Biblio

Reliability block diagram (RBD) models are a commonly used reliability analysis method. For static RBD models, combinatorial solution techniques are easy and efficient. However, static RBDs are limited in their ability to express varying system state, dependent events, and non-series-parallel topologies. A recent extension to RBDs, called Dynamic Reliability Block Diagrams (DRBD), has eliminated those limitations. This tool paper details the RBD implementation in the M¨obius modeling framework and provides technical details for using RBDs independently or in composition with other M¨obius modeling formalisms. The paper explains how the graphical front-end provides a user-friendly interface for specifying RBD models. The back-end implementation that interfaces with the M¨obius AFI to define and generate executable models that the M¨obius tool uses to evaluate system metrics is also detailed.

Reliability block diagram (RBD) models are a commonly used reliability analysis method. For static RBD models, combinatorial solution techniques are easy and efficient. However, static RBDs are limited in their ability to express varying system state, dependent events, and non-series-parallel topologies. A recent extension to RBDs, called Dynamic Reliability Block Diagrams (DRBD), has eliminated those limitations. This tool paper details the RBD implementation in the M¨obius modeling framework and provides technical details for using RBDs independently or in composition with other M¨obius modeling formalisms. The paper explains how the graphical front-end provides a user-friendly interface for specifying RBD models. The back-end implementation that interfaces with the M¨obius AFI to define and generate executable models that the M¨obius tool uses to evaluate system metrics is also detailed.

This paper has conducted a trial in establishing a systematic instrument for evaluating the performance of the marine information systems. Analytic Network Process (ANP) was introduced for determining the relative importance of a set of interdependent criteria concerned by the stakeholders (shipper/consignee, customer broker, forwarder, and container yard). Three major information platforms (MTNet, TradeVan, and Nice Shipping) in Taiwan were evaluated according to the criteria derived from ANP. Results show that the performance of marine information system can be divided into three constructs, namely: Safety and Technology (3 items), Service (3 items), and Charge (3 items). The Safety and Technology is the most important construct of marine information system evaluation, whereas Charger is the least important construct. This study give insights to improve the performance of the existing marine information systems and serve as the useful reference for the future freight information platform.

In order to enhance the supply chain security at airports, the German federal ministry of education and research has initiated the project ESECLOG (enhanced security in the air cargo chain) which has the goal to improve the threat detection accuracy using one-sided access methods. In this paper, we present a new X-ray backscatter technology for non-intrusive imaging of suspicious objects (mainly low-Z explosives) in luggage's and parcels with only a single-sided access. A key element in this technology is the X-ray backscatter camera embedded with a special twisted-slit collimator. The developed technology has efficiently resolved the problem related to the imaging of complex interior of the object by fixing source and object positions and changing only the scanning direction of the X-ray backscatter camera. Experiments were carried out on luggages and parcels packed with mock-up dangerous materials including liquid and solid explosive simulants. In addition, the quality of the X-ray backscatter image was enhanced by employing high-resolution digital detector arrays. Experimental results are discussed and the efficiency of the present technique to detect suspicious objects in luggages and parcels is demonstrated. At the end, important applications of the proposed backscatter imaging technology to the aviation security are presented.

Massive MIMO and tight cooperation between transmission nodes are expected to become an integral part of a future 5G radio system. As part of an overall interference mitigation scheme substantial gains in coverage, spectral as well as energy efficiency have been reported. One of the main limitations for massive MIMO and coordinated multi-point (CoMP) systems is the aging of the channel state information at the transmitter (CSIT), which can be overcome partly by state of the art channel prediction techniques. For a clean slate 5G radio system, we propose to integrate channel prediction from the scratch in a flexible manner to benefit from future improvements in this area. As any prediction is unreliable by nature, further improvements over the state of the art are needed for a convincing solution. In this paper, we explain how the basic ingredients of 5G like base stations with massive MIMO antenna arrays, and multiple UE antennas can help to stretch today's limits with an approximately 10 dB lower normalized mean square error (NMSE) of the predicted channel. In combination with the novel introduced concept of artificially mutually coupled antennas, adding super-directivity gains to virtual beamforming, robust and accurate prediction over 10 ms with an NMSE of -20 dB up to 15 km/h at 2.6 GHz RF frequency could be achieved. This result has been achieved for measured channels without massive MIMO, but a comparison with ray-traced channels for the same scenario is provided as well.

