This article is devoted to an empirical investigation of performance of several new large multi-t... more This article is devoted to an empirical investigation of performance of several new large multi-tier ensembles for the detection of cardiac autonomic neuropathy (CAN) in diabetes patients using subsets of the Ewing features. We used new data collected by the diabetes screening research initiative (DiScRi) project, which is more than ten times larger than the data set originally used by Ewing in the investigation of CAN. The results show that new multi-tier ensembles achieved better performance compared with the outcomes published in the literature previously. The best accuracy 97.74% of the detection of CAN has been achieved by the novel multi-tier combination of AdaBoost and Bagging, where AdaBoost is used at the top tier and Bagging is used at the middle tier, for the set consisting of the following four Ewing features: the deep breathing heart rate change, the Valsalva manoeuvre heart rate change, the hand grip blood pressure change and the lying to standing blood pressure change.
Proceedings of the 1st International Conference on Cloud Computing and Services Science, 2011
We consider a cloud data storage involving three entities, the cloud customer, the cloud business... more We consider a cloud data storage involving three entities, the cloud customer, the cloud business centre which provides services, and the cloud data storage centre. Data stored in the data storage centre comes from a variety of customers and some of these customers may compete with each other in the market place or may own data which comprises confidential information about their own clients. Cloud staff have access to data in the data storage centre which could be used to steal identities or to compromise cloud customers. In this paper, we provide an efficient method of data storage which prevents staff from accessing data which can be abused as described above. We also suggest a method of securing access to data which requires more than one staff member to access it at any given time. This ensures that, in case of a dispute, a staff member always has a witness to the fact that she accessed data.
2009 10th International Symposium on Pervasive Systems, Algorithms, and Networks, 2009
Abstract Protecting user's mailbox from infiltration of phishing email is a sign... more Abstract Protecting user's mailbox from infiltration of phishing email is a significant research issue now a day. Many researches are going on filtering phishing using classification based algorithms and achieve substantial performance. It has been studied and investigated with ...
Dark Web is one of the most challenging and untraceable mediums adopted by the cyber criminals, t... more Dark Web is one of the most challenging and untraceable mediums adopted by the cyber criminals, terrorists, and state-sponsored spies to fulfil their illicit motives. Cyber-crimes happening inside the Dark Web are alike the real world crimes. However, the sheer size, unpredictable ecosystem and anonymity provided by the Dark Web services are the essential confrontations to trace the criminals. To discover the potential solutions towards cyber-crimes evaluating the sailing Dark Web crime threats is a crucial step. In this paper, we will appraise the Dark Web by analysing the crimes with their consequences and enforced methods as well as future manoeuvres to lessen the crime threats. We used Systematic Literature Review (SLR) method with the aspiration to provide the direction and aspect of emerging crime threats in the Dark Web for the researchers and specialist in Cyber security field. For this SLR 65 most relevant articles from leading electronic databases were selected for data extraction and synthesis to answer our predefined research questions. The result of this systematic literature review provides (i) comprehensive knowledge on the growing crimes proceeding with Dark Web (ii) assessing the social, economic and ethical impacts of the cyber-crimes happening inside the Dark Web and (iii) analysing the challenges, established techniques and methods to locate the criminals and their drawbacks. Our study reveals that more in depth researches are required to identify criminals in the Dark Web with new prominent way, the crypto markets and Dark Web discussion forums analysis is crucial for forensic investigations, the anonymity provided by Dark Web services can be used as a weapon to catch the criminals and digital evidences should be analysed and processed in a way that follows the law enforcement to make the seizure of the criminals and shutting down the illicit sites in the Dark Web. INDEX TERMS Crypto market, cyber crime, dark web, onion router.
Algorithms and Architectures for Parallel Processing, 2018
With the development of big data, a demand for data analysis keeps increasing. This requirement h... more With the development of big data, a demand for data analysis keeps increasing. This requirement has prompted a need for data-aware task scheduling approach that can simultaneously schedule various tasks such as batched tasks and real-time tasks in a data center efficiently. To this end, we propose a hybrid task scheduling strategy coupled with data migration in data center. Firstly, we translate the task scheduling problem into task selection problem, and give methods of selecting batched tasks and real-time tasks respectively. Then the method for scheduling both batched tasks and real-time tasks is introduced in detail. Finally, we integrate data migration into the hybrid scheduling strategy. Experimental results show that, compared to the traditional FIFO algorithm, the proposed task scheduling strategy greatly improves the data locality and data migration performs very well on reducing the job execution time. Our algorithm also guarantees an acceptable fairness for tasks.
