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Graphical abstract Highlights • Cluster ions can only be formed from their nearest constituent atoms. • Compositional information is self-focused to areas where all the constituents are present. • Nano-patterned device made of alternated metal and dielectric lines is analyzed. • Information at the nanoscale can be obtained thanks to the Self-focusing SIMS concept. • Selective deposition of a blocking layer on the metal is assessed. • Selective deposition of a dielectric on the dielectric is assessed. Abstract Micro- and nano-electronics is increasingly relying on heterogeneous, confined and three-dimensional structures, to continue the downscaling required for the next technology generations. Area-selective atomic layer deposition (ALD) is one suited methodology to create nm-scale features through (1) the area-selective self-assembly of a blocking layer (i.e. a thiol deposited on copper) and (2) the ALD growth on the areas not covered with the blocking layer (i.e. a dielectric deposited on low-k). Assessing the efficiency and defectivity of selective deposition on such samples would require a lateral resolution much smaller than the feature size of interest. Hence the need for characterization techniques appropriate to the device's dimensions. Recently, thanks to the Self-Focusing Secondary Ions Mass Spectrometry (SF-SIMS) concept, the SIMS applicability to analyze the composition of narrow (<20 nm) trenches has been enabled through the selection of characteristic cluster ions exclusively confined to the areas of interest. In this paper, we show that the SF-SIMS concept can be extended to area-selective ALD processes. More specifically, the assessment of the blocking layer deposition on copper is studied using the characteristic copper-sulphur cluster ions while the potential reaction with the low-k material is checked by looking at silicon-sulphur cluster ions. In the same way, the ALD growth of aluminum oxide on the low-k material is assessed using silicon-aluminum clusters while the detection of copper-aluminum clusters is exploited to assess the efficiency of the blocking layer. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to develop and test a research model that looks at the direct impact of information technology (IT) capabilities on firm performance and the mediating effects of the information security management system (ISMS) on this relationship. Design/methodology/approach: The study uses a hypothetico-deductive approach based on quantitative data collected from 136 surveyed professionals in the field of IS, IT and the related security environment. Findings: The results confirm the direct impact of IT capabilities on firm performance and the mediating effects of ISMS on this relationship. Originality/value: The study draws on the resource-based view theory to develop a model that assesses the direct impact of IT capabilities on firm performance and the mediating effects of ISMS on this relationship in Cameroon, a developing country in Africa. [ABSTRACT FROM AUTHOR]

Highlights from the article: Digital supply chains are being used to inform new requirements for digital infrastructures and standards and the potential for connecting App and Device-aware consumers with their product-service supply chains ([2]). Yet, very few empirical studies have been conducted to assess the real business value of digitalisation at the firm and supply chain levels, and its impact on BPM. The findings confirm the direct impact of IT capabilities on firm performance and show that ISMS mediates the relationship between IT capabilities and firm performance.

Implementation of security objectives is conditioned by fast access to reliable and up-to-date information about processes occurring within the Safety Management Systems. The amount of information and the speed of changes taking place in the environment makes it necessary to introduce a system of information management and channels of their flow not only within the organization, but also in communication with third parties. Proper management of information resources increases the efficiency and effectiveness of SMS functioning. The article presents the possibility of a formalized description of the flow of external and internal information in a well-functioning Railway Operator Safety Management System. Analogous maps can be identified for infrastructure managers, defining key elements of its functioning.. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • Pb and Bi are absorbed in the steel only if the material is plastically deformed. • Pb adsorption at the surface of the oxide layer is more likely than Bi adsorption. • Oxygen can drive Pb atoms to the surface and then to the bulk. • No evidence of Pb or Bi in regards with the microstructure was found. • Clustering of lead and bismuth with molybdenum was found. Abstract The time of flight secondary ion mass spectroscopy (ToF-SIMS) technique was employed to investigate the interaction of liquid lead-bismuth eutectic (LBE) atoms with the surface and subsurface of a T91 steel taking into account the contribution of plastic deformation. It is shown that both Pb and Bi can penetrate the steel network only in plastically deformed material. No microstructural interface (lath boundaries, grain boundaries ...) was found to be preferential site for trapping Pb and Bi but clustering with molybdenum has been identified. Pb seems to be easier adsorbed than Bi because of its higher affinity with oxygen. [ABSTRACT FROM AUTHOR]

Abstract In cyber crimes, attackers are becoming more inventive with their exploits and use more sophisticated techniques to bypass the deployed security system. These attacks are targeted and are commonly referred as Advanced Persistent Threats (APTs). The currently available techniques to tackle these attacks are mostly reactive and signature based. Security Information and Event Management (SIEM), a proactive approach is the best solution. However, the major problem with SIEM is tackling huge amount of data in real time that makes it a time consuming and tedious task for security analyst. The use of threat intelligence caters to such issue by prioritizing the level of threat. In this paper, we assign risk score and confidence value to each feed generated at our product "T-Eye platform". On the basis of these values, we assign a severity score to each feed type. Severity score assigns a level to the threat means prioritize the threat. The results, we achieved for prioritizing the threat is more apparent and accurate. In addition, we optimize the rules of IBM-Q-Radar by using threat feeds generated at T-Eye platform. Furthermore, a huge amount of false positive alarms generated at IBM Q-Radar is reduced to a certain extent. Highlights • Proposed a platform for Threat intelligence along with a Threat Intelligence application integrated with IBM Qradar and classified the feeds on the basis of types of attack. • Calculated the risk score for each feed by taking into account severity, progression level, asset value and threat relevance. • Calculated the confidence value for each feed by using external sources, volume of traffic and aging of the traffic. • Optimized the rules of IBM Q-Radar using Threat intelligence feeds. • Reduced false positive alarms of IBM Qradar to an acceptable level. [ABSTRACT FROM AUTHOR]

