Secure Deployment Research Articles

LCMQSINABM: Design of a Low-power hybrid Consensus Method for QoS-aware Sidechain-based IoT Networks via Augmented Bioinspired computing Models

Security is one of the primary issues in any wireless network deployment, because, wireless nodes are susceptible to a wide-variety of internal & external attacks. These include improper authentication & access control, distributed denial of service (DDoS), sybil, spoofing, spying, masquerading, etc. Securing networks against these attacks requires an immutable, transparent, traceable, and distributed computing security model, that has minimum overheads. Most of these characteristics are fulfilled via use of blockchains, which assist in low-complexity deployment of security & hashing models. But the delay needed to scale these blockchains increases exponentially w.r.t. chain length, due to which researchers split the main blockchain into multiple sidechains. A wide variety of models are proposed by researchers for sidechain formation, and most of them are consensus dependent, which limits the scalability. Moreover, energy needed to mine blocks for these sidechains depends directly on the consensus model, encryption model, hash rules, and length of the blockchain. Thus, models proposed for sidechain formation are context-specific, and have limited scalability performance when used for multiple blockchain types. To overcome these limitations, and maintain high security performance, this text proposes design of a Low-power hybrid Consensus Method for QoS-aware Sidechain-based IoT Networks via Augmented Bioinspired computing Models. This method uses a combination of Proof-of-Work (PoW), Proof-of-Stake (PoS) & Proof-of-Authority (PoA) based consensus models, which assists in reducing its mining delay. The PoW model allows selection of nodes with higher performance, PoS allows selection of nodes with higher stake, and PoA ensures better control of IoT devices. Selection of these consensus models is done via use of an Improved Genetic Algorithm (IGA) model, that evaluates the power needed for mining, and minimizes it using a rule-based method. This is combined with a sidechain creation model, that assists in improving QoS performance via dynamically splitting the main blockchain into performance-specific sidechains. These sidechains are categorized into low-power, low-delay, and high-throughput sidechains, which are formed via Elephant Herding Optimization (EHO) model. Due to combination of IGA for consensus selection, and EHO for sidechain creation, the proposed model is able to reduce energy needed for mining by 15.4% when compared with various state-of-the-art models. It is also able to improve mining speed by 5.3%, while maintaining high security performance under different IoT Network attacks. Due to this performance enhancement, the proposed model is capable of being deployed for a wide variety of low-delay healthcare IoT, high-throughput industrial IoT, and low energy home IoT application deployments.

Reduction Model Checking for Multi-Agent Systems of Group Social Commitments

Innumerable industries now use multi-agent systems (MASs) in various contexts, including healthcare, security, and commercial deployments. It is challenging to select reliable business protocols for critically important safety-related systems (e.g., in healthcare). The verification and validation of business applications is increasingly explored concerning multi-agent systems’ group social commitments. This study explains a novel extended reduction verification method to model-check business applications’ critical specification rules using action restricted computation tree logic (ARCTL). In particular, we aim to conduct the verification process for the CTLGC logic using a reduction algorithm and show its effectiveness to handle MASs with huge models, thus, showing its importance and applicability in large real-world applications. To do so, we need to transform the CTLGC model to an ARCTL model and the CTLGC formulas into ARCTL formulas. Thus, the developed method was verified with the model-checker new symbolic model verifier (NuSMV), and it demonstrated effectiveness in the safety-critical specification rule support provision. The proposed method can verify up to 2.43462 × 1014 states MASs, which shows its effectiveness when applied to real-world applications.