International Journal of Building Pathology and Adaptation, 2020
PurposeThis research paper adopts the fundamental tenets of advanced technologies in industry 4.0... more PurposeThis research paper adopts the fundamental tenets of advanced technologies in industry 4.0 to monitor the structural health of concrete beam members using cost-effective non-destructive technologies. In so doing, the work illustrates how a coalescence of low-cost digital technologies can seamlessly integrate to solve practical construction problems.Design/methodology/approachA mixed philosophies epistemological design is adopted to implement the empirical quantitative analysis of “real-time” data collected via sensor-based technologies streamed through a Raspberry Pi and uploaded onto a cloud-based system. Data was analysed using a hybrid approach that combined both vibration-characteristic-based method and linear variable differential transducers (LVDT).FindingsThe research utilises a novel digital research approach for accurately detecting and recording the localisation of structural cracks in concrete beams. This non-destructive low-cost approach was shown to perform with ...
H1/IC31® is a tuberculosis (TB) subunit vaccine candidate consisting of the fusion protein of Ag8... more H1/IC31® is a tuberculosis (TB) subunit vaccine candidate consisting of the fusion protein of Ag85B and ESAT-6 (H1) formulated with the IC31® adjuvant. Previous trials have reported on the H1/IC31® vaccine in M. tuberculosis (Mtb)-naïve, BCG-vaccinated and previously Mtb-infected individuals. In this trial, conducted between December 2008 and April 2010, the safety and immunogenicity of H1/IC31® was assessed in participants living in Ethiopia - a highly TB-endemic area. Healthy male participants aged 18-25 years were recruited into four groups. Participants in group 1 (N = 12) and group 2 (N = 12) were Tuberculin Skin Test (TST) negative and QuantiFERON-TB Gold in-tube test (QFT) negative (Mtb-naïve groups), participants in group 3 (N = 3) were TST positive and QFT negative (BCG group), and participants in group 4 (N = 12) were both TST and QFT positive (Mtb-infected group). H1 vaccine alone (group 1) or H1 formulated with the adjuvant IC31® (groups 2, 3 and 4) was administered intr...
IEEE Transactions on Evolutionary Computation, 2017
Evolutionary algorithms (EAs) have recently been suggested as a candidate for solving big data op... more Evolutionary algorithms (EAs) have recently been suggested as a candidate for solving big data optimization problems that involve a very large number of variables and need to be analyzed in a short period of time. However, EAs face a scalability issue when dealing with big data problems. Moreover, the performance of EAs critically hinges on the utilized parameter values and operator types, thus it is impossible to design a single EA that can outperform all others in every problem instance. To address these challenges, we propose a heterogeneous framework that integrates a cooperative co-evolution method with various types of memetic algorithms. We use the cooperative co-evolution method to split the big problem into subproblems in order to increase the efficiency of the solving process. The subproblems are then solved using various heterogeneous memetic algorithms. The proposed heterogeneous framework adaptively assigns, for each solution, different operators, parameter values and a local search algorithm to efficiently explore and exploit the search space of the given problem instance. The performance of the proposed algorithm is assessed using the Big Data 2015 competition benchmark problems that contain data with and without noise. Experimental results demonstrate that the proposed algorithm, with the cooperative co-evolution method, performs better than without the cooperative co-evolution method. Furthermore, it obtained very competitive results for all tested instances, if not better, when compared to other algorithms using lower computational times.
Cca 2012 Computer and Applications Proceedings of the 2012 International Conference on Computer Applications, 2012
The ubiquity of the Internet and Web has led to the emergency of several Web search engines with ... more The ubiquity of the Internet and Web has led to the emergency of several Web search engines with varying capabilities. A weakness of existing search engines is the very extensive amount of hits that they can produce. Moreover, only a small number of web users actually know how to utilize the true power of Web search engines. Therefore, there is a need for searching infrastructure to help ease and guide the searching efforts of web users toward their desired objectives. In this paper, we propose a context-based metasearch engine and discuss its implementation on top of the actual Google.com search engine. The proposed meta-search engine benefits the user the most when the user does not know what exact document he or she is looking for. Comparison of the context-based meta-search engine with both Google and Guided Google shows that the results returned by context-based meta-search engine is much more intuitive and accurate than the results returned by both Google and Guided Google.