Security analysts implement various security mechanisms to protect systems from attackers. Even though these mechanisms try to secure systems, a talented attacker may use these same techniques to launch a sophisticated attack. This paper discuss about such an attack called as user account Denial of Service (DoS) where an attacker uses user account lockout features of the application to lockout all user accounts causing an enterprise wide DoS. The attack has being simulated usingastealthy attack mechanism called as Advanced Persistent Threats (APT) using a XMPP based botnet. Through the simulation, researchers discuss about the patterns associated with the attack which can be used to detect the attack in real time and how the attack can be prevented from the perspective of developers, system engineers and security analysts.

We propose a clean-slate network architecture called Centralized Identifier Network (CIN) which jointly considers the ideas of both control plane/forwarding plane separation and identifier/locator separation. In such an architecture, a controller cluster is designed to perform routers' link states gathering and routing calculation/handing out. Meanwhile, a tailor-made router without routing calculation function is designed to forward packets and communicate with its controller. Furthermore, A router or a host owns a globally unique ID and a host should be registered to a router whose ID will be the host's location. Control plane/forwarding plane separation enables CIN easily re-splitting the network functions into finer optional building blocks for sufficient flexibility and adaptability. Identifier/locator separation helps CIN deal with serious scaling problems and offer support for host mobility. This article mainly shows the routing mechanism of CIN. Furthermore, numerical results are presented to demonstrate the performance of the proposed mechanism.

Nowadays, with the rapid development of Internet, the use of Web is increasing and the Web applications have become a substantial part of people's daily life (e.g. E-Government, E-Health and E-Learning), as they permit to seamlessly access and manage information. The main security concern for e-business is Web application security. Web applications have many vulnerabilities such as Injection, Broken Authentication and Session Management, and Cross-site scripting (XSS). Subsequently, web applications have become targets of hackers, and a lot of cyber attack began to emerge in order to block the services of these Web applications (Denial of Service Attach). Developers are not aware of these vulnerabilities and have no enough time to secure their applications. Therefore, there is a significant need to study and improve attack detection for web applications through determining the most significant factors for detection. To the best of our knowledge, there is not any research that summarizes the influent factors of detection web attacks. In this paper, the author studies state-of-the-art techniques and research related to web attack detection: the author analyses and compares different methods of web attack detections and summarizes the most important factors for Web attack detection independent of the type of vulnerabilities. At the end, the author gives recommendation to build a framework for web application protection.

The RFID technology has attracted considerable attention in recent years, and brings convenience to supply chain management. In this paper, we concentrate on designing path-checking protocols to check the valid paths in supply chains. By entering a valid path, the check reader can distinguish whether the tags have gone through the path or not. Based on modified schnorr signature scheme, we provide a path-checking method to achieve multi-signatures and final verification. In the end, we conduct security and privacy analysis to the scheme.

In this paper, we focus on energy management of distributed generators (DGs) and energy storage system (ESS) in microgrids (MG) considering uncertainties in renewable energy and load demand. The MG energy management problem is formulated as a two-stage stochastic programming model based on optimization principle. Then, the optimization model is decomposed into a mixed integer quadratic programming problem by using discrete stochastic scenarios to approximate the continuous random variables. A Scenarios generation approach based on time-homogeneous Markov chain model is proposed to generate simulated time-series of renewable energy generation and load demand. Finally, the proposed stochastic programming model is tested in a typical LV network and solved by Matlab optimization toolbox. The simulation results show that the proposed stochastic programming model has a better performance to obtain robust scheduling solutions and lower the operating cost compared to the deterministic optimization modeling methods.

There are more and more systems using mobile devices to perform sensing tasks, but these increase the risk of leakage of personal privacy and data. Data hiding is one of the important ways for information security. Even though many data hiding algorithms have worked on providing more hiding capacity or higher PSNR, there are few algorithms that can control PSNR effectively while ensuring hiding capacity. In this paper, with controllable PSNR based on LSBs substitution- PSNR-Controllable Data Hiding (PCDH), we first propose a novel encoding plan for data hiding. In PCDH, we use the remainder algorithm to calculate the hidden information, and hide the secret information in the last x LSBs of every pixel. Theoretical proof shows that this method can control the variation of stego image from cover image, and control PSNR by adjusting parameters in the remainder calculation. Then, we design the encoding and decoding algorithms with low computation complexity. Experimental results show that PCDH can control the PSNR in a given range while ensuring high hiding capacity. In addition, it can resist well some steganalysis. Compared to other algorithms, PCDH achieves better tradeoff among PSNR, hiding capacity, and computation complexity.