Intelligent Omni-Surface Enhanced Aerial Secure Offloading

Different from conventional reflecting-only metasurfaces, intelligent omni-surfaces (IOSs) are capable of reflecting and transmitting the received signals simultaneously. As such, users located at the both sides of IOSs can be served efficiently. In this paper, a novel IOS-enhanced aerial secure offloading system is proposed in the presence of multiple ground eavesdroppers. Specifically, the IOS is adopted to prevent information leakage, improve legitimate reception quality and expand the security deployment range of unmanned aerial vehicles (UAVs). To maximize the secrecy energy efficiency (SEE) of the considered system, a non-convex resource allocation problem is formulated by allocating computing frequency, determining offloading strategy, controlling transmit power, designing phase shifts, and deploying UAV locations. The formulated problem is non-trivial and challenging to be solved directly due to the highly coupled variables. To tackle this issue, the alternating optimization technique is invoked to decouple the original one into five subproblems, and then the computing and communication settings are alternatively optimized using a low complexity iterative algorithm. Finally, simulation results demonstrate that: i) In terms of the SEE performance, our IOS-enhanced aerial secure offloading system significantly outperforms the benchmark schemes; ii) Compared with reflecting-only surfaces, IOSs can take full advantage of the flexible deployment ability of UAVs, such that their secure offloading space can be considerably expanded.

A joint orchestration of security and functionality services at network edge

Edge computing emerges as a new paradigm to provide low-latency network services in close proximity to end users. Based on the network function virtualization (NFV) technology, network services can be flexibly and scalably provisioned as virtual network function (VNF) chains deployed at edge servers. With such advantages, both the industry and research communities have done extensive studies on deploying VNF chains at network edge. The existing works mainly take an ideal assumption that the network is totally safe and there are no malicious users. Therefore, they leverage all available resources to serve their users. However, such an assumption is impractical in real networks. Security services, such as firewall, deep packet detection, intrusion detection, are always required for production networks. The existing service deployment methods fail to consider the co-existence of security services and functionality services. In this paper, we present the topic of joint deployment of both security and functionality services, wherein the security services are responsible to check the data flows before being processed by the functionality services. To solve this problem, we propose the Secure Deployment Pattern, which aims to simultaneously satisfy the security protection and QoS requirements at network edge. It divides the services into two kinds, i.e., the user-oriented functionality services, and the service provider-oriented security services. In this case, it is very challenging to jointly deploy the security services and functional services with respect to the resource and latency constraints. We formulate this problem as an integer programming model, and propose the heuristic algorithms to solve it. As far as we know, this paper is the first step, which targets at a proper orchestration of security and functionality services in edge computing. Extensive evaluations show that the proposed algorithms are effective and efficient, in terms of the execution time and the average number of served requests.

Key Aggregation Cryptosystem and Double Encryption Method for Cloud-Based Intelligent Machine Learning Techniques-Based Health Monitoring Systems.

Cloud technology is a business strategy that aims to provide the necessary material to customers depending on their needs. Individuals and cloud businesses alike have embraced the cloud storage service, which has become the most widely used service. The industries outsource their data to cloud storage space to relieve themselves of the load of dealing with redundant data contents. This must be protected to prevent the theft of personal belongings, and privacy must be improved as well. Different research projects have been suggested to ensure the safe management of the information included within the data content. The security of current research projects, on the contrary, still needs improvement. As a result, this method has been suggested to address the security concerns associated with cloud computing. The primary goal of this study effort is to offer a safe environment for cloud users while also increasing the profit of cloud resource providers by managing and securely delivering data contents to the cloud users. The bulk of sectors, including business, finance, military, and healthcare industry, do not store data in cloud-based storage systems. This technique is used to attract these kinds of customers. Increasing public acceptance, medical researchers are drawn to cloud computing because it allows them to store their study material in a centralized location and distribute and access it in a more flexible manner. They were collected from numerous individuals who were being evaluated for medical care at the time. Scalable and enhanced key aggregate cryptosystem is a protected data protection method that provides highly effective security in the healthcare industry. When parties interested in a dispute disagree on the outflow of sensitive information, this technique manages the disputes and ensures the data security deployment of a cloud-based intelligent health monitoring system for the parties involved. The encrypted data structure of medical and healthcare prescriptions is recorded as they move through the hands of patients and healthcare facilities, according to the technique recommended. The double encryption approach is used in order to raise the overall degree of security. An encryption class is created by referring to the Ciphertext ID during the encryption procedure. The keyholder is a master secret key that facilitates in the recovery of the secret keys of various monsters and creatures by acting as a conduit between them. It is transferred and stored as a single aggregate for the benefit of the patient or customer in order to make decryption more convenient and efficient. A safe connection between cloud-based intelligent health monitoring systems and healthcare organizations and their patients may be established via the use of a key aggregation cryptosystem and a double encryption approach, according to the researchers. Because of this, when compared to earlier techniques, the findings reveal that the research methodology provides high levels of security in terms of confidentiality and integrity, in addition to excellent scalability.

