Cryptology and network security

This book constitutes the refereed proceedings of the 11th International Conference on Cryptology and Network Security, CANS 2012, held in Darmstadt, Germany, in December 2012. The 22 revised full papers, presented were carefully reviewed and selected from 99 submissions. The papers are organized in topical sections on cryptanalysis; network security; cryptographic protocols; encryption; and s-box theory.

Nanostructured copper oxide semiconductors : a perspective on materials, synthesis methods and applications

The oxides of copper (CuxO) are fascinating materials due to their remarkable optical, electrical, thermal and magnetic properties. Nanostructuring of CuxO can further enhance the performance of this important functional material and provide it with unique properties that do not exist in its bulk form. Three distinctly different phases of CuxO, mainly CuO, Cu2O and Cu4O3, can be prepared by numerous synthesis techniques including, vapour deposition and liquid phase chemical methods. In this article, we present a review of nanostructured CuxO focusing on their material properties, methods of synthesis and an overview of various applications that have been associated with nanostructured CuxO.

Control and diagnostics of inductively coupled plasmas for chemical vapour deposition of nanocomposite carbon nitride-based films

Control and diagnostics of low-frequency (∼ 500 kHz) inductively coupled plasmas for chemical vapor deposition (CVD) of nano-composite carbon nitride-based films is reported. Relation between the discharge control parameters, plasma electron energy distribution/probability functions (EEDF/EEPF), and elemental composition in the deposited C-N based thin films is investigated. Langmuir probe technique is employed to monitor the plasma density and potential, effective electron temperature, and EEDFs/EEPFs in Ar + N2 + CH4 discharges. It is revealed that varying RF power and gas composition/pressure one can engineer the EEDFs/EEPFs to enhance the desired plasma-chemical gas-phase reactions thus controlling the film chemical structure. Auxiliary diagnostic tools for study of the RF power deposition, plasma composition, stability, and optical emission are discussed as well.

Understanding the value of social media in organisations : a taxonomic approach

While organizations strive to leverage the vast information generated daily from social media platforms and both decision makers and consultants are keen to identify and exploit this information’s value, there has been little research into social media in the business context. Social media are diverse, varying in scope and functionality, this diversity entailing a complex of attributes and characteristics, resulting in confusion for both researchers and organizations. Taxonomies are important precursors in emerging fields and are foundational for rigorous theory building. Though aspects of social media have been studied from various discipline perspectives, this work has been largely descriptive. Thus, while the need for a rigorous taxonomy of social media is strong, previous efforts to classify social media suffer limitations – e.g. lack of a systematic taxonomic method, overreliance on intuition, disregard for the users’ perspective, and inadequate consideration of purpose. Thus, this study was mainly initiated by the overarching question “How can social media in the business context be usefully classified?” In order to address this gap, the current paper proposes a systematic method for developing a taxonomy appropriate to study social media in organizations context, combining Nickerson et al,’s (2012) IS taxonomy building guidelines and a Repertory grid (RepGrid) approach.

Theorizing in design science research : an abstraction layers framework

For Design Science Research (DSR) to gain wide credence as a research paradigm in Information Systems (IS), it must contribute to theory. “Theory cannot be improved until we improve the theorizing process, and we cannot improve the theorizing process until we describe it more explicitly, operate it more self-consciously, and decouple it from validation more deliberately” (Weick 1989, p. 516). With the aim of improved design science theorizing, we propose a DSR abstraction-layers framework that integrates, interlates, and harmonizes key methodological notions, primary of which are: 1) the Design Science (DS), Design Research (DR), and Routine Design (RD) distinction (Winter 2008); 2) Multi Grounding in IS Design Theory (ISDT) (Goldkuhl & Lind 2010); 3) the Idealized Model for Theory Development (IM4TD) (Fischer & Gregor 2011); and 4) the DSR Theorizing Framework (Lee et al. 2011). Though theorizing, or the abstraction process, has been the subject of healthy discussion in DSR, important questions remain. With most attention to date having focused on theorizing for Design Research (DR), a key stimulus of the layered view was the realization that Design Science (DS) produces abstract knowledge at a higher level of generality. The resultant framework includes four abstraction layers: (i) Design Research (DR) 1st Abstract Layer, (ii) Design Science (DS) 2nd Abstract Layer, (iii) DSR Incubation 3rd Layer, and (iv) Routine Design 4th Layer. Differentiating and inter-relating these layers will aid DSR researchers to discover, position, and amplify their DSR contributions. Additionally, consideration of the four layers can trigger creative perspectives that suggest unplanned outputs. The first abstraction layer, including its alternative patterns of activity, is well recognized in the literature. The other layers, however, are less well recognized; and the integrated representation of layers is novel.

