Search results for: returning-oriented programming attacks

Authors: Otto Kakhidze, Hoda Alkhzaimi, Adam Ramey, Nasir Memon

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This paper provides an alternative, cyber security based a conceptual framework for the ethics of automated warfare. The large body of work produced on fully or partially autonomous warfare systems tends to overlook malicious security factors as in the possibility of technical attacks on these systems when it comes to the moral and legal decision-making. The argument provides a risk-oriented justification to why technical malicious risks cannot be dismissed in legal, ethical and policy considerations when warfare models are being implemented and deployed. The assumptions of the paper are supported by providing a broader model that contains the perspective of technological vulnerabilities through the lenses of the Game Theory, Just War Theory as well as standard and non-standard defense ethics. The paper argues that a conventional risk-benefit analysis without considering ethical factors is insufficient for making legal and policy decisions on automated warfare. This approach will provide the substructure for security and defense experts as well as legal scholars, ethicists and decision theorists to work towards common justificatory grounds that will accommodate the technical security concerns that have been overlooked in the current legal and policy models.

Keywords: automated warfare, ethics of automation, inherent hijacking, security vulnerabilities, risk, uncertainty

Procedia PDF Downloads 353

Authors: S. Saju, G. Thirugnanam

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In this paper, a medical image watermarking algorithm based on contourlet is proposed. Medical image watermarking is a special subcategory of image watermarking in the sense that images have special requirements. Watermarked medical images should not differ perceptually from their original counterparts because clinical reading of images must not be affected. Watermarking techniques based on wavelet transform are reported in many literatures but robustness and security using contourlet are better when compared to wavelet transform. The main challenge in exploring geometry in images comes from the discrete nature of the data. In this paper, original image is decomposed to two level using contourlet and the watermark is embedded in the resultant sub-bands. Sub-band selection is based on the value of Peak Signal to Noise Ratio (PSNR) that is calculated between watermarked and original image. To extract the watermark, Kernel ICA is used and it has a novel characteristic is that it does not require the transformation process to extract the watermark. Simulation results show that proposed scheme is robust against attacks such as Salt and Pepper noise, Median filtering and rotation. The performance measures like PSNR and Similarity measure are evaluated and compared with Discrete Wavelet Transform (DWT) to prove the robustness of the scheme. Simulations are carried out using Matlab Software.

Keywords: digital watermarking, independent component analysis, wavelet transform, contourlet

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Authors: Ritsuko Kawasaki (Aiba), Takeshi Hiromatsu

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Management is required to understand all information security risks within an organization, and to make decisions on which information security risks should be treated in what level by allocating how much amount of cost. However, such decision-making is not usually easy, because various measures for risk treatment must be selected with the suitable application levels. In addition, some measures may have objectives conflicting with each other. It also makes the selection difficult. Moreover, risks generally have trends and it also should be considered in risk treatment. Therefore, this paper provides the extension of the model proposed in the previous study. The original model supports the selection of measures by applying a combination of weighted average method and goal programming method for multi-objective analysis to find an optimal solution. The extended model includes the notion of weights to the risks, and the larger weight means the priority of the risk.

Keywords: information security risk treatment, selection of risk measures, risk acceptance, multi-objective optimization

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Authors: Lan Nguyen, Kien Le Tan, Bao Nguyen Pham Gia

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Due to the high cost, specialized dynamic measurement devices for industrial lands are difficult for many colleges to equip for hands-on teaching. This study connects a dynamic measurement sensor and receiver utilizing an inexpensive Raspberry Pi 4 board, some 24-bit ADC circuits, a geophone vibration sensor, and embedded Python open-source programming. Gather and analyze signals for dynamic measuring, ground vibration monitoring, and structure vibration monitoring. The system may wirelessly communicate data to the computer and is set up as a communication node network, enabling real-time monitoring of background vibrations at various locations. The device can be utilized for a variety of dynamic measurement and monitoring tasks, including monitoring earthquake vibrations, ground vibrations from construction operations, traffic, and vibrations of building structures.