Energy efficient secured cluster based distributed fault diagnosis protocol for IoT

The rapid growth of internet and internet services provision offers wide scope to the industries to couple the various network models to design a flexible and simplified communication infrastructure. A significant attention paid towards Internet of things (IoT), from both academics and industries. Connecting and organizing of communication over wireless IoT network models are vulnerable to various security threats, due to the lack of inappropriate security deployment models. In addition to this, these models have not only security issues; they also have many performance issues. This research work deals with an IoT security over WSN model to overcome the security and performance issues by designing a Energy efficient secured cluster based distributed fault diagnosis protocol (EESCFD) Model which combines the self-fault diagnosis routing model using cluster based approach and block cipher to organize a secured data communication and to identify security fault and communication faults to improve communication efficiency. In addition we achieve an energy efficiency by employing concise block cipher which identifies the ideal size of block, size of key, number of rounds to perform the key operations in the cipher.

Blockchain application in P2P energy markets: social and legal aspects

Flexible and distributed energy markets are a reality that is progressively reaching many regions. Despite their clear benefits, they should be accepted by the prosumers. Additionally, blockchain technology and smart contracts have been characterised as a technological enabler for the energy sector and P2P Energy Markets (PEM). However, little research has been done to explore blockchain's user-centred perspective. Therefore, this paper analyses the reluctance and/or concerns of prosumers regarding smart contracts, and investigates their perception on blockchain within PEMs. The authors present the results of a survey conducted across several European countries addressing the implementation of automated trading systems and analysing the adoption of smart contracts. Considering that the main survey outcomes are related to the regulation and legislation uncertainty around blockchain usage, this paper explores also the fit of smart contracts from a legal perspective. Additionally, a set of recommendations to be used as the basis for the design and development of PEMs is delivered, aiming to adopt blockchain and smart contracts. As a key take-away, the authors confirm the crucial role that blockchain will play in the deployment of fair, secure, flexible and distributed energy markets by ensuring transparency in the exchange of information between prosumers and energy stakeholders.

Secure PAAS environment over hybrid cloud using load-balanced Docker containers

The purpose of this research is to provide cloud service providers (CSP) a secure platform that can be accessed for configuring secure, silent software deployment on the hybrid cloud using load-balanced Docker Containers (LBDC) that are configured with different PAAS software solutions. As many researchers in the past have worked on providing PASS platforms using either a public cloud or private cloud less research is carried out on the hybrid cloud systems and researchers who have worked on the hybrid cloud have followed a different approach to providing PAAS to organizations in need but lack in securing the PAAS platform. This research will provide cloud service providers a secure deployment of the PAAS platform for the developers on the go and will reduce the overhead of CSP to deploy the PAAS services from scratch. Compared to the other researcher’s contribution this research work provides a load-balanced containerized secure PASS platform that can be scaled on-demand and be secure while scaling the resources for peak workloads. The admins of the hybrid cloud can access and deploy the Docker containers based on the requirement laid down by the developers. Once the Admin configures the Docker container with the required PAAS services he can then easily invoke the LBDC in the hybrid cloud and deploy the PAAS platform for the developers to work on in seconds. LBDC’s will help in scalable deployment of Secure PAAS services for different locations and machines simultaneously thus reducing the cost and time required for hybrid virtual machines to get up and running for the development process by the developers of the company. CSP’s can achieve less turnaround time for deployment of secure PAAS environments for organizations.

