Biblio

Edge and Fog computing paradigms are used to process big data generated by the increasing number of IoT devices. These paradigms have enabled cities to become smarter in various aspects via real-time data-driven applications. While these have addressed some flaws of cloud computing some challenges remain particularly in terms of privacy and security. We create a testbed based on a distributed processing platform called the Information flow of Things (IFoT) middleware. We briefly describe a decentralized traffic speed query and routing service implemented on this framework testbed. We configure the testbed to test countermeasure systems that aim to address the security challenges faced by prior paradigms. Using this testbed, we investigate a novel decentralized anomaly detection approach for time-sensitive distributed smart transportation systems.

Modern vehicles in Intelligent Transportation Systems (ITS) can communicate with each other as well as roadside infrastructure units (RSUs) in order to increase transportation efficiency and road safety. For example, there are techniques to alert drivers in advance about traffic incidents and to help them avoid congestion. Threats to these systems, on the other hand, can limit the benefits of these technologies. Securing ITS itself is an important concern in ITS design and implementation. In this paper, we provide a security model of ITS which extends the classic layered network security model with transportation security and information security, and gives a reference for designing ITS architectures. Based on this security model, we also present a classification of ITS threats for defense. Finally a proof-of-concept example with malicious nodes in an ITS system is also given to demonstrate the impact of attacks. We analyzed the threat of malicious nodes and their effects to commuters, like increasing toll fees, travel distances, and travel times etc. Experimental results from simulations based on Veins shows the threats will bring about 43.40% more total toll fees, 39.45% longer travel distances, and 63.10% more travel times.

The condition of road surface has a significant role in land transportation. Due to poor road conditions, the logistics and supply chain industry face a drastic loss in their business. Unmaintained roads can cause damage to goods and accidents. The existing routing techniques do not consider factors like shock, temperature and tilt of goods etc. but these factors have to be considered for the logistics and supply chain industry. This paper proposes a recommender system which target management of goods in logistics. A 3 axis accelerometer is used to measure the road surface conditions. The pothole location is obtained using Global Positioning System (GPS). Using these details a hybrid recommender system is built. Hybrid recommender system combines multiple recommendation techniques to develop an effective recommender system. Here content-based and collaborative-based techniques is combined to build a hybrid recommender system. One of the popular Multiple Criteria Decision Making (MCDM) method, The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is used for content based filtering and normalised Euclidean distance and KNN algorithm is used for collaborative filtering. The best route recommended by the system will be displayed to the user using a map application.

Delivery service via ridesharing is a promising service to share travel costs and improve vehicle occupancy. Existing ridesharing systems require participating vehicles to periodically report individual private information (e.g., identity and location) to a central controller, which is a potential central point of failure, resulting in possible data leakage or tampering in case of controller break down or under attack. In this paper, we propose a Blockchain secured ridesharing delivery system, where the immutability and distributed architecture of the Blockchain can effectively prevent data tampering. However, such tamper-resistance property comes at the cost of a long confirmation delay caused by the consensus process. A Hash-oriented Practical Byzantine Fault Tolerance (PBFT) based consensus algorithm is proposed to improve the Blockchain efficiency and reduce the transaction confirmation delay from 10 minutes to 15 seconds. The Hash-oriented PBFT effectively avoids the double-spending attack and Sybil attack. Security analysis and simulation results demonstrate that the proposed Blockchain secured ridesharing delivery system offers strong security guarantees and satisfies the quality of delivery service in terms of confirmation delay and transaction throughput.

In order to effectively assess the security risks in multimodal transport networks, a security risk assessment method based on WBS-RBS and Pythagorean Fuzzy Weighted Average (PFWA) operator is proposed. The risk matrix 0-1 assignment of WBS-RBS is replaced by the Pythagorean Fuzzy Number (PFLN) scored by experts. The security risk ranking values of multimodal transport network are calculated from two processes of whole-stage and phased, respectively, and the security risk assessment results are obtained. Finally, an example of railway-highway-waterway intermodal transportation process of automobile parts is given to verify the validity of the method, the results show that the railway transportation is more stable than the waterway transportation, and the highway transportation has the greatest security risk, and for different security risk factors, personnel risk has the greatest impact. The risk of goods will change with the change of the attributes of goods, and the security risk of storage facilities is the smallest.

While the general idea of Intelligent Transportation System (ITS) is to employ suitable, sophisticated information and communications technologies, however, such tool also encompass many system complexities. Fittingly, this paper aims to highlight the most contemporary system complications of ITS and in doing so, will also underline the safety, security and risk management concerns. More importantly, effectively treating such issues will ultimately improve the reliability and efficiency of transportation systems. Whereas such issues are among the most significant subjects for any intelligent system, for ITS in particular they the most dominant. For such intelligent systems, the safety, security and risk management issues must not only be decidedly prioritized, but also methodically integrated. As a part of such ITS integration, this paper will delicately examine the Emergency Management System (EMS) development and application. Accurate EMS is not only a mandatory feature of intelligent systems, but it is a fundamental component of ITS which will vigilantly respond to safety, security and risk management apprehensions. To further substantiate such scheme, the Sydney Metro's EMS will be also conferred. It was determined that, the Sydney Metro's EMS although highly advanced, it was also vigilantly aligned with specific designated safety, security and risk management strategies.