Keywords: sensors, FFT, signal processing, real-time data monitoring, ground propagation wave, python, raspberry Pi 4

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Authors: Tydra Preyear, Victor Clincy

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Quantum computing presents many computational advantages over classical computing methods due to the utilization of quantum mechanics. The capability of this computing infrastructure poses threats to standard cryptographic systems such as RSA and AES, which are designed for classical computing environments. This paper discusses the impact that quantum computing has on cryptography, while focusing on the evolution from classical cryptographic concepts to quantum and post-quantum cryptographic concepts. Standard Cryptography is essential for securing data by utilizing encryption and decryption methods, and these methods face vulnerability problems due to the advancement of quantum computing. In order to counter these vulnerabilities, the methods that are proposed are quantum cryptography and post-quantum cryptography. Quantum cryptography uses principles such as the uncertainty principle and photon polarization in order to provide secure data transmission. In addition, the concept of Quantum key distribution is introduced to ensure more secure communication channels by distributing cryptographic keys. There is the emergence of post-quantum cryptography which is used for improving cryptographic algorithms in order to be more secure from attacks by classical and quantum computers. Throughout this exploration, the paper mentions the critical role of the advancement of cryptographic methods to keep data integrity and privacy safe from quantum computing concepts. Future research directions that would be discussed would be more effective cryptographic methods through the advancement of technology.

Keywords: quantum computing, quantum cryptography, cryptography, data integrity and privacy

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Authors: Alan (Avi) Kirschenbaum, Carmit Rapaport

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The behavior of bystanders in emergencies and disasters have been examined for over 50 years. Such acts have been cited as contributing to saving lives in terms of providing first responder help until official emergency units can arrive. Several reasons have been suggested for this type of behavior but most focused on a broad segment of individual psychological decision-making processes. Recent theoretical evidence suggests that the external factors for such bystander decisions, mainly disaster community based social contexts factors, are also important. We aim to test these competing arguments. Specifically, we examine alternative explanatory perspectives by focusing on self-efficacy as a proxy for the accepted individual psychological case and contrast it with potential bystander characteristics of the individual as well factors as embedded in the social context of the disaster community. To do so, we will utilize a random sampling of the population from a field study of an urban community in Israel that experienced five years of continuous terror attacks. The results strongly suggest that self-efficacy, as well as external factors: preparedness and having skills for intervention during emergencies along with gender best, predict potential helping behaviors. These results broaden our view of bystander behavior and open a window for enhancing this phenomenon as another element in disaster and crisis management.

Keywords: bystander behavior, disasters emergencies, psychological motivation to help, social context for helping

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Authors: Jungho Moon, Lae-Jeong Park

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This paper introduces a signal monitoring program developed with a view to helping electrical engineering students get familiar with sensors with digital output. Because the output of digital sensors cannot be simply monitored by a measuring instrument such as an oscilloscope, students tend to have a hard time dealing with digital sensors. The monitoring program runs on a PC and communicates with an MCU that reads the output of digital sensors via an asynchronous communication interface. Receiving the sensor data from the MCU, the monitoring program shows time and/or frequency domain plots of the data in real time. In addition, the monitoring program provides a serial terminal that enables the user to exchange text information with the MCU while the received data is plotted. The user can easily observe the output of digital sensors and configure the digital sensors in real time, which helps students who do not have enough experiences with digital sensors. Though the monitoring program was programmed in the Matlab programming language, it runs without the Matlab since it was compiled as a standalone executable.

Keywords: digital sensor, MATLAB, MCU, signal monitoring program

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Authors: Kim Lytle, Tim Talty, Alan Michaels, Jeff Reed

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Implantable medical devices (IMDs) are medically necessary devices embedded in the human body that monitor chronic disorders or automatically deliver therapies. Most IMDs have wireless capabilities that allow them to share data with an offboard programming device to help medical providers monitor the patient’s health while giving the patient more insight into their condition. However, serious security concerns have arisen as researchers demonstrated these devices could be hacked to obtain sensitive information or harm the patient. Cooperative jamming can be used to prevent privileged information leaks by maintaining an adequate signal-to-noise ratio at the intended receiver while minimizing signal power elsewhere. This paper uses ray tracing to demonstrate how a low number of friendly nodes abiding by Bluetooth Low Energy (BLE) transmission regulations can enhance IMD communication security in an office environment, which in turn may inform how companies and individuals can protect their proprietary and personal information.