Abstract The preferential sputtering and the mass conservation upon AES and SIMS depth profiling have been evaluated quantitatively based on the Mixing-Roughness-Information (MRI) model. The simulation results demonstrated that (a) the preferential sputtering plays an important role in the reconstruction of the true concentration-depth profile; (b) the mass conservation is a nature consequence in SIMS depth profiling but it is not fulfilled in AES depth profiling; (c) the layer thickness can be determined by applying the mass conservation law in AES depth profiling if the atoms preferentially sputtered out from the mixing zone are taken into account. Highlights • The influence of preferential sputtering on the reconstruction of concentration-depth profile is evaluated by the MRI model. • The mass conservation in AES and SIMS depth profiling is addressed. • The layer thickness can be determined by SIMS and AES depth profiling based on the mass conservation law. [ABSTRACT FROM AUTHOR]

Information security has become more important in health care institutions in recent years. Especially, if necessary precautions are not taken in line with the development of technology, it is expected that information leaks would increase. In the study in which in-depth interviews with qualitative research directives are used in order to determine the opinions, suggestions and evaluations of employees about hospital information security, 12 hospital employees working in different units are reached. The data obtained from the interviews are analysed and interpreted in ATLAS.ti qualitative data program. In this respect, the problems that arise in practice and the solution proposal are established in line with these opinions. As a result of the research, it is determined that participants emphasize the importance of information security widely and that information security is perceived together as "patient privacy". In turn, is it also seen that physical infrastructure is necessary for information security in terms of privacy, integrity and accessibility. It is one of the proposals of the research that managers and employees should cooperate for an effective information security management system. [ABSTRACT FROM AUTHOR]

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Objective: The main reason of this study was to generate knowledge and improve understanding amongst practitioners and academics. This paper examines the extent to which SMEs have implemented physical, policy as well as logical controls in place to curb security threats as a preventive control. Analysis: Data was gathered through surveys and to achieve more reliable responses, questionnaires were distributed and collected personally by hand. ISMS provide a systematic approach to manage sensitive data in terms of maintaining its confidentiality, integrity and authentication. Method: This study is based on both quantitative and qualitative tests method or measurement which determines IEC/ISO27001 practices amongst SMEs. ISO/IEC27000 family of standards provides clear guidelines to medium and large organizations on how to keep their information assets secure. Findings: A total of 100 surveys were sent administered by hand across six enterprises which were equally represented by four sectors i.e. Business Process Outsourcing (BPO), telecommunications, software and hardware vendors. Respondents were data handlers that had at least five years of working experience. All 100 responses were collected by hand, giving this study a response rate of 100%. Result: Results reveal that 98% of the respondents agreed that ISMS has a significant relationship with recommended industry best practices. Majority of firm ISMS initiatives are on voluntary basis. [ABSTRACT FROM AUTHOR]

This work combines large area time‐of‐flight secondary ion mass spectrometry imaging with multivariate analysis methods to characterise a cold atmospheric plasma treatment of the surface of an automotive grade polypropylene. Data preprocessing steps are also presented alongside their main challenges. The results enabled the investigation of the spatial distribution of the treatment for different stand‐off distances as well as the effects of plasma plume mixing with atmosphere. [ABSTRACT FROM AUTHOR]

Due to the growth of IoT (Internet of Things) devices in different industries and markets in recent years and considering the currently insufficient protection for these devices, a security solution safeguarding IoT architectures are highly desirable. An interesting perspective for the development of security solutions is the use of an event management approach, knowing that an event may become an incident when an information asset is affected under certain circumstances. The paper at hand proposes a security solution based on the management of security events within IoT scenarios in order to accurately identify suspicious activities. To this end, different vulnerabilities found in IoT devices are described, as well as unique features that make these devices an appealing target for attacks. Finally, three IoT attack scenarios are presented, describing exploited vulnerabilities, security events generated by the attack, and accurate responses that could be launched to help decreasing the impact of the attack on IoT devices. Our analysis demonstrates that the proposed approach is suitable for protecting the IoT ecosystem, giving an adequate protection level to the IoT devices. [ABSTRACT FROM AUTHOR]