Antecedent factors of knowledge sharing in research supervision

Today’s economy is a knowledge-based economy in which knowledge is a crucial facilitator to individuals, as well as being an instigator of success. Due to the impact of globalisation, universities face new challenges and opportunities. Accordingly, they ought to be more innovative and have their own competitive advantages. One of the most important goals of universities is the promotion of students as professional knowledge workers. Therefore, knowledge sharing and transfer at the tertiary level between students and supervisors is vital in universities, as it decreases the budget and provides an affordable way to do research. Knowledge-sharing impact factors can be categorised in three groups, namely: organisational, individual, and technical factors. Individual barriers to knowledge sharing include: the lack of time and trust and the lack of communication skills and social networks. IT systems such as elearning, blogs and portals can increase the knowledge-sharing capability. However, it must be stated that IT systems are only tools and not solutions. Individuals are still responsible for sharing information and knowledge. This paper proposes a new research model to examine the effect of individual factors, organisational factors (learning strategy, trust culture, supervisory support) and technological factors on knowledge sharing in the research supervision process.

Security and Privacy in Vehicular Ad-Hoc Networks : Survey and the Road Ahead

Vehicular Ad-hoc Networks (VANETs) can make roads safer, cleaner, and smarter. It can offer a wide range of services, which can be safety and non-safety related. Many safety-related VANETs applications are real-time and mission critical, which would require strict guarantee of security and reliability. Even non-safety related multimedia applications, which will play an important role in the future, will require security support. Lack of such security and privacy in VANETs is one of the key hindrances to the wide spread implementations of it. An insecure and unreliable VANET can be more dangerous than the system without VANET support. So it is essential to make sure that “life-critical safety” information is secure enough to rely on. Securing the VANETs along with appropriate protection of the privacy drivers or vehicle owners is a very challenging task. In this work we summarize the attacks, corresponding security requirements and challenges in VANETs. We also present the most popular generic security policies which are based on prevention as well detection methods. Many VANETs applications require system-wide security support rather than individual layer from the VANETs’ protocol stack. In this work we will review the existing works in the perspective of holistic approach of security. Finally, we will provide some possible future directions to achieve system-wide security as well as privacy-friendly security in VANETs.

Detection of sinkhole attack in wireless sensor networks

Generally wireless sensor networks rely of many-to-one communication approach for data gathering. This approach is extremely susceptible to sinkhole attack, where an intruder attracts surrounding nodes with unfaithful routing information, and subsequently presents selective forwarding or change the data that carry through it. A sinkhole attack causes an important threat to sensor networks and it should be considered that the sensor nodes are mostly spread out in open areas and of weak computation and battery power. In order to detect the intruder in a sinkhole attack this paper suggests an algorithm which firstly finds a group of suspected nodes by analyzing the consistency of data. Then, the intruder is recognized efficiently in the group by checking the network flow information. The proposed algorithm's performance has been evaluated by using numerical analysis and simulations. Therefore, accuracy and efficiency of algorithm would be verified.

Security in wireless sensor networks : issues and challenges

Wireless Sensor Networks (WSNs) are employed in numerous applications in different areas including military, ecology, and health; for example, to control of important information like the personnel position in a building, as a result, WSNs need security. However, several restrictions such as low capability of computation, small memory, limited resources of energy, and the unreliable channels employ communication in using WSNs can cause difficulty in use of security and protection in WSNs. It is very essential to save WSNs from malevolent attacks in unfriendly situations. Such networks require security plan due to various limitations of resources and the prominent characteristics of a wireless sensor network which is a considerable challenge. This article is an extensive review about problems of WSNs security, which examined recently by researchers and a better understanding of future directions for WSN security.

Survey : video forensic tools

Due to extension of using CCTVs and the other video security systems in all areas, these sorts of devices have been introduced as the most important digital evidences to search and seizure crimes. Video forensics tools are developed as a part of digital forensics tools to analyze digital evidences and clear vague points of them for presenting in the courts Existing video forensics tools have been facilitated the investigation process by providing different features based on various video editing techniques. In this paper, some of the most popular video forensics tools are discussed and the strengths and shortages of them are compared and consequently, an alternative framework which includes the strengths of existing popular tools is introduced.