Keywords: implantable biomedical devices, communication system security, array signal processing, ray tracing

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Authors: Mark Davey

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Communications on a Network on Chip (NoC) produce timing information, i.e., network injection delays, packet traversal times, throughput metrics, and other attributes relating to the traffic being sent across the chip. The security requirements of a platform encompass each node to operate with confidentiality, integrity, and availability (ISO 27001). Inherently, a shared NoC interconnect is exposed to analysis of timing patterns created by contention for the network components, i.e., links and switches/routers. This phenomenon is defined as information leakage, which represents a ‘side channel’ of sensitive information that can be correlated to platform activity. The key algorithm presented in this paper evaluates how an adversary can control two platform neighbouring nodes of a target node to obtain sensitive information about communication with the target node. The actual information obtained is the period value of a periodic task communication. This enacts a breach of the expected confidentiality of a node operating in a multiprocessor platform. An experimental investigation of the side channel is undertaken to judge the level and significance of inferred information produced by access times to the NoC. Results are presented with a series of expanding task set scenarios to evaluate the efficacy of the side channel detection algorithm as the network load increases.

Keywords: embedded systems, multiprocessor, network on chip, side channel

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Authors: Htay Htay Yi, Zin May Aye

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Network security is role of the ICT environment because malicious users are continually growing that realm of education, business, and then related with ICT. The network security contravention is typically described and examined centrally based on a security event management system. The firewalls, Intrusion Detection System (IDS), and Intrusion Prevention System are becoming essential to monitor or prevent of potential violations, incidents attack, and imminent threats. In this system, the firewall rules are set only for where the system policies are needed. Dataset deployed in this system are derived from the testbed environment. The traffic as in DoS and PortScan traffics are applied in the testbed with firewall and IDS implementation. The network traffics are classified as normal or attacks in the existing testbed environment based on six machine learning classification methods applied in the system. It is required to be tested to get datasets and applied for DoS and PortScan. The dataset is based on CICIDS2017 and some features have been added. This system tested 26 features from the applied dataset. The system is to reduce false positive rates and to improve accuracy in the implemented testbed design. The system also proves good performance by selecting important features and comparing existing a dataset by machine learning classifiers.

Keywords: false negative rate, intrusion detection system, machine learning methods, performance

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Authors: Pooja Mishra, Chris Pollett

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This paper explores efficient ways to implement various media-updating features like news aggregation, video conversion, and bulk email handling. All of these jobs share the property that they are periodic in nature, and they all benefit from being handled in a distributed fashion. The data for these jobs also often comes from a social or collaborative source. We isolate the class of periodic, one round map reduce jobs as a useful setting to describe and handle media updating tasks. As such tasks are simpler than general map reduce jobs, programming them in a general map reduce platform could easily become tedious. This paper presents a MediaUpdater module of the Yioop Open Source Search Engine Web Portal designed to handle such jobs via an extension of a PHP class. We describe how to implement various media-updating tasks in our system as well as experiments carried out using these implementations on an Amazon Web Services cluster.

Keywords: distributed jobs framework, news aggregation, video conversion, email

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Authors: Saeedeh Ahmadi Basir, Mohammad Mahdavi Mazdeh, Mohammad Namakshenas

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Manufacturers often dispatch jobs in batches to reduce delivery costs. However, sending several jobs in batches can have a negative effect on other scheduling-related objective functions such as minimizing the number of tardy jobs which is often used to rate managers’ performance in many manufacturing environments. This paper aims to minimize the number of weighted tardy jobs and the sum of delivery costs of a two-stage assembly flow-shop problem in a batch delivery system. We present a mixed-integer linear programming (MILP) model to solve the problem. As this is an MILP model, the commercial solver (the CPLEX solver) is not guaranteed to find the optimal solution for large-size problems at a reasonable amount of time. We present several numerical examples to confirm the accuracy of the model.