Security information and event management (SIEM) systems receive a large number of alerts from different intrusion detection systems. They are expected, from these alerts, to make reliable and timely decisions regarding the types of ongoing attack scenarios and their priorities. However, the lack of an agreed-upon vocabulary for the representation of the domain knowledge makes it difficult for state-of-the-art SIEM systems to effectively manage these complex decisions. To overcome this problem, an ontology-based expert system approach can provide domain knowledge modeling as a foundation for disambiguation of meaning and automatic reasoning regarding ongoing attack scenarios. The proposed approach reconstructs attack scenarios by reasoning based on the evidences in the alert stream. The main idea of the proposed approach is to identify the causal relation between alerts using their similarity. This approach assumes that the similarity between two successive steps in an attack scenario is greater than that of two non-successive steps. Moreover, the similarity between the steps of the same attack scenario is greater than that between the steps of two different attack scenarios. The benefit of the proposed approach includes the fast and incremental reconstruction of known and unknown attack scenarios without expert intervention, which is an enormous step forward in developing expert and intelligent systems for cyber security. We evaluated the proposed technique by performing experiments on two known datasets: DARPA 2000 and MACCDC 2012. The results prove the advantages of the proposed approach with regard to completeness and soundness criteria. [ABSTRACT FROM AUTHOR]

Abstract Compared with ordinary information systems, power information systems are characterized by high complexity, strong real-time performance, high dynamics, and high-security requirements. The security-related data is varied. It is helpful to integrate the different types of data from multiple resources to support the further analysis such as abnormal detection or damage prediction. Considering the data complexity, this paper proposes a framework to automatically integrate security-related data in an electric system using ontology reasoning. In this paper, we try to determine the relationship between the ontology or between the local ontology and the global ontology through certain reasoning rules to help establish the data structure automatically. The experiment results demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Abstract Abnormal detection is an important task to ensure the stable running of the electric power system. In this paper, an abnormal detection framework for electric security data is proposed based on scenario modeling that supplies the descriptions of typical security issues. In this framework, the electric power system security-related data is first collected from different resources in real time. Then we create a scenario model based on the historical data for the typical security issues such as warning, system error or fatal error using the association rule mining algorithms. Then multiple scenario models are tagged with indicators that are observable from the sensors or monitors. Finally, the real-time data is analyzed to detect the defined indicators based on which the possible security scenarios are predicted and corresponding operation or protection will be activated automatically. The experiment results suggest that the proposed method can effectively identify and prevent the many of the common issues in the electric system. [ABSTRACT FROM AUTHOR]

Organizations deploy the Security Information and Event Management (SIEM) systems for centralized management of security alerts for securing their multimedia content. The SIEM system not only preserves events data, generated by devices and applications, in the form of logs but also performs real-time analysis of the event data. The SIEM works as the Security Operation Centre (SOC) in an organization, therefore, errors in the SIEM may compromise the security of the organization. In addition to focusing on the architecture, features, and the performance of the SIEM, it is imperative to carry out a formal analysis to verify that the system is impeccable. The ensuing research focuses mainly on the formal verification of the OSTORM a SIEM system. We have used High-Level Petri Nets (HLPN) and Z language to model and analyze the system. Moreover, Satisfiability Modulo Theories Library (SMT-Lib) and Z3 solver are used in this research to prove the correctness of the overall working of the OSTORM system. We demonstrate the correctness of the underlying system based on four security properties, namely: a) event data confidentiality, b) authentication, c) event data integrity, and d) alarm integrity. The results reveal that the OSTORM system functions correctly. [ABSTRACT FROM AUTHOR]

With the continuous advancements of technology, cyber-criminals accordingly develop sophisticated tactics to exploit vulnerabilities in individual systems, organization networks, and nation-states. Enterprises routinely collect huge amount of securityrelevant data such as log events of people, networks, and software applications for future forensic analysis. Existing traditional security analysis tools fail to work well with large scales of data and usually produces high false alarms especially when the enterprises moves to cloud architecture and collect more data. Moreover, the detection of recent and more sophisticated attacks, like advanced persistent threats (APTs), requires continuous monitoring and analysis of huge security related data, accurately and rapidly. Big Data analytics has been in active use in several fields such as financial transactions, healthcare and industrial applications among others. Recently, it has attracted the attention of information security audience due to its promised ability in correlating security related data and draw insights efficiently at unprecedented scale. In this paper, we analyze the traditional technology/systems and Security Information and Event Management (SIEM) tools and show their shortcomings in dealing with huge data scales and advanced sophisticated threats. We then explore the requirements for Big Data analytics to be successfully adopted in cyber threat intelligence and cyber-security landscape to deal with high data scales and sophisticated threats. Finally, we highlight the challenges resulted from such adoption, and suggest some recommendations to overcome adoption challenges in future research. [ABSTRACT FROM AUTHOR]

Organizations deploy security information and event management (SIEM) systems for centralized management of security events. The real-time security monitoring capability of the SIEM depends on the correlation process where events data are matched against the security rules. Most SIEM systems use general purpose languages to define security rules. Creating new rules in general purpose languages require excellent programming skills in the proprietary language and intimate knowledge of events. This paper introduces a high-level domain-specific language (HDSL) which simplifies rule creation for the SIEM system. We formally specify the HDSL with extended Backus-Naur form grammar in another tool for language recognition according to the model driven engineering approach. In our implementation framework, the rules defined in the HDSL are converted in the standard event processing language. For evaluation purpose, the converted security rules are tested on the service real-time data security analytics. The results indicate that the rules are converted accurately and generate alarms when specific attacks are detected. For checking correctness of the HDSL, formal verification is carried out using satisfiability modulo theory and Z3 solver. The results are evaluated under diverse attack scenarios, which reveal that HDSL is functioning correctly. The HDSL enhances the SIEM correlation capabilities by providing a tranquil approach for writing the correlation rules. [ABSTRACT FROM AUTHOR]

