Biblio

In this paper, we leverage previous work in the Identity Ecosystem, a Bayesian network mathematical representation of a person's identity, to create a framework to evaluate identity protection systems. Information dynamic is considered and a protection game is formed given that the owner and the attacker both gain some level of control over the status of other PII within the dynamic Identity Ecosystem. We present a policy iteration algorithm to solve the optimal policy for the game and discuss its convergence. Finally, an evaluation and comparison of identity protection strategies is provided given that an optimal policy is used against different protection policies. This study is aimed to understand the evolutionary process of identity theft and provide a framework for evaluating different identity protection strategies and future privacy protection system.

Collaborative filtering (CF) is a successful and hence most widely used technique for recommender systems. However, it is vulnerable to shilling attack due to its open nature, which results in generating biased or false recommendations for users. In literature, segment attack (push attack) has been widely studied and investigated while rare studies have been performed on nuke attack, to the best of our knowledge. Further, the robustness of binary collaborative filtering and hybrid approach has not been investigated against segment-focused attack. In this paper, from the perspective of robustness, binary collaborative filtering, hybrid approach, stand-alone rating user-based, and stand-alone rating item- based recommendation have been evaluated against segment attack on a large dataset (100K ratings) which is found to be more successful as it attacks target set of items. With an aim to find an approach which reflects a higher accuracy in recommending items and is less vulnerable to segment-based attack, the possibility of any relationship between accuracy and vulnerability of six CF approaches were studied. Such an approach needs to be re-examined by the researchers marking the future of recommender system (RS). Experimental results show negligible positive correlation between accuracy and vulnerability of techniques. Publicly available dataset namely MovieLens was used for conducting experiments. Robustness and accuracy of CF techniques were calculated using prediction shift and F-measure, respectively.

Wireless networks offer great flexibility and ease of deployment for the rapid implementation of smart grids. However, these data network technologies are prone to security issues. Especially, the risk of eavesdropping attacks increases due to the inherent characteristics of the wireless medium. In this context, physical layer security can augment secrecy through appropriate coding and signal processing. In this paper we consider the use of faster-than-Nyquist signaling to introduce artificial noise in the wireless network segment of the smart grid; with the aim of reinforce the information security at the physical layer. The results show that the proposed scheme can significantly improves the secrecy rate of the channel. Guaranteeing, in coexistence with other security mechanisms and despite the presence of potential eavesdroppers, a reliable and secure flow of information for smart grids.

Users regularly enter sensitive data, such as passwords, credit card numbers, or tax information, into the browser window. While modern browsers provide powerful client-side privacy measures to protect this data, none of these defenses prevent a browser compromised by malware from stealing it. In this work, we present Fidelius, a new architecture that uses trusted hardware enclaves integrated into the browser to enable protection of user secrets during web browsing sessions, even if the entire underlying browser and OS are fully controlled by a malicious attacker. Fidelius solves many challenges involved in providing protection for browsers in a fully malicious environment, offering support for integrity and privacy for form data, JavaScript execution, XMLHttpRequests, and protected web storage, while minimizing the TCB. Moreover, interactions between the enclave and the browser, the keyboard, and the display all require new protocols, each with their own security considerations. Finally, Fidelius takes into account UI considerations to ensure a consistent and simple interface for both developers and users. As part of this project, we develop the first open source system that provides a trusted path from input and output peripherals to a hardware enclave with no reliance on additional hypervisor security assumptions. These components may be of independent interest and useful to future projects. We implement and evaluate Fidelius to measure its performance overhead, finding that Fidelius imposes acceptable overhead on page load and user interaction for secured pages and has no impact on pages and page components that do not use its enhanced security features.