Keywords: scheduling, two-stage assembly flow-shop, tardy jobs, batched delivery system

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Authors: Diego De Castro Rodrigues, Marcelo Lisboa Rocha, Daniela M. De Q. Trevisan, Marcos Dias Da Conceicao, Gabriel Rosa, Rommel M. Barbosa

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The use of association rules algorithms within data mining is recognized as being of great value in the knowledge discovery in databases. Very often, the number of rules generated is high, sometimes even in databases with small volume, so the success in the analysis of results can be hampered by this quantity. The purpose of this research is to present a method for reducing the quantity of rules generated with association algorithms. Therefore, a computational algorithm was developed with the use of a Weka Application Programming Interface, which allows the execution of the method on different types of databases. After the development, tests were carried out on three types of databases: synthetic, model, and real. Efficient results were obtained in reducing the number of rules, where the worst case presented a gain of more than 50%, considering the concepts of support, confidence, and lift as measures. This study concluded that the proposed model is feasible and quite interesting, contributing to the analysis of the results of association rules generated from the use of algorithms.

Keywords: data mining, association rules, rules reduction, artificial intelligence

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Authors: Ziyuan Wu, Yulong Jia, Xiang Zhang, Wanting Zhou, Lei Li

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The Internet of Things (IoT) is a rapidly evolving field involving a large number of interconnected embedded devices. In the design of embedded System-on-Chip (SoC), the key issues are power consumption, performance, and security. However, the easy-to-implement software and untrustworthy third-party IP cores may threaten the safety of hardware assets. Considering that illegal access and malicious attacks against SoC resources pass through the bus that integrates IPs, we propose a Lightweight Hardware Firewall (LHF) to protect SoC, which monitors and disallows the offending bus transactions based on physical addresses. Furthermore, under the LHF architecture, this paper refines two types of firewalls: Destination Hardware Firewall (DHF) and Source Hardware Firewall (SHF). The former is oriented to fine-grained detection and configuration, whose core technology is based on the method of dynamic grading units. In addition, we design the SHF based on static entries to achieve lightweight. Finally, we evaluate the hardware consumption of the proposed method by both Field-Programmable Gate Array (FPGA) and IC. Compared with the exciting efforts, LHF introduces a bus latency of zero clock cycles for every read or write transaction implemented on Xilinx Kintex-7 FPGAs. Meanwhile, the DC synthesis results based on TSMC 90nm show that the area is reduced by about 25% compared with the previous method.

Keywords: IoT, security, SoC, bus architecture, lightweight hardware firewall, FPGA

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Authors: Zakir Husain

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Main objective of a power transformer design optimization problem requires minimizing the total overall cost and/or mass of the winding and core material by satisfying all possible constraints obligatory by the standards and transformer user requirement. The constraints include appropriate limits on winding fill factor, temperature rise, efficiency, no-load current and voltage regulation. The design optimizations tasks are a constrained minimum cost and/or mass solution by optimally setting the parameters, geometry and require magnetic properties of the transformer. In this paper, present the above design problems have been formulated by using genetic algorithm (GA) and simulated annealing (SA) on the MATLAB platform. The importance of the presented approach is stems for two main features. First, proposed technique provides reliable and efficient solution for the problem of design optimization with several variables. Second, it guaranteed to obtained solution is global optimum. This paper includes a demonstration of the application of the genetic programming GP technique to transformer design.

Keywords: optimization, power transformer, genetic algorithm (GA), simulated annealing technique (SA)

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Authors: Michał Witas

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This paper presents a technical approach to analysis of security of SCADA systems. Main goal of the paper is to make SCADA administrators aware of risks resulting from SCADA systems usage and to familiarize with methods that can be adopt to existing or planned system, to increase overall system security level. Because SCADA based systems become a industrial standard, more attention should be paid to the security of that systems. Industrial Control Systems (ICS) like SCADA are responsible for controlling crucial aspects of wide range of industrial processes. In pair with that responsibility, goes a lot of money that can be earned or lost – this fact is main reason of increased interest of attackers. Additionally ICS are often responsible for maintaining resources strategic from the point of view of national economy, like electricity (including nuclear power plants), heating, water resources or military facilities, so they can be targets of terrorist cybernetic attacks. Without proper risk analysis and management, vulnerabilities resulting from the usage of SCADA can be easily exploited by potential attacker. Paper is based mostly on own experience in systems security, gathered during academic studies and professional work in international company. As title suggests, it will cover only basics of topic, because every of points mentioned in the document can be base for additional research and papers.