This research presents a proposal of malware classification and its update based on capacity and obfuscation. This article is an extension of [4]a, and describes the procedure for malware updating, that is, to take obsolete malware that is already detectable by antiviruses, update it through obfuscation techniques and thus making it undetectable again. As the updating of malware is generally performed manually, an automatic solution is presented together with a comparison from the standpoint of cost and processing time. The automated method proved to be more reliable, fast and less intensive in the use of resources, specially in terms of antivirus analysis and malware functionality checking times. [ABSTRACT FROM AUTHOR]

Security Information and Event Management (SIEM) is a combination of Security Information Management and Security Event Management. SIEM helps in the collection of events from heterogeneous devices and ordering into Common Event Format. The events collected are correlated and observed for changes in the system behaviour. Homogeneous Events such as DoS/Probe attacks can be detected by monitoring single event source. In this paper, TCP SYN flood attack is considered. RETE algorithm is applied on the network event attributes to formulate the rules and stored in database. An alert is triggered, when the rule for TCP SYN attack is matched. [ABSTRACT FROM AUTHOR]

Large tilt angle (LTA) implantation has been employed in Si manufacturing processes in many applications, such as lightly doped drain and halo implant. The depth profile of boron ions usually consists of only single peak at incident angle of 0° with respect to the perpendicular of the silicon surface. However, an abnormal dual-peak profile was observed at LTA (>40°) with incident energy of 160 keV. By using a Monte Carlo method to simulate the ion implant process, it was found that the projected range of boron ions agrees completely with the formation of the first peak position that is shallower in depth, while the cause for the second peak that corresponds with a depth much deeper in the Si substrate was unknown. During the simulation, it was also found that when the tilt angle was increased, the sputtering yields and Si displacements increased significantly, and this phenomenon indicates that during LTA implantation, Si damage may not be negligible anymore. The Si damage effect that was as due to either low Si density or transient Si displacement in the simulation could have led to partial incident boron ions penetrating much deeper into the Si substrate and thus, caused the emergence of the second peak. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

We study secure transmission considering the practical scenario in which only outdated knowledge of the legitimate receiver's channel and statistical knowledge of the eavesdropper's channel are available at the transmitter. Conditioned on the limited channel knowledge, we adopt an on–off secure transmission scheme and propose a versatile strategy to determine the codeword transmission rate. We first analyze the outage performance of the system and then provide the design of optimal wiretap code parameters maximizing the secrecy throughput. Compared with the existing solution in the literature, the proposed secure transmission design enlarges the achievable reliability–security region and increases the maximum secrecy throughput. [ABSTRACT FROM PUBLISHER]

In order to achieve a safe and systematic treatment of security protocols, organizations release a number of technical briefings describing how to detect and manage security incidents. A critical issue is that this document set may suffer from semantic deficiencies, mainly due to ambiguity or different granularity levels of description and analysis. An approach to face this problem is the use of semantic methodologies in order to provide better Knowledge Externalization from incident protocols management. In this article, we propose a method based on semantic techniques for both, analyzing and specifying (meta)security requirements on protocols used for solving security incidents. This would allow specialist getting better documentation on their intangible knowledge about them. [ABSTRACT FROM AUTHOR]

A primary feature of cloud computing is the provision of a variety of transparent services with efficient resource utilization. However, there are concerns with cloud computing in terms of the user's data privacy and security, especially in evidence collection for forensics analysis, because the tangible resources and hardware are out of reach for users who own the data. This paper presents a framework using security information and event management (SIEM), to address the issue of efficient evidence collection for crime investigation, such as that for cloud forensics, with respect to the cloud service provider. Indeed, evidence could be shared with cloud users when required. SIEM can be considered as a major player in terms of evidence collection in a virtualized environment. The proposed mechanism using SIEM focuses on passive attacks and provides a solution from the cloud administrator or service provider's point of view. The proposed framework can help in performing detailed cloud forensics in terms of efficient evidence building for crime investigations. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The utility of energy sequencing for extracting an accurate matrix level interface profile using ultra-low energy SIMS (uleSIMS) is reported. Normally incident O over an energy range of 0.25-2.5 keV were used to probe the interface between SiGe/Si, which was also studied using high angle annular dark field scanning transmission electron microscopy (HAADF-STEM). All the SIMS profiles were linearized by taking the well understood matrix effects on ion yield and erosion rate into account. A method based on simultaneous fitting of the SIMS profiles measured at different energies is presented, which allows the intrinsic sample profile to be determined to sub-nanometer precision. Excellent agreement was found between the directly imaged HAADF-STEM interface and that derived from SIMS. [ABSTRACT FROM AUTHOR]

This work precisely evaluates whether browser security warnings are as ineffective as proposed by popular sentiments and past writings. This research used different kinds of Android mobile browsers as well as desktop browsers to evaluate security warnings. Security experts and developers should give emphasis on making a user aware of security warnings and should not neglect aim of communicating this to users. Security experts and system architects should emphasis the goal of communicating security information to end users. In most of the browsers, security warnings are not emphasized, and browsers simply do not show warnings, or there are a number of ways to hide those warnings of malicious sites. This work precisely finds that how inconsistent browsers really are in prompting security warnings. In particular, majority of the modern mobile web browsers are vulnerable to these security threats. We find inconsistency in SSL warnings among web browsers. Based on this work, we make recommendations for warning designers and researchers. [ABSTRACT FROM AUTHOR]