In the RFID technology, the privacy of low-cost tag is a hot issue in recent years. A new mutual authentication protocol is achieved with the time stamps, hash function and PRNG. This paper analyzes some common attack against RFID and the relevant solutions. We also make the security performance comparison with original security authentication protocol. This protocol can not only speed up the proof procedure but also save cost and it can prevent the RFID system from being attacked by replay, clone and DOS, etc..

Smart grid is a cyber-physical system that integrates power infrastructures with information technologies. To facilitate efficient information exchange, wireless networks have been proposed to be widely used in the smart grid. However, the jamming attack that constantly broadcasts radio interference is a primary security threat to prevent the deployment of wireless networks in the smart grid. Hence, spread spectrum systems, which provide jamming resilience via multiple frequency and code channels, must be adapted to the smart grid for secure wireless communications, while at the same time providing latency guarantee for control messages. An open question is how to minimize message delay for timely smart grid communication under any potential jamming attack. To address this issue, we provide a paradigm shift from the case-by-case methodology, which is widely used in existing works to investigate well-adopted attack models, to the worst-case methodology, which offers delay performance guarantee for smart grid applications under any attack. We first define a generic jamming process that characterizes a wide range of existing attack models. Then, we show that in all strategies under the generic process, the worst-case message delay is a U-shaped function of network traffic load. This indicates that, interestingly, increasing a fair amount of traffic can in fact improve the worst-case delay performance. As a result, we demonstrate a lightweight yet promising system, transmitting adaptive camouflage traffic (TACT), to combat jamming attacks. TACT minimizes the message delay by generating extra traffic called camouflage to balance the network load at the optimum. Experiments show that TACT can decrease the probability that a message is not delivered on time in order of magnitude.

In this paper, we focus on the principal-agent problems in continuous time when the participants have ambiguity on the output process in the framework of g-expectation. The first best (or, risk-sharing) type is studied. The necessary condition of the optimal contract is derived by means of the optimal control theory. Finally, we present some examples to clarify our results.

Exhaustive enumeration of a S-select-k problem for hypothesized substations outages can be practically infeasible due to exponential growth of combinations as both S and k numbers increase. This enumeration of worst-case substations scenarios from the large set, however, can be improved based on the initial selection sets with the root nodes and segments. In this paper, the previous work of the reverse pyramid model (RPM) is enhanced with prioritization of root nodes and defined segmentations of substation list based on mean-time-to-compromise (MTTC) value that is associated with each substation. Root nodes are selected based on the threshold values of the substation ranking on MTTC values and are segmented accordingly from the root node set. Each segmentation is then being enumerated with S-select-k module to identify worst-case scenarios. The lowest threshold value on the list, e.g., a substation with no assignment of MTTC or extremely low number, is completely eliminated. Simulation shows that this approach demonstrates similar outcome of the risk indices among all randomly generated MTTC of the IEEE 30-bus system.

Information and Communications Technologies (ICTs), especially the Internet, have become a key enabler for government organisations, businesses and individuals. With increasing growth in the adoption and use of ICT devices such as smart phones, personal computers and the Internet, Cybersecurity is one of the key concerns facing modern organisations in both developed and developing countries. This paper presents an overview of cybersecurity challenges in Bhutan, within the context that the nation is emerging as an ICT developing country. This study examines the cybersecurity incidents reported both in national media and government reports, identification and analysis of different types of cyber threats, understanding of the characteristics and motives behind cyber-attacks, and their frequency of occurrence since 1999. A discussion on an ongoing research study to investigate cybersecurity management and practices for Bhutan's government organisations is also highlighted.

A database is a vast collection of data which helps us to collect, retrieve, organize and manage the data in an efficient and effective manner. Databases are critical assets. They store client details, financial information, personal files, company secrets and other data necessary for business. Today people are depending more on the corporate data for decision making, management of customer service and supply chain management etc. Any loss, corrupted data or unavailability of data may seriously affect its performance. The database security should provide protected access to the contents of a database and should preserve the integrity, availability, consistency, and quality of the data This paper describes the architecture based on placing the Elliptical curve cryptography module inside database management software (DBMS), just above the database cache. Using this method only selected part of the database can be encrypted instead of the whole database. This architecture allows us to achieve very strong data security using ECC and increase performance using cache.