With the recent proliferation of Internet of Things (IoT) and embedded devices, there is a growing need to develop a security framework to protect such devices. RISC-V is a promising open source architecture that targets low-power embedded devices and SoCs. However, there is a dearth of practical and low-overhead security solutions in the RISC-V architecture. Programs compiled using RISC-V toolchains are still vulnerable to code injection and code reuse attacks such as buffer overflow and return-oriented programming (ROP). In this paper, we propose FIXER, a hardware implemented security extension to RISC-V that provides a defense mechanism against such attacks. FIXER enforces fine-grained control-flow integrity (CFI) of running programs on backward edges (returns) and forward edges (calls) without requiring any architectural modifications to the RISC-V processor core. We implement FIXER on RocketChip, a RISC-V SoC platform, by leveraging the integrated Rocket Custom Coprocessor (RoCC) to detect and prevent attacks. Compared to existing software based solutions, FIXER reduces energy overhead by 60% at minimal execution time (1.5%) and area (2.9%) overheads.

In network communication domain, one of the most widely used protocol for encrypting data and securing communications is the IPSec protocol. The design of this protocol is based on two main phases which are: exchanging keys phase and transferring data phase. In this paper we focus on enhancing the exchanging keys phase which is included in the security association (SA), using a chaotic cryptosystem. Initially IPSec is based on the Internet Key Exchange (IKE) protocol for establishing the SA. Actually IKE protocol is in charge for negotiating the connection and for authenticating both nodes. However; using IKE gives rise to a major problem related to security attack such as the Man in the Middle Attack. In this paper, we propose a chaotic cryptosystem solution to generate SA file for the connected nodes of the network. By solving a 4-Dimension chaotic system, a SA file that includes 128-bit keys will be established. The proposed solution is implemented and tested using FPGA boards.

The six papers in this special section focuses on services and software computing. Services computing provides a foundation to build software systems and applications over the Internet as well as emerging hybrid networked platforms motivated by it. Due to the open, dynamic, and evolving nature of the Internet, new features were born with these Internet-scale and service-based software systems. Such systems should be situation- aware, adaptable, and able to evolve to effectively deal with rapid changes of user requirements and runtime contexts. These emerging software systems enable and require novel methods in conducting software requirement, design, deployment, operation, and maintenance beyond existing services computing technologies. New programming and lifecycle paradigms accommodating such Internet- scale and service-based software systems, referred to as Internetware, are inevitable. The goal of this special section is to present the innovative solutions and challenging technical issues, so as to explore various potential pathways towards Internet-scale and service-based software systems.

We present a new method, called hyperplane folding, that increases the margin in Support Vector Machines (SVMs). Based on the location of the support vectors, the method splits the dataset into two parts, rotates one part of the dataset and then merges the two parts again. This procedure increases the margin as long as the margin is smaller than half of the shortest distance between any pair of data points from the two different classes. We provide an algorithm for the general case with n-dimensional data points. A small experiment with three folding iterations on 3-dimensional data points with non-linear relations shows that the margin does indeed increase and that the accuracy improves with a larger margin. The method can use any standard SVM implementation plus some basic manipulation of the data points, i.e., splitting, rotating and merging. Hyperplane folding also increases the interpretability of the data.

This research concerns the detection of unauthorised access within hospital networks through the real-time analysis of audit logs. Privacy is a primary concern amongst patients due to the rising adoption of Electronic Patient Record (EPR) systems. There is growing evidence to suggest that patients may withhold information from healthcare providers due to lack of Trust in the security of EPRs. Yet, patient record data must be available to healthcare providers at the point of care. Ensuring privacy and confidentiality of that data is challenging. Roles within healthcare organisations are dynamic and relying on access control is not sufficient. Through proactive monitoring of audit logs, unauthorised accesses can be detected and presented to an analyst for review. Advanced data analytics and visualisation techniques can be used to aid the analysis of big data within EPR audit logs to identify and highlight pertinent data points. Employing a human-in-the-loop model ensures that suspicious activity is appropriately investigated and the data analytics is continuously improving. This paper presents a system that employs a Human-in-the-Loop Machine Learning (HILML) algorithm, in addition to a density-based local outlier detection model. The system is able to detect 145 anomalous behaviours in an unlabelled dataset of 1,007,727 audit logs. This equates to 0.014% of the EPR accesses being labelled as anomalous in a specialist Liverpool (UK) hospital.