The underlying principle of a SIEM system is that relevant data about an enterprise's security is produced in multiple locations and being able to look at all the data from a single point of view makes it easier to spot trends and see patterns that are out of the ordinary. Today's security threats are dynamic in nature and exploits are constantly evolving. Attackers grow more organized, precise and persistent and have access to various automated tools that can trigger very sophisticated attacks. As threatsand security events evolve, SIEM vendors and the information securitycommunity must work together to build relevant and actionable businessanalytics into their systems. By continuously improving recommendationsand the controls to support those recommendations, SIEM products canbecome true information security hubs that not only automate audits butalso provide proactive means to protect the organization. SIEMtechnologies for centralization and consolidation of an organization'ssecurity data will continue to be important investments for organizationswanting to accurately respond to threats and ultimately improve their riskand compliance postures. In the field of computer security, security information and event management (SIEM) software products and services combine security information management (SIM) and security event management (SEM). They provide real-time analysis of security alerts generated by network hardware and applications. [ABSTRACT FROM AUTHOR]

Understanding the interplay of climatic and biological events in deep time requires resolving the precise timing and pattern of paleotemperature changes and their temporal relationship with carbon cycle variations and biodiversity fluctuations. In situ oxygen isotope analyses of conodont apatite from South China enables us to reconstruct high-resolution seawater temperature records across the Permian–Triassic boundary (PTB) intervals in the upper slope (Meishan), lower slope (Shangsi), and carbonate platform (Daijiagou and Liangfengya) settings. Constrained by the latest high-precision geochronological dates and high-resolution conodont biozones, we can establish the temporal and spatial patterns of seawater temperature changes and assess their potential connections with the carbon cycle disruption and biodiversity decline. We find a rapid warming of ~ 10 °C during the latest Permian–earliest Triassic that postdated the onset of the negative shift in δ 13 C carb by ~ 81 kyr (thousand years), the abrupt decline in δ 13 C carb by ~ 32 kyr and the onset of mass extinction by ~ 23 kyr, which contradicts previous claims that the extreme temperature rise started immediately before or coincided with the onset of mass extinction. Our new evidence indicates that climate warming was most likely not a direct cause for the main pulse of the end-Permian mass extinction (EPME), but rather a later participant or a catalyst that increased the pace of the biodiversity decline. In addition, a prominent cooling is recorded in the earliest Changhsingian, with the main phase (a drop of ~ 8 °C in ~ 0.2 Ma) confined to the lower part of the Clarkina wangi zone and synchronous with the positive limb of the carbon isotope excursion (CIE) around the Wuchiapingian–Changhsingian boundary (WCB) in Meishan and Shangsi. Further long-term and high-resolution studies from other sections are needed to confirm the full contexts and underlying dynamics of the WCB “cooling event”. [ABSTRACT FROM AUTHOR]

Cooperative intrusion detection use several intrusion detection systems (IDS) and analyzers in order to build a reliable overview of the monitored system trough a central security information and event management system (SIEM). In such environment, the definition of a shared vocabulary describing the exchanged information between tools is prominent. Since these pieces of information are structured, we propose in this paper to use an ontological representation based on Description Logics (DLs) which is a powerful tool for knowledge representation. Moreover, DLs are able to ensure a decidable reasoning. An alert correlation prototype is presented using this ontology, and an illustrative attack scenario is carried out to show the usefulness of the proposed ontology. [ABSTRACT FROM AUTHOR]

Security Information and Event Management (SIEM) is a consolidated technology that relies on the correlation of massive amounts of security-relevant information in order to detect ongoing attacks and intrusions. This correlation process is usually fed with logs generated by network devices and equipment, thus proving to be ineffective against attacks that affect multiple domains (e.g. physical, logical) or different architectural levels (e.g. network, operating system, application) of a service infrastructure. To bridge the gap, we propose a flexible framework for event collection and correlation, namely the Generic Event Translator, which is able to process heterogeneous data and spot evidence of security issues by using complex event pattern detectors that correlate information from multiple architectural layers and domains of the monitored infrastructure. The framework has been integrated into the open-source SIEM OSSIM, and validated in two challenging case studies, namely a dam infrastructure control system and a mobile phone based payment service. [ABSTRACT FROM AUTHOR]