The Ecological Value of Typical Agricultural Products: An Emergy-Based Life-Cycle Assessment Framework

Agri-products have an impact on food security, ecology protection, and crucial strategic deployment. With this respect, the economic value of agri-products should be paralleled with a non-monetary assessment of ecological value for humans. This study set up an emergy-based life-cycle assessment (Em-LCA) framework to calculate the ecosystem service (ES) and ecosystem dis-services (EDS) that was applied to six typical crops, exploring the implementation path of the agricultural eco-product value. The results showed the agriculture system mainly depends on non-renewable resources. EDS generated by China’s agri-products is higher than the ES provided by them. Nevertheless, there is a low correlation between the current price of agri-products and their greenness, but, economic value presents a rising trend with agri-product greenness increasing. Further to discussing effective approaches to sustainable agriculture, it can be seen that 1) sustainable agriculture will lead to increased greenness, but it is impossible to improve greenness indefinitely. 2) Improving greenness is an effective way to implement ecological value, another way to preserve and raise ecological value is to reduce EDS generation. 3) Reducing energy consumption leads to a decrease in EDS but it is not an appropriate way to achieve sustainable development. These findings provide meaningful suggestions for decision-makers to realize the ecological value of agri-products.

Facile and secure deployment of plastic stent through an endoscopic tapered sheath for endoscopic ultrasound-guided drainage.

Facile and secure deployment of plastic stent through an endoscopic tapered sheath for endoscopic ultrasound-guided drainage.

A Survey of Security in Cloud, Edge, and Fog Computing.

The field of information security and privacy is currently attracting a lot of research interest. Simultaneously, different computing paradigms from Cloud computing to Edge computing are already forming a unique ecosystem with different architectures, storage, and processing capabilities. The heterogeneity of this ecosystem comes with certain limitations, particularly security and privacy challenges. This systematic literature review aims to identify similarities, differences, main attacks, and countermeasures in the various paradigms mentioned. The main determining outcome points out the essential security and privacy threats. The presented results also outline important similarities and differences in Cloud, Edge, and Fog computing paradigms. Finally, the work identified that the heterogeneity of such an ecosystem does have issues and poses a great setback in the deployment of security and privacy mechanisms to counter security attacks and privacy leakages. Different deployment techniques were found in the review studies as ways to mitigate and enhance security and privacy shortcomings.

Security Assurance Model of Software Development for Global Software Development Vendors

The number of security attacks and the impact has grown considerably in the recent several years. As a result, new emerging software development models are required that assist in developing software that is secure by default. This article reviews the most widely used security software models. It proposes a new Security Assurance Model (SAM) for Software Development that is adaptable to all contemporary scenarios, emphasizing global software development (GSD) vendor companies. The SAM of Software Development was developed after studying 11 well-known development models and analyzing results obtained from a systematic literature review (SLR) and questionnaire survey. The SAM of Software Development consists of seven security assurance levels: Governance and Security Threat Analysis, Secure Requirement Analysis, Secure Design, Secure Coding, Secure Testing and Review, Secure Deployment, and Security Improvement. The security assurance levels of SAM of software development consist of 46 critical software security risks (CSSRs) and 388 practices for addressing these risks. The proposed SAM of Software Development was assessed based on a tool created by Motorola, which is used to evaluate the present state of a company’s software processes and find areas for improvement. We conducted 3 case studies on software development companies, using data from real software projects to examine the results of a practical experiment in each company. The results of the case studies indicate that the proposed SAM of Software Development helps measure the security assurance level of an organization. In addition, it can potentially serve as a framework for researchers to develop new software security measures.

Security analysis of telecommunication networks of the 5G generation

The article examines the issues of protection in telecommunication networks of the new generation based on 5G technologies. Models of secure deployment of 5G networks, Protection of subscribers and devices, Network protection, New stack of IT protocols, Protection technologies used in 5G are considered. Inheritance of security across generations of technology is shown, comparison of LTE protection with 5G protection is made.