Evidence-Based Complementary and Alternative Medicine, 2016
The clinical efficacy and safety of Shiunko ointment (phase II clinical trial) was investigated i... more The clinical efficacy and safety of Shiunko ointment (phase II clinical trial) was investigated in 40 Ethiopian patients with cutaneous leishmaniasis. Patients were randomized to receive treatment with Shiunko ointment or placebo (n=20, each), applied on the lesion twice a day for 4 weeks. Clinicoparasitological assessments were performed before treatment, weekly for 4 weeks, and then 4, 8, and 12 weeks after the end of treatment. A marked reduction in lesion size was observed on week 16 of treatment in the Shiunko compared with placebo group (69% and 22% reduction, resp.). The overall rate of lesion reduction during the four weeks of treatment was significantly faster in the Shiunko group. Shiunko provided significant effect on wound closure in patients with ulcerated lesion. The clinical efficacy and tolerability of Shiunko were comparable to placebo with regard to its clinicoparasitological response (cure rate and parasitological clearance). Results of this preliminary study may ...
International Journal of Trust Management in Computing and Communications, 2015
In electronic commerce (e-commerce) environment, trust management has been identified as vital co... more In electronic commerce (e-commerce) environment, trust management has been identified as vital component for establishing and maintaining successful relational exchanges between the trading partners. As trust management systems depend on the feedbacks provided by the trading partners, they are fallible to strategic manipulation of the rating attacks. Therefore, in order to improve the reliability of the trust management systems, an approach that addresses feedback-related vulnerabilities is paramount. This paper proposes an approach for identifying and actioning of falsified feedbacks to make trust management systems robust against rating manipulation attacks. The viability of the proposed approach is studied experimentally and the results of various simulation experiments show that the proposed approach can be highly effective in identifying falsified feedbacks.
2013 12th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, 2013
ABSTRACT In this paper, an approach for profiling email-born phishing activities is proposed. Pro... more ABSTRACT In this paper, an approach for profiling email-born phishing activities is proposed. Profiling phishing activities are useful in determining the activity of an individual or a particular group of phishers. By generating profiles, phishing activities can be well understood and observed. Typically, work in the area of phishing is intended at detection of phishing emails, whereas we concentrate on profiling the phishing email. We formulate the profiling problem as a clustering problem using the various features in the phishing emails as feature vectors. Further, we generate profiles based on clustering predictions. These predictions are further utilized to generate complete profiles of these emails. The performance of the clustering algorithms at the earlier stage is crucial for the effectiveness of this model. We carried out an experimental evaluation to determine the performance of many classification algorithms by incorporating clustering approach in our model. Our proposed profiling email-born phishing algorithm (ProEP) demonstrates promising results with the RatioSize rules for selecting the optimal number of clusters.
Autonomic middleware services will play an important role in the management of resources and dist... more Autonomic middleware services will play an important role in the management of resources and distributed workloads in emerging distributed computing environments. In this paper, we address the problem of autonomic grid resource scheduling and propose a scheduling infrastructure that is capable of self-management in the face of dynamic behavior inherent to this kind of systems.
This article is devoted to an empirical investigation of performance of several new large multi-t... more This article is devoted to an empirical investigation of performance of several new large multi-tier ensembles for the detection of cardiac autonomic neuropathy (CAN) in diabetes patients using subsets of the Ewing features. We used new data collected by the diabetes screening research initiative (DiScRi) project, which is more than ten times larger than the data set originally used by Ewing in the investigation of CAN. The results show that new multi-tier ensembles achieved better performance compared with the outcomes published in the literature previously. The best accuracy 97.74% of the detection of CAN has been achieved by the novel multi-tier combination of AdaBoost and Bagging, where AdaBoost is used at the top tier and Bagging is used at the middle tier, for the set consisting of the following four Ewing features: the deep breathing heart rate change, the Valsalva manoeuvre heart rate change, the hand grip blood pressure change and the lying to standing blood pressure change.