Isotopologue deficits of up to 200 ‰ below ideal mixing are observed in UO2+ species during SIMS gechronological analyses using the SHRIMP IIe instrument. These are identified by bombarding natural U-bearing minerals with an 18O2-primary beam. The large anomalies are associated with repeat analyses down a single SIMS sputtering crater (Compston et al., 1984), analysis of high-uranium, radiation damaged zircon, and analysis of baddeleyite. Analysis of zircon under routine conditions yield UO2+ isotopologue anomalies generally within a few percent of equilibrium. The conditions under which the isotopologue anomalies are observed are also conditions in which the UOx-based corrections, or calibration, for relative U vs. Pb ionization efficiencies fail. The existence of these isotopologue anomalies suggest that failure of the various UOx species to equilibrate with each other is the reason that none of them will successfully correct the U / Pb ratio. No simple isotopologue-based correction is apparent. However, isotopologue disequilibrium appears to be a more sensitive tool for detecting hi U calibration breakdowns than Raman spectroscopy, which showed sharper peaks for ~ 37 Ma high uranium 20 zircons than for reference zircons OG1 and Temora. U-Th-Sm/He ages were determined for aliquots of reference zircons OG1 (755 ± 71 Ma) and Temora (323 ± 43 Ma), suggesting that the broader Raman lines for the Temora reference zircons may be due to something other than accumulated radiation damage. Isotopologue abundances for UO+ and ThO+ and their energy spectra are consistent with most or all molecular species being 25 the product of atomic recombination when the primary beam impact energy is greater than 5.7 kV. This, in addition with the large UO2+ instrumentally generated isotopologue disequilibria, suggest any attempts to use SIMS to detect naturally occurring isotopologue deviations could be tricky. [ABSTRACT FROM AUTHOR]

A primary tool of nuclear safeguards authorities for detecting undeclared nuclear activities is environmental sample analysis containing uranium-bearing aerosol particles. SIMS (Secondary Ion Mass Spectrometry) has been established as a powerful technique for performing uranium isotope analysis on safeguards samples. Typically, a screening of the sample for locating the particles of interest is followed by micro-beam measurements of individual particles in order to obtain their precise isotopic composition. The uncertainty of these measurements, in particular for the minor isotopes 234U and 236U, is mainly limited by the counting statistics as the total amount of uranium available is very low, usually less than 1 pg. This uncertainty can be reduced when recording several isotopes simultaneously using a multi-collection system. This has been available commercially for many years and has been used for different applications in geosciences on Large Geometry-SIMS (LG-SIMS) instruments. This paper will describe and discuss how isotope measurements of low content uranium materials can be optimized using a multi-ion counting system consisting of five discrete dynode electron multiplier (EM) detectors. The results obtained for uranium isotope ratios are presented for different measurement protocols: static multi-collector, dynamic multi-collector and single collector measurements. Some of the fundamental properties of the detector system that affect the overall measurement uncertainty are discussed. Best practices are also suggested based on the current experience. [ABSTRACT FROM AUTHOR]

Li ion batteries and its accessories are now under increased focus of research due to enhanced energy storage and recycling requirements and the need for clean environments. In this context, observations on Li battery electrodes prepared using multi-wall carbon nanotubes (MWCNT) coated on stainless steel as observed by time of flight secondary ion mass spectrometry (TOF-SIMS) analysis and their relevance in understanding and improving the electrochemical properties of such battery systems are discussed. Porosity issues due to MWCNT, and accumulation of chemical residues with operational cycles were observed, their possible causes were also analyzed and discussed. Issues on change in electrode performance due to usage of tin oxide coatings on the MWCNT were also compared and analyzed. [ABSTRACT FROM AUTHOR]

We present a new strategy for analyzing imaging time-of-flight SIMS data sets affected by detector saturation. Rather than attempt to correct the measured data to remove saturation, we incorporate the detector behavior into the statistical basis of the analysis. This is performed within the framework of maximum a posteriori reconstruction. The proposed approach has several advantages over previous techniques. No approximations are involved other than the assumed model of the detector. The method performs well even when applied to highly saturated and/or single-scan data sets. It is statistically rigorous, correctly treating the underlying statistical distribution of the data. It is also compatible with Bayesian methods for incorporating prior knowledge about sample properties. An efficient iterative scheme for solving the proposed equations is presented for the case of the bilinear model commonly used in analyses of SIMS data. The correctness of the approach and its efficacy are demonstrated on synthetic data sets. The method is found to perform better than a widely-used data-correction method used in combination with alternating-least-squares Multivariate Curve Resolution analysis. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

To determine the magnitude of N-isotope fractionation between diamond and its parental fluid, detailed C- and N-isotope analyses of a complexly-zoned, eclogitic diamond (JDE-25) were undertaken using secondary ion mass spectrometry. Combined C- and N-isotope and N-abundance measurements were made across four distinct growth zones and show the following range of values: δ 13 C = − 5.7 to − 2.1‰; δ 15 N = − 7.0 to + 5.5‰; [N] = 104 to 5420 at. ppm. The core zone displays a continuous, rimward increase in δ 13 C and δ 15 N values and decreases in N-abundance, and is interpreted to have formed by fractional crystallization of diamond from a single pulse of fluid (i.e., closed system). Modelling of the isotopic and abundance data from the core zone yields a diamond–fluid nitrogen partition coefficient ( K N ) of 4.4 and a N-isotope fractionation factor (∆ 15 N diam–fluid ) of − 4.0 ± 1.2‰ (2σ) at ~ 1100 °C, for precipitation from a pure carbonate fluid. Calculated K N and ∆ 15 N diam–fluid values would have larger magnitudes if JDE-25 formed from a more complex fluid, in which the carbonate species formed only a minor component. Theoretical calculations of N-isotope fractionation between the principal N-species associated with upper mantle fluids (N 2 , NH 3 or NH 4 + ) and the CN − molecule, as an analogue for the carbon–nitrogen bond in diamond, yield the following ∆ 15 N diam (CN)–fluid estimates at 1100 °C: − 3.6‰ for NH 4 + , − 2.1‰ for N 2 and − 1.4‰ for NH 3 . The theoretical calculations provide only minimum estimates of the true diamond–fluid N-isotope fractionation factor, given that the C–N single bond in diamond would have a lower affinity for 15 N than the stronger C–N triple bond in the CN − molecule. Accordingly, the theoretical N-isotope fractionation factors are consistent with the empirical fractionation factor derived from diamond JDE-25. As a consequence of the large magnitude of ∆ 15 N diam–fluid , intracrystalline N-isotope variations in diamond should provide a sensitive test for fluid-related, fractional crystallization processes. Furthermore, the large magnitude of ∆ 15 N diam–fluid could be reflected in the wide range of δ 15 N values for natural diamonds and the absence of clearly defined modes for the N-isotope compositions of peridotitic and eclogitic diamonds. [ABSTRACT FROM AUTHOR]