Companies develop their software in versions and iterations. Ensuring the security of each additional version using code review is costly and time consuming. This paper investigates automated tracing of the impacts of code changes on the security of a given software. To this end, we use call graphs to model the software code, and security assurance cases to model the security requirements of the software. Then we relate assurance case elements to code through the entry point methods of the software, creating a map of monitored security functions. This mapping allows to evaluate the security requirements that are affected by code changes. The approach is implemented in a set of tools and evaluated using three open-source ERP/E-commerce software applications. The limited evaluation showed that the approach is effective in identifying the impacts of code changes on the security of the software. The approach promises to considerably reduce the security assessment time of the subsequent releases and iterations of software, keeping the initial security state throughout the software lifetime.

Experience in designing general-purpose systems that enforce security goals shows that achieving universality, security, and performance remains a very difficult challenge. As a result, two directions emerged in designing, one of which focused on universality and performance with limited security mechanisms, and another - on robust security with reasonable performance for limited sets of applications. In the first case, popular but unsecure systems were created, and various efforts were subsequently made to upgrade the protected infrastructure for such systems. In the work, the latter approach is considered. It is obvious that the inclusion of built-in security mechanisms leads to a decrease in system performance. The paper considers a reference monitor and the assessment of its impact on system performance. For this purpose, the functional structure of reference monitor is built and the analytical model of impact evaluation on system performance is proposed.

Based on the Indonesian of Statistics the level of society people in 2019 is grow up. Based on data, the bank conducted a community to simple transaction payment in the market. Bank just used a debit card or credit card for the transaction, but the banks need more investment for infrastructure and very expensive. Based on that cause the bank needs another solution for low-cost infrastructure. Obtained from solutions that, the bank implementation QR Code Biometric authentication Payment Online is one solution that fulfills. This application used for payment in online merchant. The transaction permits in this study lie in the biometric encryption, or decryption transaction permission and QR Code Scan to improve communication security and transaction data. The test results of implementation Biometric Cloud Authentication Platform show that AES 256 agents can be implemented for face biometric encryption and decryption. Code Scan QR to carry out transaction permits with Face verification transaction permits gets the accuracy rate of 95% for 10 sample people and transaction process gets time speed of 53.21 seconds per transaction with a transaction sample of 100 times.

Heterogeneous Networks (Het Nets) are introduced to fulfill the increasing demands of wireless communications. To be manageable, it is expected that these networks are self-organized and in particular, self-healing to detect and relief faults autonomously. In the Cooperative Cell Outage Detection (COD), the Macro-Base Station (MBS) and a group of Femto-Base Stations (FBSs) in a specific range are cooperatively communicating to find out if each FBS is working properly or not. In this paper, we discuss the impacts of the cooperation range on the detection delay and accuracy and then conclude that there is an optimal amount for cooperation range which maximizes detection accuracy. We then derive the optimal cooperative range that improves the detection accuracy by using network parameters such as FBS's transmission power, noise power, shadowing fading factor, and path-loss exponent and investigate the impacts of these parameters on the optimal cooperative range. The simulation results show the optimal cooperative range that we proposed maximizes the detection accuracy.

Health Information Technology Systems (HITS) are increasingly used to improve the quality of patient care while reducing costs. These systems have been developed in response to the changing models of care to an ongoing relationship between patient and care team, supported by the use of technology due to the increased instance of chronic disease. However, the use of HITS may increase the risk to patient safety and security. While standards can be used to address and manage these risks, significant communication problems exist between experts working in different departments. These departments operate in silos often leading to communication breakdowns. For example, risk management stakeholders who are not clinicians may struggle to understand, define and manage risks associated with these systems when talking to medical professionals as they do not understand medical terminology or the associated care processes. In order to overcome this communication problem, we propose the use of the “Three Amigos” approach together with the use of the SIMPLE tool that has been developed to assist patients in understanding medical terms. This paper examines how the “Three Amigos” approach and the SIMPLE tool can be used to improve estimation of severity of risk by non-clinical risk management stakeholders and provides a practical example of their use in a ten step risk management process.