Keywords: denial of service, SCADA, security policy, distributed network

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Authors: Olumide A. Fafore, Khondlo Mtshali

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The beginning of the 21st century saw the emergence of new and global threats to national and transnational security in West Africa and the Asia Pacific regions as a result of the spread of jihadist terrorism across borders, a manifestation of the rise of radical Islam. Extremist and armed Islamic movements influenced by Salafism, the Jihad in Afghanistan and the Muslim Brotherhood are prevalent in Northern Nigeria, Niger, Cameroon, Mali, Chad, Pakistan, Afghanistan, and India. Carrying out attacks across borders, including assassinations, murders, armed robberies, and kidnapping, assisted by open and porous borders and large flow of illegal immigrants across borders. This paper examines the effect of Radical Islam on Transnational security through a review of past literature and the social and security consequences on the people of the regions. Our findings indicate that the activities of armed Islamic movements such as Boko Haram, Ansaru and Al-Qaeda are having a negative impact on the economy, development, and security of the states and people of West Africa and the Asia Pacific. It stresses the importance of regional, transnational and international cooperation, as these threats to national and transnational security can no longer be solved in a national or regional framework.

Keywords: Islamic movements, jihadist terrorism, radical Islam, transnational security

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Authors: Abul Bashar

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The recent surge in the adoption of cloud computing systems by various organizations has brought forth the challenge of evaluating their performance. One of the major issues faced by the cloud service providers and customers is to assess the ability of cloud computing systems to provide the desired services in accordance to the QoS and SLA constraints. To this end, an opportunity exists to develop means to ensure that the desired performance levels of such systems are met under simulated environments. This will eventually minimize the service disruptions and performance degradation issues during the commissioning and operational phase of cloud computing infrastructure. However, it is observed that several simulators and modelers are available for simulating the cloud computing systems. Therefore, this paper presents a critical evaluation of the state-of-the-art modeling and simulation frameworks applicable to cloud computing systems. It compares the prominent simulation frameworks in terms of the API features, programming flexibility, operating system requirements, supported services, licensing needs and popularity. Subsequently, it provides recommendations regarding the choice of the most appropriate framework for researchers, administrators and managers of cloud computing systems.

Keywords: cloud computing, modeling framework, performance evaluation, simulation tools

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Authors: Lakshmi Prayaga, Chandra Prayaga. Aaron Wade, Gopi Shankar Mallu, Harsha Satya Pola

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Synthetic data generated by Generative Adversarial Networks and Autoencoders is becoming more common to combat the problem of insufficient data for research purposes. However, generating synthetic data is a tedious task requiring extensive mathematical and programming background. Open-source platforms such as the Synthetic Data Vault (SDV) and Mostly AI have offered a platform that is user-friendly and accessible to non-technical professionals to generate synthetic data to augment existing data for further analysis. The SDV also provides for additions to the generic GAN, such as the Gaussian copula. We present the results from two synthetic data sets (CTGAN data and CTGAN with Gaussian Copula) generated by the SDV and report the findings. The results indicate that the ROC and AUC curves for the data generated by adding the layer of Gaussian copula are much higher than the data generated by the CTGAN.

Keywords: synthetic data generation, generative adversarial networks, conditional tabular GAN, Gaussian copula

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Authors: Selcuk Aslan, Dervis Karaboga, Celal Ozturk

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Artificial Bee Colony (ABC) algorithm is one of the most successful swarm intelligence based metaheuristics. It has been applied to a number of constrained or unconstrained numerical and combinatorial optimization problems. In this paper, we presented a parallelized version of ABC algorithm by adapting employed and onlooker bee phases to the Compute Unified Device Architecture (CUDA) platform which is a graphical processing unit (GPU) programming environment by NVIDIA. The execution speed and obtained results of the proposed approach and sequential version of ABC algorithm are compared on functions that are typically used as benchmarks for optimization algorithms. Tests on standard benchmark functions with different colony size and number of parameters showed that proposed parallelization approach for ABC algorithm decreases the execution time consumed by the employed and onlooker bee phases in total and achieved similar or better quality of the results compared to the standard sequential implementation of the ABC algorithm.

