Biblio

Zero trust security model has been picking up adoption in various organizations due to its various advantages. Data quality is still one of the fundamental challenges in data curation in many organizations where data consumers don’t trust data due to associated quality issues. As a result, there is a lack of confidence in making business decisions based on data. We design a model based on the zero trust security model to demonstrate how the trust of data consumers can be established. We present a sample application to distinguish the traditional approach from the zero trust based data quality framework.

This short paper argues that current conceptions in trust formation scholarship miss the context of zero trust, a practice growing in importance in cyber security. The contribution of this paper presents a novel approach to help conceptualize and operationalize zero trust and a call for a research agenda. Further work will expand this model and explore the implications of zero trust in future digital systems.

Network-on-Chip (NoC) is widely used as an efficient communication architecture in multi-core and many-core System-on-Chips (SoCs). However, the shared communication resources in NoCs, e.g., channels, buffers, and routers might be used to conduct attacks compromising the security of NoC-based SoCs. Almost all of the proposed encryption-based protection methods in the literature need to leave some parts of the packet unencrypted to allow the routers to process/forward packets accordingly. This uncovers the source/destination information of the packet to malicious routers, which can be used in various attacks. In this paper, we propose the idea of secure anonymous routing with minimal hardware overhead to hide the source/destination information while exchanging secure information over the network. The proposed method uses a novel source-routing algorithm that works with encrypted destination addresses and prevents malicious routers from discovering the source/destination of secure packets. To support our proposal, we have designed and implemented a new NoC architecture that works with encrypted addresses. The conducted hardware evaluations show that the proposed security solution combats the security threats at an affordable cost of 1% area and 10% power overheads chip-wide.

In the information age, computer network technology has covered different areas of social life and involved various fields, and artificial intelligence, as an emerging technology with a very rapid development momentum in recent years, is important in promoting the development of computer network systems. This article explains the concept of artificial intelligence technology, describes the problems faced by computer networks, further analyses the advantages of artificial intelligence and the inevitability of application in network technology, and then studies the application of artificial intelligence in computer network technology.

The cutting edge of Industry 4.0 has driven everything to be converted to disruptive innovation and digitalized. This digital revolution is imprinted by modern and advanced technology that takes advantage of Big Data and Artificial Intelligence (AI) to nurture from automatic learning systems, smart city, smart energy, smart factory to the edge computing technology, and so on. To harness an appealing, noteworthy, and leading development in smart manufacturing industry, the modern industrial sciences and technologies such as Big Data, Artificial Intelligence, Internet of things, and Edge Computing have to be integrated cooperatively. Accordingly, a suggestion on the integration is presented in this paper. This proposed paper describes the design and implementation of big data platform for intelligence industrial internet of things sensor monitoring system and conveys a prediction of any upcoming errors beforehand. The architecture design is based on edge computing and artificial intelligence. To extend more precisely, industrial internet of things sensor here is about the condition monitoring sensor data - vibration, temperature, related humidity, and barometric pressure inside facility manufacturing factory.

Recent technological advancements have proliferated the use of small embedded devices for collecting, processing, and transferring the security-critical information. The Internet of Things (IoT) has enabled remote access and control of these network-connected devices. Consequently, an attacker can exploit security vulnerabilities and compromise these devices. In this context, the secure boot becomes a useful security mechanism to verify the integrity and authenticity of the software state of the devices. However, the current secure boot schemes focus on detecting the presence of potential malware on the device but not on disinfecting and restoring the software to a benign state. This manuscript presents CARE - the first secure boot framework that provides malicious code modification attack detection, resilience, and onboard recovery mechanism for the compromised devices. The framework uses a prototype hybrid CARE: Code Authentication and Resilience Engine to verify the integrity and authenticity of the software and restore it to a benign state. It uses Physical Memory Protection (PMP) and other security enchaining techniques of RISC-V processor to provide resilience from modern attacks. The state-of-the-art comparison and performance analysis results indicate that the proposed secure boot framework provides promising resilience and recovery mechanism with very little (8%) performance and resource overhead.