In the process of mobile intelligent terminal for file transfer, ensure the safety of data transmission is significant. It is necessary to prevent the file from being eavesdropped and tampered during transmission. The method of using double encryption on covert channel is proposed in this paper based on the analysis of encryption algorithms and covert channel, which uses asymmetric encryption algorithm to encrypt the key of symmetric encryption, to form hidden information, and to carry out covert transmission through covert channels to enhance the security of mobile terminal data transmission. By simulating the above scenarios in intelligent mobile terminal, the confidentiality and concealment of important information are realized in the transmission process.

Maritime transportation plays a critical role for the U.S. and global economies, and has evolved into a complex system that involves a plethora of supply chain stakeholders spread around the globe. The inherent complexity brings huge security challenges including cargo loss and high burdens in cargo inspection against illicit activities and potential terrorist attacks. The emerging blockchain technology provides a promising tool to build a unified maritime cargo tracking system critical for cargo security. However, most existing efforts focus on transportation data itself, while ignoring how to bind the physical cargo movements and information managed by the system consistently. This can severely undermine the effectiveness of securing cargo transportation. To fulfill this gap, we propose a binding scheme leveraging a novel digital identity management mechanism. The digital identity management mechanism maps the best practice in the physical world to the cyber world and can be seamlessly integrated with a blockchain-based cargo management system.

As the Industrial Internet of Things (IIot) becomes more prevalent in critical application domains, ensuring security and resilience in the face of cyber-attacks is becoming an issue of paramount importance. Cyber-attacks against critical infrastructures, for example, against smart water-distribution and transportation systems, pose serious threats to public health and safety. Owing to the severity of these threats, a variety of security techniques are available. However, no single technique can address the whole spectrum of cyber-attacks that may be launched by a determined and resourceful attacker. In light of this, we consider a multi-pronged approach for designing secure and resilient IIoT systems, which integrates redundancy, diversity, and hardening techniques. We introduce a framework for quantifying cyber-security risks and optimizing IIoT design by determining security investments in redundancy, diversity, and hardening. To demonstrate the applicability of our framework, we present a case study in water-distribution systems. Our numerical evaluation shows that integrating redundancy, diversity, and hardening can lead to reduced security risk at the same cost.

The indoor air quality in industrial workplace buildings, e.g. air temperature, humidity and levels of carbon dioxide (CO2), play a critical role in the perceived levels of workers' comfort and in reported medical health. CO2 can act as an oxygen displacer, and in confined spaces humans can have, for example, reactions of dizziness, increased heart rate and blood pressure, headaches, and in more serious cases loss of consciousness. Specialized organizations can be brought in to monitor the work environment for limited periods. However, new low cost wireless sensor network (WSN) technologies offer potential for more continuous and autonomous assessment of industrial workplace air quality. Central to effective decision making is the data analytics approach and visualization of what is potentially, big data (BD) in monitoring the air quality in industrial workplaces. This paper presents a case study that monitors air quality that is collected with WSN technologies. We discuss the potential BD problems. The case trials are from two workshops that are part of a large on-shore logistics base a regional shipping industry in Norway. This small case study demonstrates a monitoring and visualization approach for facilitating BD in decision making for health and safety in the shipping industry. We also identify other potential applications of WSN technologies and visualization of BD in the workplace environments; for example, for monitoring of other substances for worker safety in high risk industries and for quality of goods in supply chain management.

The Cyber Transport Systems (CTSs) have made significant advancement along with the development of the information technology and transportation industries worldwide. The rapid proliferation of cyber transportation technology provides rich information and infinite possibilities for our society to understand and use the complex inherent mechanism, which governs the novel intelligence world. In addition, applying information technology to cyber transportation applications open a range of new application scenarios, such as vehicular safety, energy efficiency, reduced pollution, and intelligent maintenance services. However, while enjoying the services and convenience provided by CTS, users, vehicles, even the systems might lose privacy during information transmitting and processing. This paper summarizes the state-of-art research findings on information privacy issues in a broad range. We firstly introduce the typical types of information and the basic mechanisms of information communication in CTS. Secondly, considering the information privacy issues of CTS, we present the literature on information privacy issues and privacy protection approaches in CTS. Thirdly, we discuss the emerging challenges and the opportunities for the information technology community in CTS.

In the 21st century, integrated transport, service and mobility concepts for real-life situations enabled by automation system and smarter connectivity. These services and ideas can be blessed from cloud computing, and big data management techniques for the transport system. These methods could also include automation, security, and integration with other modes. Integrated transport system can offer new means of communication among vehicles. This paper presents how hybrid could computing influence to make urban transportation smarter besides considering issues like security and privacy. However, a simple structured framework based on a hybrid cloud computing system might prevent common existing issues.