The southernmost Baltic Shield exposes polymetamorphic continental crust that was largely formed and accreted during a series of 1.92–1.66 Ga Paleoproterozoic orogenic events and later reworked during the 1.14–0.90 Ga Sveconorwegian orogeny. An intermediate period of metamorphism, deformation and magmatism at 1.47–1.38 Ga has been attributed to the Hallandian orogeny, but due to overprinting by Sveconorwegian high-grade metamorphism and deformation, the P–T-t evolution and deformation of the Hallandian event have remained obscure. This study presents the first quantitative P–T model of the Hallandian event using high-temperature aluminous gneisses in the south-easternmost marginal part of the Sveconorwegian orogen. The high-grade metamorphism and spatially associated granite magmatism are dated using U–Pb SIMS analysis of zircon. Petrography, bulk and mineral geochemistry, and pseudosection models demonstrate prograde staurolite-sillimanite-grade metamorphism reaching granulite-facies temperatures (700–750 °C) at low pressures (4–5 kbar), with the formation of Crd + Sil + Grt + K-fsp + Ilm + Melt ± Bt. The rocks followed a clockwise P–T path. Later stages involved the formation of sillimanite + biotite at the expense of garnet and cordierite. Local low-temperature and fluid-assisted retrogression also caused the formation of chlorite and muscovite at the expense of cordierite. Both granite and aluminous gneisses contain complex zircon with inherited 1.70 Ga igneous cores and high-U, secondary zircon, mainly formed by reworking of protolith cores. The latter date the Hallandian high-grade metamorphism at 1451 ± 6 Ma and the granite magmatism at 1445 ± 8 Ma. The presence of 1.70 Ga igneous zircon cores in both metamorphic and magmatic rocks suggests that they formed from similar protoliths. The protolith ages correlate with the youngest generation of magmatic rocks of the Transscandinavian Igneous Belt. The aluminous gneisses are of supracrustal origin, and may have formed by chemical alteration of magmatic rocks. Hallandian regional metamorphism took place under a strongly elevated geotherm and was associated with granitic magmatism, suggesting an accretionary orogenic setting. The Hallandian event may demonstrate an 1.47–1.38 Ga Andean-type continental margin at the SW margin of Baltica. [ABSTRACT FROM AUTHOR]

The origin and tectonic setting of the Mesoproterozoic (1.50–1.34 Ga) granite–rhyolite Provinces of the midcontinent region of the United States, and the coeval A-type granite plutons of the southwestern United States, have been an enigma for decades. In this paper we review the history of this problem, examine the significance of a wealth of previously published U–Pb zircon and whole-rock Sm–Nd data, and present new U–Pb zircon age and Lu–Hf isotopic data from selected zircon samples. Our data show that the initiation of this magmatism spans the interval 1.50–1.40 Ga across the continent, but there is a general younging westward. Younger, 1.39–1.34 Ga magmatism also occurred across the continent, but forms a major magmatic event only in the south-central mid-continent. There is generally a good correlation between Sm–Nd and Lu–Hf isotopic compositions and inferred mantle derivation model ages, except possibly in southeastern Oklahoma. The absence of older cores in zircons is compatible with calculated zircon saturation temperatures of ca. 850 °C, and supports mantle-driven basaltic underplating and resulting crustal partial melting as a petrogenetic model for the A-type magmatism. Our new data compilation refines the existence of the “Nd-line” that extends from southwestern Texas into southeastern Michigan and the western Grenville Province in Canada; it marks an isotopic boundary between granites and rhyolites of cratonal origin to the northwest (1.8–1.6 Ga model ages) and those of more juvenile origin to the southeast (1.5–1.4 Ga model ages). Our suggested tectonic model for the Mesoproterozoic A-type magmatism across eastern and southern Laurentia involves the development of an active Laurentian margin extending from eastern Canada, across what is now the midcontinent region of the United States, and at least into the current southwestern United States. Magmatism along this margin was likely related to asthenosphere–lithosphere interactions associated with the accretion of outboard arcs and possible exotic terranes that caused complex deformational and magmatic responses in the continental interior. This activity evidently spread from northeast to southwest over a period of ca. 70 million years. The occurrence of the younger, ca. 1.39–1.34 Ga event indicates that similar processes occurred some 130 million years later, suggesting a long-lived convergent plate margin and recurring basaltic underplating in some locations, perhaps due to inboard lithospheric delamination and/or mantle upwelling. [ABSTRACT FROM AUTHOR]