Research and Implementation of Network Security Deployment Based on Private Cloud Security Platform

With the development of science and technology, the computer age has come. As a new type of computer network application technology, cloud computing technology is of great significance to promote China's economic development. However, in the development of cloud technology, it faces serious security problems. Although cloud providers all claim that their services are very secure in all aspects, especially in data management. However, for large enterprises, business-related data is their lifeline. Large enterprises will not put their important applications on the public cloud for operation, and private cloud has great advantages in this respect. This paper introduces the relevant concepts and network security deployment methods of cloud technology and private cloud security platform. The research on private cloud security platform is to better resist the next generation of security threats. Deploying network security on private cloud security platform can reduce the informatization cost of enterprises, public institutions and government departments and improve work efficiency.

A Multi-Message Multi-Receiver Signcryption Scheme with Edge Computing for Secure and Reliable Wireless Internet of Medical Things Communications

Thanks to recent advancements in biomedical sensors, wireless networking technologies, and information networks, traditional healthcare methods are evolving into a new healthcare infrastructure known as the Internet of Medical Things (IoMT). It enables patients in remote areas to obtain preventative or proactive healthcare services at a cheaper cost through the ease of time-independent interaction. Despite the many benefits of IoMT, the ubiquitously linked devices offer significant security and privacy concerns for patient data. In the literature, several multi-message and multi-receiver signcryption schemes have been proposed that use traditional public-key cryptography, identity-based cryptography, or certificateless cryptography methods to securely transfer patient health-related data from a variety of biomedical sensors to healthcare professionals. However, certificate management, key escrow, and key distribution are all complications with these methods. Furthermore, in terms of IoMT performance and privacy requirements, they are impractical. This article aims to include edge computing into an IoMT with secure deployment employing a multi-message and multi-receiver signcryption scheme to address these issues. In the proposed method, certificate-based signcryption and hyperelliptic curve cryptography (HECC) have been coupled for excellent performance and security. The cost study confirms that the proposed scheme is better than the existing schemes in terms of computational and communication costs.

SecDocker: Hardening the Continuous Integration Workflow

Current Continuous Integration (CI) processes face significant intrinsic cybersecurity challenges. The idea is not only to solve and test formal or regulatory security requirements of source code but also to adhere to the same principles to the CI pipeline itself. This paper presents an overview of current security issues in CI workflow. It designs, develops, and deploys a new tool for the secure deployment of a container-based CI pipeline flow without slowing down release cycles. The tool, called SecDocker for its Docker-based approach, is publicly available in GitHub. It implements a transparent application firewall based on a configuration mechanism avoiding issues in the CI workflow associated with intended or unintended container configurations. Integrated with other DevOps Engineers tools, it provides feedback from only those scenarios that match specific patterns, addressing future container security issues.

Sharpening the Axe: Identifying and Closing Gaps Within the Training Space of the South African Private Security Industry

The ever-present threat of crime in South Africa continues to drive the rise and demand for Private Security Industry (PSI) services amongst various governmental institutions, businesses and citizens to ensure their safety. This rise for the Private Security Services (PSS) persistently presents new challenges to the Private Security Industry Regulatory Authority (PSiRA) such as poor security training standards and deployment of untrained security officers attached to the Private Security Companies (PSCs), which negatively impacts the professionalism of the security industry. This study was guided by this objective: Identifying and closing the gaps within South African training space of PSI. This qualitative study was guided by the exploratory research design. The judgemental sampling technique was adopted to sample 40 participants confined to Gauteng (GP), Kwa-Zulu Natal (KZN) and Western Cape (WC) Provinces. The selected relevant stakeholders were attached to the South African Police Service (SAPS), Department of Labour (DoLl), Department of Home Affairs (DoH), National Prosecuting Authority (NPA) and the legal fraternity) and the PSI Directors and security officers to form part of the Focus Group Discussions (FGDs) and hybrid semi-structured interviews. The findings highlighted that the majority of the participants agreed that the private security industry training space is affected by security service providers letting PSiRA down by not training at, but rather engaging in, criminal activity through selling and people buying PSiRA security certificates. Some of the challenges mentioned include; poor training standards, non-compliance to legislated training standards, unqualified security training facilitators and outdated security Grades, misuse of security equipment leading to serious injuries and death, corruption in the industry, some of it being perpetrated by PSiRA inspectors, the very people who are supposed to keep the industry in check. This study recommends that, in order to overcome the challenges in the security training space, PSiRA needs to do away with the outdated security Grades by developing a new policy framework which will enable the creation of a new security-training curriculum and revise the training methods to suit the ever-changing security industry.