Rapid development of cloud storage services, users are allowed to upload heavy storage and computational cost to cloud to reduce the local resource and energy consumption. While people enjoy the desirable benefits from the cloud storage service, critical security concerns in data outsourcing have been raised seriously. In the cloud storage service, data owner loses the physical control of the data and these data are fully controlled by the cloud server. As such, the integrity of outsourced data is being put at risk in reality. Remote data integrity checking (RDIC) is an effective solution to checking the integrity of uploaded data. However, most RDIC schemes are rely on traditional public key infrastructure (PKI), which leads communication and storage overhead due to the certificate management. Identity-based RDIC scheme is not need the storage management, but it has a drawback of key escrow. To solve these problems, we propose a practical certificateless RDIC scheme. Moreover, many public auditing schemes authorize the third party auditor (TPA) to check the integrity of remote data and the TPA is not fully trusted. Thus, we take the data privacy into account. The proposed scheme not only can overcome the above deficiencies but also able to preserve the data privacy against the TPA. Our theoretical analyses prove that our mechanism is correct and secure, and our mechanism is able to audit the integrity of cloud data efficiently.

Distributed Denial of Service (DDoS) attacks are among the most harmful cyberattack types in the Internet. The main goal of a DDoS defense mechanism is to reduce the attack's effect as close as possible to their sources to prevent malicious traffic in the Internet. In this work, we examine the DDoS attacks as a rate management and congestion control problem and propose a collaborative fair rate throttling mechanism to combat DDoS attacks. Additionally, we propose anomaly detection mechanisms to detect attacks at the victim site, early attack detection mechanisms by intermediate Autonomous Systems (ASes), and feedback mechanisms between ASes to achieve distributed defense against DDoS attacks. To reduce additional vulnerabilities for the feedback mechanism, we use a secure, private, and authenticated communication channel between AS monitors to control the process. Our mathematical model presents proactive resource management, where the victim site sends rate adjustment requests to upstream routers. We conducted several experiments using a real-world dataset to demonstrate the efficiency of our approach under DDoS attacks. Our results show that the proposed method can significantly reduce the impact of DDoS attacks with minimal overhead to routers. Moreover, the proposed anomaly detection techniques can help ASes to detect possible attacks and early attack detection by intermediate ASes.

Cyber resiliency in Cloud computing is one of the most important capability of an enterprise network that provides continues ability to withstand and quick recovery from the adversary conditions. This capability can be measured through cybersecurity risk assessment techniques. However, cybersecurity risk management studies in cloud computing resiliency approaches are deficient. This paper proposes resilient cloud cybersecurity risk assessment tailored specifically to Dropbox with two methods: technical-based solution motivated by a cybersecurity risk assessment of cloud services, and a target personnel-based solution guided by cybersecurity-related survey among employees to identify their knowledge that qualifies them withstand to any cyberattack. The proposed work attempts to identify cloud vulnerabilities, assess threats and detect high risk components, to finally propose appropriate safeguards such as failure predicting and removing, redundancy or load balancing techniques for quick recovery and return to pre-attack state if failure happens.

Mobile Ad Hoc Network (MANET) is one of the types of Ad-hoc Network which is comprised of wireless in a network. The main problem in this research is the vulnerability of the protocol routing Dymo against jellyfish attack, so it needs detection from a jellyfish attack. This research implements the DELPHI method to detect jellyfish attacks on a DYMO protocol which has better performance because the Delay Per-Hop Indicator (DELPHI) gathers the amount of hop and information delay from the disjoint path and calculates the delays per-hop as an indicator of a jellyfish attack. The evaluation results indicate an increase in the end-to-end delay average, start from 112.59s in 10 nodes increased to 143.732s in 30 nodes but reduced to 84,2142s in 50 nodes. But when the DYMO routing did not experience any jellyfish attacks both the delivery ratio and throughput are decreased. The delivery ratio, where decreased from 10.09% to 8.19% in 10 nodes, decreased from 20.35% to 16.85%, and decreased from 93.5644% to 82.825% in 50 nodes. As for the throughput, for 10 nodes decreased from 76.7677kbps to 68.689kbps, for 30 nodes decreased from 100kbps to 83.5821kbps and for 50 nodes decreased from 18.94kbps to 15.94kbps.