Peer-to-Peer networks are designed to rely on the resources of their own users. Therefore, resource management plays an important role in P2P protocols. Early P2P networks did not use proper mechanisms to manage fairness. However, after seeing difficulties and rise of freeloaders in networks like Gnutella, the importance of providing fairness for users have become apparent. In this paper, we propose an incentive-based security model which leads to a network infrastructure that lightens the work of Seeders and makes Leechers to contribute more. This method is able to prevent betrayals in Leecher-to-Leecher transactions and helps Seeders to be treated more fairly. This is what other incentive methods such as Bittorrent are incapable of doing. Additionally, by getting help from cryptography and combining it with our method, it is also possible to achieve secure channels, immune to spying, next to a fair network. This is the first protocol designed for P2P networks which has separated Leechers and Seeders without the need to a central server. The simulation results clearly show how our proposed approach can overcome free-riding issue. In addition, our findings revealed that our approach is able to provide an appropriate level of fairness for the users and can decrease the download time.

We present two novel sound and complete netlist transformations, which substantially improve verification scalability while enabling very efficient trace reconstruction. First, we present a 2QBF variant of input reparameterization, capable of eliminating inputs without introducing new logic and without complete range computation. While weaker in reduction potential, it yields up to 4 orders of magnitude speedup to trace reconstruction when used as a fast-and-lossy preprocess to traditional reparameterization. Second, we present a novel scalable approach to leverage sequential unateness to merge selective inputs, in cases greatly reducing netlist size and verification complexity. Extensive benchmarking demonstrates the utility of these techniques. Connectivity verification particularly benefits from these reductions, up to 99.8%.

The digitalization of the electric power industry and the development of territories isolated from the unified energy system are priorities in the development of the energy sector. Thanks to innovative solutions and digital technologies, it becomes possible to make more effective managing and monitoring. Such solution is IoT platform with intelligent control system implemented by software.

Though some software development teams are highly effective at delivering security, others either do not care or do not have access to security experts to teach them how. Unfortunately, these latter teams are still responsible for the security of the systems they build: systems that are ever more important to ever more people. We propose that a series of lightweight in-terventions, six hours of facilitated workshops delivered over three months, can improve a team's motivation to consider security and awareness of assurance techniques, changing its security culture even when no security experts are involved. The interventions were developed after an Appreciative Inquiry and Grounded Theory survey of security professionals to find out what approaches work best. They were then validated in fieldwork with a Participatory Action Research study that de-livered the workshops to three development organizations. This approach has the potential to be applied by many development teams, improving the security of software worldwide.

Today, intrusion detection and prevention systems (IDS / IPS) are a necessary element of protection against network attacks. The main goal of such systems is to identify an unauthorized access to the network and take appropriate countermeasures: alarming security officers about intrusion, reconfiguration of firewall to block further acts of the attacker, protection against cyberattacks and malware. For traditional computer networks there are a large number of sufficiently effective approaches for protection against malicious activity, however, for the rapidly developing dynamic adhoc networks (Internet of Things - IoT, MANET, WSN, etc.) the task of creating a universal protection means is quite acute. In this paper, we review various methods for detecting polymorphic intrusion activity (polymorphic viral code and sequences of operations), present a comparative analysis, and implement the suggested technology for detecting polymorphic chains of operations using bioinformatics for IoT. The proposed approach has been tested with different lengths of operation sequences and different k-measures, as a result of which the optimal parameters of the proposed method have been determined.

Emergence of Information and Communication Technology (ICT) has facilitated its users to access electronic services through open channel like Internet. This approach of digital communication has its specific security lapses, which should be addressed properly to ensure Privacy, Integrity, Non-repudiation and Authentication (PINA) of information. During message communication, intruders may mount infringement attempts to compromise the communication. The situation becomes critical, if an user is identified by multiple identification numbers, as in that case, intruder have a wide window open to use any of its identification number to fulfill its ill intentions. To resolve this issue, author have proposed a single window based cloud service delivery model, where a smart card serves as a single interface to access multifaceted electronic services like banking, healthcare, employment, etc. To detect and prevent unauthorized access, in this paper, authors have focused on the intrusion detection system of the cloud service model during cloud banking transaction.