The network intrusion detection problem domain is described with mathematical knowledge in this paper, and a novel IDS detection model based on immune mechanism is designed. We study the key modules of IDS system, detector tolerance module and the algorithms of IDS detection intensively. Then, the continuous bit matching algorithm for computing affinity is improved by further analysis. At the same time, we adopt controllable variation and random variation, as well as dynamic demotion to improve the dynamic clonal selection algorithm. Finally the experimental simulations verify that the novel artificial immune algorithm has better detection rate and lower noise factor.

National assets such as transportation networks, large manufacturing, business and health facilities, power generation, and distribution networks are critical infrastructures. The cyber threats to these infrastructures have increasingly become more sophisticated, extensive and numerous. Cyber security conventional measures have proved useful in the past but increasing sophistication of attacks dictates the need for newer measures. The autonomic computing paradigm mimics the autonomic nervous system and is promising to meet the latest challenges in the cyber threat landscape. This paper provides a brief review of autonomic computing applications for SCADA systems and proposes architecture for cyber security.

It is estimated that 50% of the global population lives in urban areas occupying just 0.4% of the Earth's surface. Understanding urban activity constitutes monitoring population density and its changes over time, in urban environments. Currently, there are limited mechanisms to non-intrusively monitor population density in real-time. The pervasive use of cellular phones in urban areas is one such mechanism that provides a unique opportunity to study population density by monitoring the mobility patterns in near real-time. Cellular carriers such as AT&T harvest such data through their cell towers; however, this data is proprietary and the carriers restrict access, due to privacy concerns. In this work, we propose a system that passively senses the population density and infers mobility patterns in an urban area by monitoring power spectral density in cellular frequency bands using periodic beacons from each cellphone without knowing who and where they are located. A wireless sensor network platform is being developed to perform spectral monitoring along with environmental measurements. Algorithms are developed to generate real-time fine-resolution population estimates.

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.

The globalization of trade is due to the transportation possibilities and the standardization (containerization of freight). The dependency of the economy to the sea and to the merchant navy has increase this last decade. This process forms a worldwide maritime network between the different locations of production and consumption. This network, representing between 80 % and 90% of world traffic is a major economic concern, including freight distribution, raw materials or energy. Rodrigue demonstrates[1] the economic dependency of energy is increasing in the industrialized countries (North America, Europe, East Asia). The inter-regional trade of oil was 31 million bbl/day in 2002 and is expected to grow up to 57 bbl/day in 2030 [2]. Most of the international traffic use a maritime way, where may occur disruptions. For example, the Suez crisis (1956-1957) caused a closure of the canal, reducing the throughput capacity of transportation. This disruption cost a 2 millions of barrels lost per day. This article focuses on vulnerability of the energy supply, and proposes a methodology to formalize and assess the vulnerability of the network by taking into account the spatial structure of maritime territories.

The safety, security, and resilience of international postal, shipping, and transportation critical infrastructure are vital to the global supply chain that enables worldwide commerce and communications. But security on an international scale continues to fail in the face of new threats, such as the discovery by Panamanian authorities of suspected components of a surface-to-air missile system aboard a North Korean-flagged ship in July 2013 [1].This reality calls for new and innovative approaches to critical infrastructure security. Owners and operators of critical postal, shipping, and transportation operations need new methods to identify, assess, and mitigate security risks and gaps in the most effective manner possible.

Critical Infrastructure represents the basic facilities, services and installations necessary for functioning of a community, such as water, power lines, transportation, or communication systems. Any act or practice that causes a real-time Critical Infrastructure System to impair its normal function and performance will have debilitating impact on security and economy, with direct implication on the society. SCADA (Supervisory Control and Data Acquisition) system is a control system which is widely used in Critical Infrastructure System to monitor and control industrial processes autonomously. As SCADA architecture relies on computers, networks, applications and programmable controllers, it is more vulnerable to security threats/attacks. Traditional SCADA communication protocols such as IEC 60870, DNP3, IEC 61850, or Modbus did not provide any security services. Newer standards such as IEC 62351 and AGA-12 offer security features to handle the attacks on SCADA system. However there are performance issues with the cryptographic solutions of these specifications when applied to SCADA systems. This research is aimed at improving the performance of SCADA security standards by employing NTRU, a faster and light-weight NTRU public key algorithm for providing end-to-end security.

Content distribution in the Internet places content providers in a dominant position, with delivery happening directly between two end-points, that is, from content providers to consumers. Information-Centrism has been proposed as a paradigm shift from the host-to-host Internet to a host-to-content one, or in other words from an end-to-end communication system to a native distribution network. This trend has attracted the attention of the research community, which has argued that content, instead of end-points, must be at the center stage of attention. Given this emergence of information-centric solutions, the relevant management needs in terms of performance have not been adequately addressed, yet they are absolutely essential for relevant network operations and crucial for the information-centric approaches to succeed. Performance management and traffic engineering approaches are also required to control routing, to configure the logic for replacement policies in caches and to control decisions where to cache, for instance. Therefore, there is an urgent need to manage information-centric resources and in fact to constitute their missing management and control plane which is essential for their success as clean-slate technologies. In this thesis we aim to provide solutions to crucial problems that remain, such as the management of information-centric approaches which has not yet been addressed, focusing on the key aspect of route and cache management.