Human errors in computer related abuses

The term “Human error” can simply be defined as an error which made by a human. In fact, Human error is an explanation of malfunctions, unintended consequents from operating a system. There are many factors that cause a person to have an error due to the unwanted error of human. The aim of this paper is to investigate the relationship of human error as one of the factors to computer related abuses. The paper beings by computer-relating to human errors and followed by mechanism mitigate these errors through social and technical perspectives. We present the 25 techniques of computer crime prevention, as a heuristic device that assists. A last section discussing the ways of improving the adoption of security, and conclusion.

Modelling total duration of traffic incidents including incident detection and recovery time

Traffic incidents are key contributors to non-recurrent congestion, potentially generating significant delay. Factors that influence the duration of incidents are important to understand so that effective mitigation strategies can be implemented. To identify and quantify the effects of influential factors, a methodology for studying total incident duration based on historical data from an ‘integrated database’ is proposed. Incident duration models are developed using a selected freeway segment in the Southeast Queensland, Australia network. The models include incident detection and recovery time as components of incident duration. A hazard-based duration modelling approach is applied to model incident duration as a function of a variety of factors that influence traffic incident duration. Parametric accelerated failure time survival models are developed to capture heterogeneity as a function of explanatory variables, with both fixed and random parameters specifications. The analysis reveals that factors affecting incident duration include incident characteristics (severity, type, injury, medical requirements, etc.), infrastructure characteristics (roadway shoulder availability), time of day, and traffic characteristics. The results indicate that event type durations are uniquely different, thus requiring different responses to effectively clear them. Furthermore, the results highlight the presence of unobserved incident duration heterogeneity as captured by the random parameter models, suggesting that additional factors need to be considered in future modelling efforts.

In-hospital mortality rates after a cemented femoral component for displaced neck of femur fractures

Aim This prospective cohort study investigated whether the use of preoperative anticoagulants is an independent risk factor for the outcomes of surgical treatment of patients with a neck of femur fracture. Methods Data was obtained from a prospectively collected database. All patients admitted for a neck of femur fracture between Nov 2010 and Oct 2011 were included. This resulted in three hundred twenty-eight patients with 330 neck of femur fractures. Four groups were defined; patients preoperatively (i) on aspirin (n = 105); (ii) on clopidogrel (n = 28); (iii) on warfarin (n = 30), and; (iv) without any anticoagulation history (n = 167, the control group). The non-warfarin group included the aspirin group, clopidogrel group and the control group. Primary outcome was the in-hospital mortality. Secondary outcomes were the postoperative complications, return to theatre and length of stay. Results Thirteen in-hospital deaths were identified, 4 deaths in the aspirin group, 1 death in the clopidogrel group, 2 deaths in the warfarin group and 6 deaths in the control group. No significant difference in the mortality rates was found between the different groups. Also in the secondary outcomes, no significant difference was found between the four groups. A trend to a higher wound complication rate for the warfarin group was detected. Conclusion The use of clopidrogel or aspirin pre operatively is not an influence on short term patient outcome for patients with a neck of femur fracture. Surgical procedures should not be delayed to reverse their influence.

A normal-distribution based reputation model

Rating systems are used by many websites, which allow customers to rate available items according to their own experience. Subsequently, reputation models are used to aggregate available ratings in order to generate reputation scores for items. A problem with current reputation models is that they provide solutions to enhance accuracy of sparse datasets not thinking of their models performance over dense datasets. In this paper, we propose a novel reputation model to generate more accurate reputation scores for items using any dataset; whether it is dense or sparse. Our proposed model is described as a weighted average method, where the weights are generated using the normal distribution. Experiments show promising results for the proposed model over state-of-the-art ones on sparse and dense datasets.

A rating aggregation method for generating product reputations

Many websites offer the opportunity for customers to rate items and then use customers' ratings to generate items reputation, which can be used later by other users for decision making purposes. The aggregated value of the ratings per item represents the reputation of this item. The accuracy of the reputation scores is important as it is used to rank items. Most of the aggregation methods didn't consider the frequency of distinct ratings and they didn't test how accurate their reputation scores over different datasets with different sparsity. In this work we propose a new aggregation method which can be described as a weighted average, where weights are generated using the normal distribution. The evaluation result shows that the proposed method outperforms state-of-the-art methods over different sparsity datasets.