The evaluation of nanostructure is important to develop the highly controlled nanomaterials. In this study, two kinds of layered titanate nanosheets, which were produced by using hexylamine and laurylamine, respectively, as surfactants were investigated by Gentle Secondary Ion Mass Spectrometry Gentle-SIMS (G-SIMS) and g-ogram, which is the latest Time-of-Flight Secondary Ion Mass Spectrometry (TOF-SIMS) data analysis method for detecting more intact ions and obtaining the information on original chemical structures of samples precisely from complicated TOF-SIMS spectra. As a result, molecular related ions of the surfactants were detected from each sample, and the structural information of samples was obtained. From both samples, surfactant molecular ions connected with hydrocarbon were detected as more intact ions rather than molecular ions of themselves. It was suggested that hydrophobic domains of their lamellar mesostructure are formed robustly by more than two surfactant molecules connected with each other linearly. After all, important information on the chemical structure of the layered titanate nanosheets, which would be difficult to be found by using typical structural analysis methods such as X-ray diffraction and transmission electron microscopy, were obtained using G-SIMS and g-ogram. Therefore, it was shown that g-ogram and G-SIMS are helpful to evaluate the nanostructured materials. And it was also shown that g-ogram is applicable to organic-inorganic materials which contain long hydrocarbon structures. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

We propose a new approach to express SIMS depth profiling on a TOF.SIMS-5 time-of-flight mass spectrometer. The approach is based on the instrument capability to independently perform raster scans of sputter and probe ion beams. The probed area can be much smaller than the diameter of a sputter ion beam, like in the AES depth profiling method. This circumstance alleviates limitations on the sputter beam-raster size relation, which are critical in other types of SIMS, and enables analysis on a curved-bottomed sputter crater. By considerably reducing the raster size, it is possible to increase the depth profiling speed by an order of magnitude without radically degrading the depth resolution. A technique is proposed for successive improvement of depth resolution through profile recovery with account for the developing curvature of the sputtered crater bottom in the probed area. Experimental study of the crater bottom form resulted in implementing a method to include contribution of the instrumental artifacts in a nonstationary depth resolution function within the Hofmann's mixing-roughness-information depth model. The real-structure experiment has shown that the analysis technique combining reduction of a raster size with a successive nonstationary recovery ensures high speed of profiling at ~100 µm/h while maintaining the depth resolution of about 30 nm at a 5 µm depth. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The nature and range of threats to security have extremely changed that caused a following reaction which is the transition in the nature of the war as well. Under the changing circumstances of operational environment and in the face of new security environment which is more complex and ambiguous than before, modern armies have started to look for alternatives or for better options to surpass the challenge of transition in the new era. In order to comprehend the security environment better and find out new or alternative ways for solutions, International Conference on Military and Security Studies (ICMSS- 2015) launched in Turkish War Colleges Command, Istanbul on March 10th and 11th. This report is prepared to mention the importance of the military decision making and present the summary of one of the workshops which is "Decision Making and Artificial Intelligence" for the purpose of helping the research in the field of the study. [ABSTRACT FROM AUTHOR]

Business security and threat actors continue to play a dangerous cat-and-mouse game with businesses intellectual property, customer data, and business reputations at stake. Businesses need to delve into a new way of doing business security to break out of this game. Businesses are sitting on repositories full of security-relevant data that is not being capitalized upon with the current information security and physical security organizations within businesses. This article poses the introduction of a data scientist role and a new supporting central data correlation technology platform based on big data predictive analytics into business security functions. The goal is to intelligently and autonomously identify, correlate and pinpoint normally innocuous or unnoticed security event attributes to allow security personnel to preemptively remediate physical and information risks before exploitation or loss of intellectual property occurs. [ABSTRACT FROM PUBLISHER]

Security information and event management (SIEM) is considered to be a promising paradigm to reconcile traditional intrusion detection processes along with most recent advances on artificial intelligence techniques in providing automatic and self-adaptive systems. However, classic management-related flaws still persist, e.g. the fusion of large amounts of security events reported from many heterogeneous systems, whilst novel intriguing challenges arise specially when dealing with the adaptation to newly encountered and multi-step attacks. In this article, we provide SIEM correlation with self-adaptation capabilities to optimize and significantly reduce the intervention of operators. In particular, our enhanced correlation engine automatically learns and produces correlation rules based on the context for different types of multi-step attacks using genetic programming. The context is considered as the knowledge and reasoning, not only acquired by a human expert but also inferred by our system, which assist in the identification and fusion of events. In this regard, a number of artificial neural networks are trained to classify events according to the corresponding context established for the attack. Experimentation is conducted on a real deployment within OSSIM to validate our proposal. [ABSTRACT FROM AUTHOR]

All computers talk; whether it be your laptop, tablet, mobile phone or smart TV, you may never have heard them speak but they have a voice, says Giacomo F. Mosca FBCS, Senior Director, Technical Operations, Transparent Technology [ABSTRACT FROM AUTHOR]