space. Firstly, a topology-aware access control (TAAC) model is proposed. It can express the cyber access control, the physical access control, and the interaction access control simultaneously. Secondly, a risk assessment approach is proposed for the policy enforcement phase. It is used to evaluate the user behavior and ensures that the suspicious behaviors executed by authorized users can be handled correctly. Thirdly, we propose a role activation algorithm to ensure that the objects are accessed only by legal and honest users. Finally, we evaluate our approach by using an illustrative example and the performance analysis. The results demonstrate the feasibility of our approach.

Fair Data Transactions Across Private Databases

In this era of big data, data transactions are becoming more frequent and bringing new benefits for both data buyers and providers. However, there are no data transaction schemes to satisfy the special security and business requirements of data transactions. In this paper, we introduce the requirements in practical data transaction processes and compare the differences of requirements and techniques between data transaction and traditional data sharing. Next, we propose and implement the first data transaction scheme based on a newly defined concept probabilistic commutative encryption, which makes the decryption order of a probabilistic encryption algorithm and a deterministic encryption algorithm commutative. Since the security concerns of both sides can be achieved in a malicious model, our scheme is fair to both data buyers and data providers from a business perspective. Furthermore, our scheme allows data transaction to be partly outsourced to a semi-honest cloud storage platform.

Toward the automation of threat modeling and risk assessment in IoT systems

The Internet of Things (IoT) has recently become one of the most relevant emerging technologies in the IT landscape. IoT systems are characterized by the high heterogeneity of involved architectural components (e.g., device platforms, services, networks, architectures) and involve a multiplicity of application domains. In the IoT scenario, the identification of specific security requirements and the security design are very complex and expensive tasks, since they heavily depend on the configuration deployment actually in place and require security experts. In order to overcome these issues, we propose an approach aimed at supporting the security analysis of an IoT system by means of an almost completely automated process for threat modeling and risk assessment, which also helps identify the security controls to implement in order to mitigate existing security risks. We demonstrate the effectiveness of the approach by discussing its application to a home automation system, built on top of commercial IoT products.

The Role of Theater of the Oppressed on Correction and Rehabilitation of Prisoners (Case Study: Yazd Province Prisons)

Nowadays attention to the function of theater in various social domains is considered by artists, sociologists and psychologists. Among the various types of theater functions, educational work and behavior modification in the form of theatrical theater and theater therapy in Iran are more than welcome. The audience of this type of theater is mostly those who feel the need to change their behavior, lifestyle, and thought. But due to the limitations of the performance of this show, such as the creation of appropriate text, the effective and efficient application space of artists in this way of communicating effectively, some social groups have less use of this type of display. The prisoners' group is less likely to participate in this way than the rest of the groups, given the special security and protection requirements. On the other hand, the prisoners' problems require that, along with the usual methods of rehabilitation and improvement of education, new and more effective methods be used and their effects published. Therefore, the functioning in prisons, which has so far been neglected, should be investigated in a scientific and analytical manner. The statistical population of this research includes 135 prisoners in Yazd province. The research results show that theater is effective in reforming prisoners.

A Novel Risk Assessment Methodology for SCADA Maritime Logistics Environments

In recent years maritime logistics infrastructures are the global links among societies and economies. This challenges adversaries to intrude on the cyber-dependent ICTs by performing high-level intelligent techniques. A potential cyber-attack on such infrastructures can cause tremendous damages starting from supply chain service disruption ending up with threatening the whole human welfare. Current risk management policies embed significant limitations in terms of capturing the specific security requirements of ICTs and control/monitoring devices, such as IoT platforms, satellites and time installations, which are primary functioning for the provision of Maritime Logistics and Supply Chain (MLoSC) services. This work presents a novel risk assessment methodology capable of addressing the security particularities and specificities of the complex nature of SCADA infrastructures and Cyber-Physical Systems (CPSs) of the Maritime Logistics Industry. The methodology identifies asset vulnerabilities and threats to estimate the cyber-risks and their cascading effects within the supply chain, introducing a set of subsequent security assessment services. The utilization of these services is demonstrated via a critical, real-life SCADA scenario indicating how they can facilitate supply chain operators in comprehending the threat landscape of their infrastructures and guide them how to adopt optimal mitigation strategies to counter or eliminate their cyber-risks.

A biometric security scheme for wireless body area networks

Wireless body area networks (WBANs) are receiving significant interest as the next generation of wireless networks and emerging technology in the field of health monitoring. One of the most important factors for the acceptance of WBANs is the provision of appropriate security and access control mechanisms. Due to its nature in transferring the patients' sensitive data, WBAN has both classical and specific security requirements. In this paper, we survey such requirements and propose a new security scheme for satisfying them in WBANs. The proposed scheme deals with the overall network architecture, including intra- and inter-WBAN tiers, and proposes two mutual authentication and key exchange protocols for diverse WBAN environments. In our scheme, we use biometrics as one part of the solution for authentication and key exchange, and the simple password three-party key exchange protocol as the other part of the WBAN security. Our scheme meets security requirements along with energy-constraint considerations. We verify our scheme through BAN Logic. Unlike the majority of the existing security protocols, our scheme proposes a solution for entire WBANs communications, from biosensors to the medical server as a trusted third party.

Modeling Security and Privacy Requirements: a Use Case-Driven Approach

Context: Modern internet-based services, ranging from food-delivery to home-caring, leverage the availability of multiple programmable devices to provide handy services tailored to end-user needs. These services are delivered through an ecosystem of device-specific software components and interfaces (e.g., mobile and wearable device applications). Since they often handle private information (e.g., location and health status), their security and privacy requirements are of crucial importance. Defining and analyzing those requirements is a significant challenge due to the multiple types of software components and devices integrated into software ecosystems. Each software component presents peculiarities that often depend on the context and the devices the component interact with, and that must be considered when dealing with security and privacy requirements. Objective: In this paper, we propose, apply, and assess a modeling method that supports the specification of security and privacy requirements in a structured and analyzable form. Our motivation is that, in many contexts, use cases are common practice for the elicitation of functional requirements and should also be adapted for describing security requirements. Method: We integrate an existing approach for modeling security and privacy requirements in terms of security threats, their mitigations, and their relations to use cases in a misuse case diagram. We introduce new security-related templates, i.e., a mitigation template and a misuse case template for specifying mitigation schemes and misuse case specifications in a structured and analyzable manner. Natural language processing can then be used to automatically report inconsistencies among artifacts and between the templates and specifications. Results: We successfully applied our approach to an industrial healthcare project and report lessons learned and results from structured interviews with engineers. Conclusion: Since our approach supports the precise specification and analysis of security threats, threat scenarios and their mitigations, it also supports decision making and the analysis of compliance to standards.