Keywords: Artificial Bee Colony algorithm, GPU computing, swarm intelligence, parallelization

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Authors: Abed Ahmed, Mehrdad Asadi, Jennifer Martay

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Stainless steel pipelines are crucial components to transportation and storage in the oil and gas industry. However, the rise of random attacks and vandalism on these pipes for their valuable transport has led to more security and protection for incoming surface impacts. These surface impacts can lead to large global deformations of the pipe and place the pipe under strain, causing the eventual failure of the pipeline. Therefore, understanding how these surface impact loads affect the pipes is vital to improving the pipes’ security and protection. In this study, experimental test and finite element analysis (FEA) have been carried out on EN3B stainless steel specimens to study the impact behaviour. Low velocity impact tests at 9 m/s with 16 kg dome impactor was used to simulate for high momentum impact for localised failure. FEA models of clamped and deformable boundaries were modelled to study the effect of the boundaries on the pipes impact behaviour on its impact resistance, using experimental and FEA approach. Comparison of experimental and FE simulation shows good correlation to the deformable boundaries in order to validate the robustness of the FE model to be implemented in pipe models with complex anisotropic structure.

Keywords: dynamic impact, deformable boundary conditions, finite element modelling, LS-DYNA, stainless steel pipe

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Authors: Michael Josef Schwerer

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Background: The identification of unknown victims from mass disasters, violent crimes, or terrorist attacks is frequently facilitated through information from missing persons lists, portrait photos, old or recent pictures showing unique characteristics of a person such as scars or tattoos, or simply reference samples from blood relatives for DNA analysis. In contrast, the identification or at least the characterization of an unknown perpetrator from criminal or terrorist actions remains challenging, particularly in the absence of material or data for comparison, such as fingerprints, which had been previously stored in criminal records. In scenarios that result in high levels of destruction of the perpetrator’s corpse, for instance, blast or fire events, the chance for a positive identification using standard techniques is further impaired. Objectives: This study shows the forensic genetic procedures in the Legal Medicine Service of the German Air Force for the identification of unknown individuals, including such cases in which reference samples are not available. Scenarios requiring such efforts predominantly involve aircraft crash investigations, which are routinely carried out by the German Air Force Centre of Aerospace Medicine as one of the Institution’s essential missions. Further, casework by military police or military intelligence is supported based on administrative cooperation. In the talk, data from study projects, as well as examples from real casework, will be demonstrated and discussed with the audience. Methods: Forensic genetic identification in our laboratories involves the analysis of Short Tandem Repeats and Single Nucleotide Polymorphisms in nuclear DNA along with mitochondrial DNA haplotyping. Extended DNA analysis involves phenotypic markers for skin, hair, and eye color together with the investigation of a person’s biogeographic ancestry. Assessment of the biological age of an individual employs CpG-island methylation analysis using bisulfite-converted DNA. Forensic Investigative Genealogy assessment allows the detection of an unknown person’s blood relatives in reference databases. Technically, end-point-PCR, real-time PCR, capillary electrophoresis, pyrosequencing as well as next generation sequencing using flow-cell-based and chip-based systems are used. Results and Discussion: Optimization of DNA extraction from various sources, including difficult matrixes like formalin-fixed, paraffin-embedded tissues, degraded specimens from decomposed bodies or from decedents exposed to blast or fire events, provides soil for successful PCR amplification and subsequent genetic profiling. For cases with extremely low yields of extracted DNA, whole genome preamplification protocols are successfully used, particularly regarding genetic phenotyping. Improved primer design for CpG-methylation analysis, together with validated sampling strategies for the analyzed substrates from, e.g., lymphocyte-rich organs, allows successful biological age estimation even in bodies with highly degraded tissue material. Conclusions: Successful identification of unknown individuals or at least their phenotypic characterization using pigmentation markers together with age-informative methylation profiles, possibly supplemented by family tree search employing Forensic Investigative Genealogy, can be provided in specialized laboratories. However, standard laboratory procedures must be adapted to work with difficult and highly degraded sample materials.