The digitalization process did not circumvent either railway domain. With new technology and new functionality, such as digital interlocking system, automated train operation, object recognition, GPS positioning, traditional railway domain got a vulnerability that can be exploited. Another issue is usage of CotS (Commercial-of-the-Shelf) hardware and software and openness of traditionally closed system. Most of published similar paper are focused on cyber security and security & safety model for securing of assessment in this kind of domain, but this paper will deal with this upcoming railway technology and digital investigation process in such kind of environment. Digital investigation process will be presented, but not only in ICS and SCADA system, but also in specific, railway environment. Framework for investigation process and for maintaining chain of custody in railway domain will be proposed.

The existing methods of constructing a trusted computing environment do not fully meet the requirements. Intel SGX provides a new hardware foundation for the construction of trusted computing environment. However, existing SGX still faces problems such as side channel attacks. To overcome it, this paper present F-SGX which is the future SGX for trusting computing. In our opinion, F-SGX hold stronger isolation than current SGX, and reduce the dependence of enclave on host operating system. Furthermore, F-SGX hold a private key for the attestation. We believe that F-SGX can further provide better support for trusting computing environments while there is a good balance between isolation and dependencies.

Renewable energy resource plays an important role due to increasing energy claim. Power generation by PV technology is one of the fastest growing renewable energy sources due to its clean, economical and sustainable property. Grid integrated PV systems plays an important role in power generation sector. As the energy demand is increasing day by day, the power transfer capability of transmission line is increasing which leads various problems like stability, increase in fault current, congestion etc. To overcome the problem, we can use either FACTS device or battery storage or construct additional lines which is cost effective. This paper deals with grid connected PV system, which functions as PV-STATCOM. Voltage and damping control are used to elevate the power transfer capacity and to achieve regulated voltage within the limits at the point of common coupling (PCC). The studies are performed on SMIB and the simulation is carried out in MATLAB/SIMULINK environment.

With the reform of the power market(PM), various power applications based on computer networks have also developed. As a network application system supporting the operation of the PM, the technical support system(TSS) of the PM has become increasingly important for its network information security(NIS). The purpose of this article is to study the security protection of computer network information in power systems. This paper proposes an identity authentication algorithm based on digital signatures to verify the legitimacy of system user identities; on the basis of PMI, according to the characteristics of PM access control, a role-based access control model with time and space constraints is proposed, and a role-based access control model is designed. The access control algorithm based on the attribute certificate is used to manage the user's authority. Finally, according to the characteristics of the electricity market data, the data security transmission algorithm is designed and the feasibility is verified. This paper presents the supporting platform for the security test and evaluation of the network information system, and designs the subsystem and its architecture of the security situation assessment (TSSA) and prediction, and then designs the key technologies in this process in detail. This paper implements the subsystem of security situation assessment and prediction, and uses this subsystem to combine with other subsystems in the support platform to perform experiments, and finally adopts multiple manifestations, and the trend of the system's security status the graph is presented to users intuitively. Experimental studies have shown that the residual risks in the power system after implementing risk measures in virtual mode can reduce the risk value of the power system to a fairly low level by implementing only three reinforcement schemes.

Some of the recent reports show that Power Grid is a target of attack and gradually the need for understanding the security of Grid network is getting a prime focus. The Department of Homeland Security has imposed focus on Cyber Threats on Power Grid in their "Cyber Security Strategy,2018" [1] . DHS has focused on innovations to manage risk attacks on Power System based national resources. Power Grid is a cyber physical system which consists of power flow and data transmission. The important part of a microgrid is the two-way power flow which makes the system complex on monitoring and control. In this paper, we have tried to study different types of attacks which change the data propagation of Synchrophasor, network communication interruption behavior and find the data propagation scenario due to attack. The focus of the paper is to develop a platform for Synchrophasor based data network attack study which is a part of Microgrid design. Different types of intrusion models were studied to observe change in Synchrophasor data pattern which will help for further prediction to improve Microgrid resiliency for different types of cyber-attack.