COVID-19 One Year on – Security and Privacy Review of Contact Tracing Mobile Apps

The ongoing Coronavirus Disease 2019 (COVID-19) pandemic has caused 3.8 million deaths since December 2019. At the current vaccination pace, this global pandemic could persist for several years. Throughout the world, contact tracing (CT) apps were developed, which play a significant role in mitigating the spread of COVID-19. This work examines the current state of security and privacy landscape of mobile CT apps. Our work is the first attempt, to our knowledge, which provides a comprehensive analysis of 70 CT apps used worldwide as of the year Q1 2021. Among other findings, we observed that 80% of them may have handled sensitive data without adequate protection, 70% of them used weak cryptographic algorithms, and 35% of them embedded data trackers. We also observed key developments in app privacy protection and security assurance initiatives. Our findings provide useful insights into the design and deployment of more secure and privacy-preserving CT apps moving forward.

Identifying and Mitigating Phishing Attack Threats in IoT Use Cases Using a Threat Modelling Approach.

Internet of things (IoT) is a technology that enables our daily life objects to connect on the Internet and to send and receive data for a meaningful purpose. In recent years, IoT has led to many revolutions in almost every sector of our society. Nevertheless, security threats to IoT devices and networks are relentlessly disruptive, because of the proliferation of Internet technologies. Phishing is one of the most prevalent threats to all Internet users, in which attackers aim to fraudulently extract sensitive information of a user or system, using fictitious emails, websites, etc. With the rapid increase in IoT devices, attackers are targeting IoT devices such as security cameras, smart cars, etc., and perpetrating phishing attacks to gain control over such vulnerable devices for malicious purposes. In recent decades, such scams have been spreading, and they have become increasingly advanced over time. By following this trend, in this paper, we propose a threat modelling approach to identify and mitigate the cyber-threats that can cause phishing attacks. We considered two significant IoT use cases, i.e., smart autonomous vehicular system and smart home. The proposed work is carried out by applying the STRIDE threat modelling approach to both use cases, to disclose all the potential threats that may cause a phishing attack. The proposed threat modelling approach can support the IoT researchers, engineers, and IoT cyber-security policymakers in securing and protecting the potential threats in IoT devices and systems in the early design stages, to ensure the secure deployment of IoT devices in critical infrastructures.

Scalable & Resilient Vehicle-Centric Certificate Revocation List Distribution in Vehicular Communication Systems

In spite of progress in securing Vehicular Communication (VC) systems, there is no consensus on how to distribute Certificate Revocation Lists (CRLs). The main challenges lie exactly in (i) crafting an efficient and timely distribution of CRLs for numerous anonymous credentials, pseudonyms, (ii) maintaining strong privacy for vehicles prior to revocation events, even with honest-but-curious system entities, (iii) and catering to computation and communication constraints of on-board units with intermittent connectivity to the infrastructure. Relying on peers to distribute the CRLs is a double-edged sword: abusive peers could "pollute" the process, thus degrading the timely CRLs distribution. In this paper, we propose a vehicle-centric solution that addresses all these challenges and thus closes a gap in the literature. Our scheme radically reduces CRL distribution overhead: each vehicle receives CRLs corresponding only to its region of operation and its actual trip duration. Moreover, a "fingerprint" of CRL 'pieces' is attached to a subset of (verifiable) pseudonyms for fast CRL 'piece' validation (while mitigating resource depletion attacks abusing the CRL distribution). Our experimental evaluation shows that our scheme is efficient, scalable, dependable, and practical: with no more than 25 KB/s of traffic load, the latest CRL can be delivered to 95% of the vehicles in a region (15 x 15 KM) within 15s, i.e., more than 40 times faster than the state-of-the-art. Overall, our scheme is a comprehensive solution that complements standards and can catalyze the deployment of secure and privacy-protecting VC systems.