Proceedings of the 1st International Conference on Cloud Computing and Services Science, 2011
We consider a cloud data storage involving three entities, the cloud customer, the cloud business... more We consider a cloud data storage involving three entities, the cloud customer, the cloud business centre which provides services, and the cloud data storage centre. Data stored in the data storage centre comes from a variety of customers and some of these customers may compete with each other in the market place or may own data which comprises confidential information about their own clients. Cloud staff have access to data in the data storage centre which could be used to steal identities or to compromise cloud customers. In this paper, we provide an efficient method of data storage which prevents staff from accessing data which can be abused as described above. We also suggest a method of securing access to data which requires more than one staff member to access it at any given time. This ensures that, in case of a dispute, a staff member always has a witness to the fact that she accessed data.
2009 10th International Symposium on Pervasive Systems, Algorithms, and Networks, 2009
Abstract Protecting user's mailbox from infiltration of phishing email is a sign... more Abstract Protecting user's mailbox from infiltration of phishing email is a significant research issue now a day. Many researches are going on filtering phishing using classification based algorithms and achieve substantial performance. It has been studied and investigated with ...
Dark Web is one of the most challenging and untraceable mediums adopted by the cyber criminals, t... more Dark Web is one of the most challenging and untraceable mediums adopted by the cyber criminals, terrorists, and state-sponsored spies to fulfil their illicit motives. Cyber-crimes happening inside the Dark Web are alike the real world crimes. However, the sheer size, unpredictable ecosystem and anonymity provided by the Dark Web services are the essential confrontations to trace the criminals. To discover the potential solutions towards cyber-crimes evaluating the sailing Dark Web crime threats is a crucial step. In this paper, we will appraise the Dark Web by analysing the crimes with their consequences and enforced methods as well as future manoeuvres to lessen the crime threats. We used Systematic Literature Review (SLR) method with the aspiration to provide the direction and aspect of emerging crime threats in the Dark Web for the researchers and specialist in Cyber security field. For this SLR 65 most relevant articles from leading electronic databases were selected for data extraction and synthesis to answer our predefined research questions. The result of this systematic literature review provides (i) comprehensive knowledge on the growing crimes proceeding with Dark Web (ii) assessing the social, economic and ethical impacts of the cyber-crimes happening inside the Dark Web and (iii) analysing the challenges, established techniques and methods to locate the criminals and their drawbacks. Our study reveals that more in depth researches are required to identify criminals in the Dark Web with new prominent way, the crypto markets and Dark Web discussion forums analysis is crucial for forensic investigations, the anonymity provided by Dark Web services can be used as a weapon to catch the criminals and digital evidences should be analysed and processed in a way that follows the law enforcement to make the seizure of the criminals and shutting down the illicit sites in the Dark Web. INDEX TERMS Crypto market, cyber crime, dark web, onion router.
Algorithms and Architectures for Parallel Processing, 2018
With the development of big data, a demand for data analysis keeps increasing. This requirement h... more With the development of big data, a demand for data analysis keeps increasing. This requirement has prompted a need for data-aware task scheduling approach that can simultaneously schedule various tasks such as batched tasks and real-time tasks in a data center efficiently. To this end, we propose a hybrid task scheduling strategy coupled with data migration in data center. Firstly, we translate the task scheduling problem into task selection problem, and give methods of selecting batched tasks and real-time tasks respectively. Then the method for scheduling both batched tasks and real-time tasks is introduced in detail. Finally, we integrate data migration into the hybrid scheduling strategy. Experimental results show that, compared to the traditional FIFO algorithm, the proposed task scheduling strategy greatly improves the data locality and data migration performs very well on reducing the job execution time. Our algorithm also guarantees an acceptable fairness for tasks.
International Journal of Building Pathology and Adaptation, 2020
PurposeThis research paper adopts the fundamental tenets of advanced technologies in industry 4.0... more PurposeThis research paper adopts the fundamental tenets of advanced technologies in industry 4.0 to monitor the structural health of concrete beam members using cost-effective non-destructive technologies. In so doing, the work illustrates how a coalescence of low-cost digital technologies can seamlessly integrate to solve practical construction problems.Design/methodology/approachA mixed philosophies epistemological design is adopted to implement the empirical quantitative analysis of “real-time” data collected via sensor-based technologies streamed through a Raspberry Pi and uploaded onto a cloud-based system. Data was analysed using a hybrid approach that combined both vibration-characteristic-based method and linear variable differential transducers (LVDT).FindingsThe research utilises a novel digital research approach for accurately detecting and recording the localisation of structural cracks in concrete beams. This non-destructive low-cost approach was shown to perform with ...