Keywords: identification, forensic genetics, phenotypic markers, CPG methylation, biological age estimation, forensic investigative genealogy

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Authors: Behnam Zahednejad, Saeed Kosari

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Widespread deployment of Internet of Things (IoT) has raised security and privacy issues in this environment. Designing a secure two-factor authentication scheme between the user and server is still a challenging task. In this paper, we focus on Cancelable Biometric (CB) as an authentication factor in IoT. We show that previous CB-based scheme fail to provide real two-factor security, Perfect Forward Secrecy (PFS) and suffer database attacks and traceability of the user. Then we propose our improved scheme based on CB and Physically Unclonable Functions (PUF), which can provide real two-factor security, PFS, user’s unlinkability, and resistance to database attack. In addition, Key Compromise Impersonation (KCI) resilience is achieved in our scheme. We also prove the security of our proposed scheme formally using both Real-Or-Random (RoR) model and the ProVerif analysis tool. For the usability of our scheme, we conducted a performance analysis and showed that our scheme has the least communication cost compared to the previous CB-based scheme. The computational cost of our scheme is also acceptable for the IoT environment.

Keywords: IoT, two-factor security, cancelable biometric, key compromise impersonation resilience, perfect forward secrecy, database attack, real-or-random model, ProVerif

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Authors: Nuur Ezaini Akmar Ismail, Norbazilah Rahim, Norul Huda Md Rasdi, Maslina Daud

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A web application is the most targeted by the attacker because the web application is accessible by the end users. It has become more advantageous to the attacker since not all the end users aware of what kind of sensitive data already leaked by them through the Internet especially via social network in shake on ‘sharing’. The attacker can use this information such as personal details, a favourite of artists, a favourite of actors or actress, music, politics, and medical records to customize phishing attack thus trick the user to click on malware-laced attachments. The Phishing attack is one of the most popular attacks for social engineering technique against web applications. There are several methods to detect phishing websites such as Blacklist/Whitelist based detection, heuristic-based, and visual similarity-based detection. This paper illustrated a comparison between the heuristic-based technique using features of a uniform resource locator (URL) and visual similarity-based detection techniques that compares the content of a suspected phishing page with the legitimate one in order to detect new phishing sites based on the paper reviewed from the past few years. The comparison focuses on three indicators which are false positive and negative, accuracy of the method, and time consumed to detect phishing website.

Keywords: heuristic-based technique, phishing detection, social engineering and visual similarity-based technique

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Authors: Danielle Klassen, Reiko Yeap, Margo Schmitt-Boshnick, Scott Oddie

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The development of the 7-week Alberta Happiness Basics program was initiated in 2010 in response to the need for community mental health programming. This provincial wide program aims to increase overall happiness and reduce negative thoughts and feelings through a positive psychology intervention. While the 7-week program has proven effective, a shortened 4-week program has additionally been developed to address client needs. In this study, participants were interviewed to determine if the 4- and 7-week programs had similar success of producing lasting behavior change at 3, 6, and 9 months post-program. A health quality of life (HQOL) measure was also used to compare the two programs and examine patient outcomes. Quantitative and qualitative analysis showed significant improvements in HQOL and sustainable behavior change for both programs. Findings indicate that the shorter, patient-centered program was effective in increasing happiness and reducing negative thoughts and feelings.

Keywords: primary care, mental health, depression, short duration

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Authors: Basil Manos, Thomas Bournaris, Christina Moulogianni

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The European agricultural policy supports all member states to apply agricultural development plans for the development of their agricultural sectors. A specific measure of the agricultural development plans refers to young people in order to enter into the agricultural sector. This measure helps the participating young farmers in achieving maximum efficiency, using methods and environmentally friendly practices, by altering their farm plans. This study applies a Multicriteria Mathematical Programming (MCDA) model for the young farmers to find farm plans that achieve the maximum gross margin and the minimum environmental impacts (less use of fertilizers and irrigation water). The analysis was made in the region of Central Macedonia, Greece, among young farmers who have participated in the “Setting up Young Farmers” measure during 2007-2010. The analysis includes the implementation of the MCDA model for the farm plans optimization and the comparison of selected environmental indicators with those of the existent situation.