The Center for Strategic and International Studies estimates the annual cost from cyber crime to be more than \$400 billion. Most notable is the recent digital identity thefts that compromised millions of accounts. These attacks emphasize the security problems of using clonable static information. One possible solution is the use of a physical device known as a Physically Unclonable Function (PUF). PUFs can be used to create encryption keys, generate random numbers, or authenticate devices. While the concept shows promise, current PUF implementations are inherently problematic: inconsistent behavior, expensive, susceptible to modeling attacks, and permanent. Therefore, we propose a new solution by which an unclonable, dynamic digital identity is created between two communication endpoints such as mobile devices. This Physically Unclonable Digital ID (PUDID) is created by injecting a data scrambling PUF device at the data origin point that corresponds to a unique and matching descrambler/hardware authentication at the receiving end. This device is designed using macroscopic, intentional anomalies, making them inexpensive to produce. PUDID is resistant to cryptanalysis due to the separation of the challenge response pair and a series of hash functions. PUDID is also unique in that by combining the PUF device identity with a dynamic human identity, we can create true two-factor authentication. We also propose an alternative solution that eliminates the need for a PUF mechanism altogether by combining tamper resistant capabilities with a series of hash functions. This tamper resistant device, referred to as a Quasi-PUDID (Q-PUDID), modifies input data, using a black-box mechanism, in an unpredictable way. By mimicking PUF attributes, Q-PUDID is able to avoid traditional PUF challenges thereby providing high-performing physical identity assurance with or without a low performing PUF mechanism. Three different application scenarios with mobile devices for PUDID and Q-PUDI- have been analyzed to show their unique advantages over traditional PUFs and outline the potential for placement in a host of applications.

The speedy advancement in computer hardware has caused data encryption to no longer be a 100% safe solution for secure communications. To battle with adversaries, a countermeasure is to avoid message routing through certain insecure areas, e.g., Malicious countries and nodes. To this end, avoidance routing has been proposed over the past few years. However, the existing avoidance protocols are single-path-based, which means that there must be a safe path such that no adversary is in the proximity of the whole path. This condition is difficult to satisfy. As a result, routing opportunities based on the existing avoidance schemes are limited. To tackle this issue, we propose an avoidance routing framework, namely Multi-Path Avoidance Routing (MPAR). In our approach, a source node first encodes a message into k different pieces, and each piece is sent via k different paths. The destination can assemble the original message easily, while an adversary cannot recover the original message unless she obtains all the pieces. We prove that the coding scheme achieves perfect secrecy against eavesdropping under the condition that an adversary has incomplete information regarding the message. The simulation results validate that the proposed MPAR protocol achieves its design goals.

Remote data integrity checking is of crucial importance in cloud storage. It can make the clients verify whether their outsourced data is kept intact without downloading the whole data. In some application scenarios, the clients have to store their data on multicloud servers. At the same time, the integrity checking protocol must be efficient in order to save the verifier's cost. From the two points, we propose a novel remote data integrity checking model: ID-DPDP (identity-based distributed provable data possession) in multicloud storage. The formal system model and security model are given. Based on the bilinear pairings, a concrete ID-DPDP protocol is designed. The proposed ID-DPDP protocol is provably secure under the hardness assumption of the standard CDH (computational Diffie-Hellman) problem. In addition to the structural advantage of elimination of certificate management, our ID-DPDP protocol is also efficient and flexible. Based on the client's authorization, the proposed ID-DPDP protocol can realize private verification, delegated verification, and public verification.

A robust appearance model is usually required in visual tracking, which can handle pose variation, illumination variation, occlusion and many other interferences occurring in video. So far, a number of tracking algorithms make use of image samples in previous frames to update appearance models. There are many limitations of that approach: 1) At the beginning of tracking, there exists no sufficient amount of data for online update because these adaptive models are data-dependent and 2) in many challenging situations, robustly updating the appearance models is difficult, which often results in drift problems. In this paper, we proposed a tracking algorithm based on compressive sensing theory and particle filter framework. Features are extracted by random projection with data-independent basis. Particle filter is employed to make a more accurate estimation of the target location and make much of the updated classifier. The robustness and the effectiveness of our tracker have been demonstrated in several experiments.