Security and consistency of smart grids is one of the main issues in the design and maintenance of highly controlled and monitored new power grids. Bad data injection attack could lead to disasters such as power system outage, or huge economical losses. In many attack scenarios, the attacker can come up with new attack strategies that couldn't be detected by the traditional bad data detection methods. Adaptive Partitioning State Estimation (APSE) method [3] has been proposed recently to combat such attacks. In this work, we evaluate and compare with a traditional method. The main idea of APSE is to increase the sensitivity of the chi-square test by partitioning the large grids into small ones and apply the test on each partition individually and repeat this procedure until the faulty node is located. Our simulation findings using MATPOWER program show that the method is not consistent where it is sensitive the systems size and the location of faulty nodes as well.

In the era of Industry 4.0 (IR 4.0), information leakage has become a critical issue for information security. The basic approach to addressing information leakage threats is to implement an information security policy (ISP) that defines the standards, boundaries, and responsibilities of users of information and technology of an organization. ISPs are one of the most commonly used methods for controlling internal user security behaviours, which include, but not limited to, computer usage ethics; organizational system usage policies; Internet and email usage policies; and the use of social media. Human error is the main security threat to information security, resulting from negligence, ignorance, and failure to adhere to organizational information security policies. Information security incidents are a problem related to human behaviour because technology is designed and operated by humans, presenting the opportunities and spaces for human error. In addition to the factor of human error as the main source of information leakage, this study aims to systematically analyse the fundamental issues of information security policy compliance. An analysis of these papers identifies and categories critical factor that effect an employee's attitude toward compliance with ISP. The human, process, technology element and information governance should be thought as a significant scope for more efficiency of information security policy compliance and in any further extensive studies to improve on information security policy compliance. Therefore, to ensure these are properly understood, further study is needed to identity the information governance that needs to be included in organizations and current best practices for developing an information security policy compliance within organizations.

The task of the insider threat detection is one of the most sophisticated problems of the information security. The analysis of the logs of the access control system may reveal on how employees move and interact providing thus better understanding on how personnel observe security policies and established business processes. The paper presents an approach to the detection of the location-centric employees' interaction patterns. The authors propose the formal definition of the interaction patterns and present the visualization-driven technique to the extraction of the patterns from the data when any prior information about existing interaction routine and procedures is not available. The proposed approach is demonstrated on the data set provided within VAST MiniChallenge-2 2016 contest.

Very sensitive magnetic instruments on the JUICE spacecraft require an extremely low magnetic field emission of the various subsystems. The JUICE solar array includes a photovoltaic assembly and various mechanisms with a magnetic signature. The design of the photovoltaic assembly has been optimised not only with respect to magnetic moment, but also with respect to the emitted magnetic field, by applying the so-called back-wiring technique, alternating string polarity etc. The remanent magnetic field of the mechanisms (hinges, eddy-current damper, hold-down & release mechanism) was tested including a process for demagnetisation. In addition, the temperature coefficient for the magnetic moment was measured, down to the operational temperature of -130°C. The eddy-current damper was also subjected to a field-induced magnetisation test. All the contributors were included in a model to calculate the magnetic field at the instrument location.

Datasheets of different commercially available integrated sensors for vector measurements of magnetic fields provide typical specifications, such as measurement range, sampling rate, resolution, and noise. Other characteristics of interest, such as linearity, cross-sensitivity, remanent magnetization, and drifts over temperature, are mostly missing. This letter presents testing results of those characteristics of integrated three-dimensional (3-D) sensors working with different sensor principles and technologies in a reproducible measuring process. The sensors are exposed to temperatures from -20 °C to 80 °C and are cycled in hysteresis loops in fields up to 2.5 mT. For applying high-accuracy magnetic fields, a calibrated 3-D Helmholtz coil setup is used. Commercially available integrated 3-D magnetic field sensors are put in operation on a printed circuit board using nonmagnetic passive components. All sensors are configured for best measurement accuracy according to their data-sheets. The results show that sensors based on anisotropic magnetoresistance have high accuracy and low offsets yet also a high degree of nonlinearity. Hall-based sensors show good linearity but also high cross-sensitivity. A magnetic remanence appears for Hall-based sensors with integrated magnetic concentrators as well as for sensors using anisotropic magnetoresistance. Nearly all sensors show remaining drifts over temperature regarding offset and sensitivity up to several percentages.