Poultry farming has contributed immensely to global food security and the economy. Its produces are favourites and hugely subscribed, due to the uniqueness of their nutrients to all categories of people and the alternatives they provide to other high-cholesterol proteins. The increase in the world's population will continuously stretch for an increase in demands for poultry products. A smart way to ensure continuous production and increased yields in various farms is to adopt automated and remote management of poultries. This paper modelled and developed a collaborative system using the synergistic wireless sensor network technology and the internet of things. The system integrated resourcefully selected wireless sensors, mobile phone, other autonomous devices and the internet to remotely monitor and control environmental parameters and activities within the farm. Parameters such as temperature, humidity, water level, food valve level, ammonia gas, illumination are sensed, benchmarked against selected thresholds, and communicated wirelessly to the sink node and the internet cloud. The required control actions can also be initiated remotely by the administrator through messages or command signal. Also, the various parameters and actions can be read or documented in real-time over the web. The system was tested and evaluated to give an average of about 93.7% accuracy in parameters detection and 2s delay in real-time response. Therefore, a modelled system has been developed to provide robust and more intuitive solutions in poultry farming.

This work examines volatile memory modules as ephemeral key storage for security applications in the context of low temperatures. In particular, we note that such memories exhibit a rising level of data remanence as the temperature decreases, especially for temperatures below 280 Kelvin. Therefore, these memories cannot be used to protect the superconducting modules found in high-speed Magnetic Levitation (MagLev) trains, as such modules most often require extremely low temperatures in order to provide superconducting applications. Thus, a novel secure storage solution is required in this case, especially within the oncoming framework concept of the internet of railway things, which is partially based on the increasing utilisation of commercial off-the-shelf components and potential economies of scale, in order to achieve cost efficiency and, thus, widespread adoption. Nevertheless, we do note that volatile memory modules can be utilised as intrinsic temperature sensors, especially at low temperatures, as the data remanence they exhibit at low temperatures is highly dependent on the ambient temperature, and can, therefore, be used to distinguish between different temperature levels.

This paper discusses securities and cryptocurrency trading using artificial intelligence (AI) in the sense that it focuses on performing Exploratory Data Analysis (EDA) on selected technical indicators before proceeding to modelling, and then to develop more practical models by introducing new reward loss function that maximizes the returns during training phase. The results of EDA reveal that the complex patterns within the data can be better captured by discriminative classification models and this was endorsed by performing back-testing on two securities using Artificial Neural Network (ANN) and Random Forests (RF) as discriminative models against their counterpart Na\"ıve Bayes as a generative model. To enhance the learning process, the new reward loss function is utilized to retrain the ANN with testing on AAPL, IBM, BRENT CRUDE and BTC using auto-trading strategy that serves as the intelligent unit, and the results indicate this loss superiorly outperforms the conventional cross-entropy used in predictive models. The overall results of this work suggest that there should be larger focus on EDA and more practical losses in the research of machine learning modelling for stock market prediction applications.

Security is a key component of the network. Software Defined Networking (SDN) is a refined form of traditional network management system. It is a new encouraging approach to design-build and manage networks. SDN decouples control plane (software-based router) and data plane (software-based switch), hence it is programmable. Consequently, it facilitates implementation of security based applications for the prevention of DOS attacks. Various solutions have been proposed by researches for handling of DOS attacks in SDN. However, these solutions are very limited in scope, complex, time consuming and change resistant. In this article, we have proposed a novel model driven framework i.e. MDAP (Model Based DOS Attacks Prevention) Framework. Particularly, a meta model is proposed. As tool support, a tree editor and a Sirius based graphical modeling tool with drag drop palette have been developed in Oboe designer community edition. The tool support allows modeling and visualization of simple and complex network topology scenarios. A Model to Text transformation engine has also been made part of framework that generates java code for the Floodlight SDN controller from the modeled scenario. The validity of proposed framework has been demonstrated via case study. The results prove that the proposed framework can effectively handle DOS attacks in SDN with simplicity as per the true essence of MDSE and can be reliably used for the automation of security based applications in order to deny DOS attacks in SDN.

Novel acoustic wave networks comprising resonators achieving prescribed coupling are proposed. The design methodology is based on classic network synthesis of doubly- and/or singly-terminated networks. The synthesis of LTE Band 25 contiguous duplexer prototype is performed and its electrical characteristics are presented.