Keywords: multicriteria, optimum farm plans, environmental impacts, sustainable management

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Authors: Mohsen Najarchi

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This research was carried out in five fields (5-15 hectares) in Arak located in center of Iran, to determine optimum level of water consumed for Barely in four stages growth (vegetative, yield formation, flowering, and ripening). Actual evapotranspiration was calculated using measured water requirement in the fields. Five levels of water requirement equal to 50, 60, 70, 80, and 90 percents formed the treatments. To determine the optimum level of water requirement linear programming was used. The study showed 60 percent water requirement (40 percent deficit irrigation) has been the optimum level of irrigation for winter wheat in four stages of growth. Comparison between all of the treatments indicated above with normal condition (100% water requirement) shows increasing in water use efficiency. Although 40% deficit irrigation treatment lead to decrease of 38% in yield, net benefit was increasing in 11.37%. Furthermore, in comparison with normal condition, 70% of water requirement increased water use efficiency as 30%.

Keywords: optimum, deficit irrigation, water use efficiency, evapotranspiration

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Authors: Atefeh Saljooghi Khoshkar, Jafar Hassanpour

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One of the main problems of the design stage relating to many tunneling projects is the lack of an appropriate standard for the provision of engineering geological data in a predefined format. In particular, this is more reflected in highway and railroad tunnel projects in which there is a number of tunnels and different professional teams involved. In this regard, comprehensive software needs to be designed using the accepted methods in order to help engineering geologists to prepare standard reports, which contain sufficient input data for the design stage. Regarding this necessity, applied software has been designed using macro capabilities and Visual Basic programming language (VBA) through Microsoft Excel. In this software, all of the engineering geological input data, which are required for designing different parts of tunnels, such as discontinuities properties, rock mass strength parameters, rock mass classification systems, boreability classification, the penetration rate, and so forth, can be calculated and reported in a standard format.

Keywords: engineering geology, rock mass classification, rock mechanic, tunnel

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Authors: Francis E. Idachaba, Sarah Uyimeh Tommy

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This paper describes the design of an RFID laptop monitoring and management system. Laptops embedded with RFID chips are monitored and tracked to provide a monitoring system for the purpose of tracking as well as monitoring movement of the laptops in and out of a building. The proposed system is implemented with both hardware and software components. The hardware architecture consists of RFID passive tag, RFID module (reader), and a server hosting the application and database. The RFID readers are distributed at major exits of a building or premises. The tags are programmed with owner laptop details are concealed in the laptops. The software architecture consists of application software that has the APIs (Applications Programming Interface) necessary to interface the RFID system with the PC, to achieve automated laptop monitoring system. A friendly graphic user interface (GUI) and a database that saves all readings and owners details. The system is capable of reducing laptop theft especially in students’ hostels as laptops can be monitored as they are taken either in or out of the building.

Keywords: asset tracking, GUI, laptop monitoring, radio frequency identification, passive tags

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Authors: Roseline Oghogho Osaseri, Osaseri E. I.

Abstract:

Lassa fever is an epidemic hemorrhagic fever caused by the Lassa virus, an extremely virulent arena virus. This highly fatal disorder kills 10% to 50% of its victims, but those who survive its early stages usually recover and acquire immunity to secondary attacks. One of the major challenges in giving proper treatment is lack of fast and accurate diagnosis of the disease due to multiplicity of symptoms associated with the disease which could be similar to other clinical conditions and makes it difficult to diagnose early. This paper proposed an Adaptive Neuro Fuzzy Inference System (ANFIS) for the prediction of Lass Fever. In the design of the diagnostic system, four main attributes were considered as the input parameters and one output parameter for the system. The input parameters are Temperature on admission (TA), White Blood Count (WBC), Proteinuria (P) and Abdominal Pain (AP). Sixty-one percent of the datasets were used in training the system while fifty-nine used in testing. Experimental results from this study gave a reliable and accurate prediction of Lassa fever when compared with clinically confirmed cases. In this study, we have proposed Lassa fever diagnostic system to aid surgeons and medical healthcare practictionals in health care facilities who do not have ready access to Polymerase Chain Reaction (PCR) diagnosis to predict possible Lassa fever infection.

Keywords: anfis, lassa fever, medical diagnosis, soft computing

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