When a fault occurs in power grid, the analytic model for power grid fault diagnosis could generate multiple solutions under one or more protective relays (PRs) and/or circuit breakers (CBs) malfunctioning, and/or one or more their alarm information failing. Hence, this paper, calling the electrical quantities, presents an optimal solution discrimination method, which determines the optimal solution by constructing the electrical criteria of suspicious faulty components. Furthermore, combining the established electrical criteria with the existing analytic model, a hierarchical fault diagnosis mode is proposed. It uses the analytic model for the first level diagnosis based on the switching quantities. Thereafter, aiming at multiple solutions, it applies the electrical criteria for the second level diagnosis to determine the diagnostic result. Finally, the examples of fault diagnosis demonstrate the feasibility and effectiveness of the developed method.

Digital signature is more appropriate for message security in Wireless Sensors Networks (WSNs), which is energy-limited, than costly encryption. However, it meets with difficulty of verification when a large amount of message-signature pairs swarm into the central node in WSNs. In this paper, a scalable group testing algorithm based on Latin square (SGTLS) is proposed, which focus on both batch verification of signatures and invalid signature identification. To address the problem of long time-delay during individual verification, we adapt aggregate signature for batch verification so as to judge whether there are any invalid signatures among the collection of signatures once. In particular, when batch verification fails, an invalid signature identification algorithm is presented based on scalable OR-checking matrix of Latin square, which can adjust the number of group testing by itself with the variation of invalid signatures. Comprehensive analyses show that SGTLS has more advantages, such as scalability, suitability for parallel computing and flexible design (Latin square is popular), than other algorithm.

Modern SoC applications include a variety of sensitive modules in which data must be protected against malicious access. Security vulnerabilities, when exercised during the SoC operation, lead to denial of service or disclosure of protected data. Hence, it is essential to undertake security validation before and after SoC fabrication and make provisions for continuous security assessment during operation. This paper presents a methodology for optimized post-deployment monitoring of SoC's security properties by migrating pre-fab design security assertions to post-fab run-time security monitors. We show that the method is scalable for large systems and complex properties by optimizing the hardware monitors and applying it to a large SoC design based on a OpenRISC-1200 SoC. About 40 security assertions were specified in System Verilog Assertions (SVA). Following formal verification, the assertions were synthesized into finite state machines and cross optimized. Following code generation in Verilog, commercial logic and layout synthesis tools were used to generate hardware monitors which were then integrated with the SoC design ready for fabrication.

Surface acoustic wave devices based on LiNbO3/interlayer/substrate layered structure have attracted great attention due to the high electromechanical coupling coefficient (K2) of LiNbO3 and the energy confinement effect of the layered structure. In this study, 30° YX-LiNbO3 (LN)/SiO2/Si multilayered structure, which can excited shear-horizontal surface acoustic wave (SH-SAW) with high K2, was proposed. The optimized orientation of LiNbO3 was verified by the effective permittivity method based on the stiffness matrix. The phase velocity, K2 value, and temperature coefficient of frequency (TCF) of the SH-SAW were calculated as a function of the LiNbO3 thickness at different thicknesses of the SiO2 in 30° YX-LiNbO3/SiO2/Si multilayer structure by finite element method (FEM). The results show that the optimized LiNbO3 thickness is 0.1 and the optimized SiO2 thickness is 0.2λ. The optimized Al electrode thickness and metallization ratio are 0.07 and 0.4, respectively. The K2 of the SH-SAW is 29.89%, the corresponding phase velocity is 3624.00 m/s and TCF is about 10 ppm/°C with the optimized IDT/30° YX-LiNbO3/SiO2/Si layered structure.

In Magnetic Josephson Junctions (MJJs) based on Superconductor-Insulator-Superconductor-Ferromagnet-Superconductor (SIS’FS), we provide evidence of an unconventional magnetic field behavior of the critical current characterized by an inverted magnetic hysteresis, i.e., an inverted shift of the whole magnetic field pattern when sweeping the external field. By thermoremanence measurements of S/F/S trilayers, we have ruled out that this uncommon behavior could be related to the F-stray fields. In principle, this finding could have a crucial role in the design and proper functioning of scalable cryogenic memories.