H1/IC31® is a tuberculosis (TB) subunit vaccine candidate consisting of the fusion protein of Ag8... more H1/IC31® is a tuberculosis (TB) subunit vaccine candidate consisting of the fusion protein of Ag85B and ESAT-6 (H1) formulated with the IC31® adjuvant. Previous trials have reported on the H1/IC31® vaccine in M. tuberculosis (Mtb)-naïve, BCG-vaccinated and previously Mtb-infected individuals. In this trial, conducted between December 2008 and April 2010, the safety and immunogenicity of H1/IC31® was assessed in participants living in Ethiopia - a highly TB-endemic area. Healthy male participants aged 18-25 years were recruited into four groups. Participants in group 1 (N = 12) and group 2 (N = 12) were Tuberculin Skin Test (TST) negative and QuantiFERON-TB Gold in-tube test (QFT) negative (Mtb-naïve groups), participants in group 3 (N = 3) were TST positive and QFT negative (BCG group), and participants in group 4 (N = 12) were both TST and QFT positive (Mtb-infected group). H1 vaccine alone (group 1) or H1 formulated with the adjuvant IC31® (groups 2, 3 and 4) was administered intr...
IEEE Transactions on Evolutionary Computation, 2017
Evolutionary algorithms (EAs) have recently been suggested as a candidate for solving big data op... more Evolutionary algorithms (EAs) have recently been suggested as a candidate for solving big data optimization problems that involve a very large number of variables and need to be analyzed in a short period of time. However, EAs face a scalability issue when dealing with big data problems. Moreover, the performance of EAs critically hinges on the utilized parameter values and operator types, thus it is impossible to design a single EA that can outperform all others in every problem instance. To address these challenges, we propose a heterogeneous framework that integrates a cooperative co-evolution method with various types of memetic algorithms. We use the cooperative co-evolution method to split the big problem into subproblems in order to increase the efficiency of the solving process. The subproblems are then solved using various heterogeneous memetic algorithms. The proposed heterogeneous framework adaptively assigns, for each solution, different operators, parameter values and a local search algorithm to efficiently explore and exploit the search space of the given problem instance. The performance of the proposed algorithm is assessed using the Big Data 2015 competition benchmark problems that contain data with and without noise. Experimental results demonstrate that the proposed algorithm, with the cooperative co-evolution method, performs better than without the cooperative co-evolution method. Furthermore, it obtained very competitive results for all tested instances, if not better, when compared to other algorithms using lower computational times.
Cca 2012 Computer and Applications Proceedings of the 2012 International Conference on Computer Applications, 2012
The ubiquity of the Internet and Web has led to the emergency of several Web search engines with ... more The ubiquity of the Internet and Web has led to the emergency of several Web search engines with varying capabilities. A weakness of existing search engines is the very extensive amount of hits that they can produce. Moreover, only a small number of web users actually know how to utilize the true power of Web search engines. Therefore, there is a need for searching infrastructure to help ease and guide the searching efforts of web users toward their desired objectives. In this paper, we propose a context-based metasearch engine and discuss its implementation on top of the actual Google.com search engine. The proposed meta-search engine benefits the user the most when the user does not know what exact document he or she is looking for. Comparison of the context-based meta-search engine with both Google and Guided Google shows that the results returned by context-based meta-search engine is much more intuitive and accurate than the results returned by both Google and Guided Google.
Evidence-Based Complementary and Alternative Medicine, 2016
The clinical efficacy and safety of Shiunko ointment (phase II clinical trial) was investigated i... more The clinical efficacy and safety of Shiunko ointment (phase II clinical trial) was investigated in 40 Ethiopian patients with cutaneous leishmaniasis. Patients were randomized to receive treatment with Shiunko ointment or placebo (n=20, each), applied on the lesion twice a day for 4 weeks. Clinicoparasitological assessments were performed before treatment, weekly for 4 weeks, and then 4, 8, and 12 weeks after the end of treatment. A marked reduction in lesion size was observed on week 16 of treatment in the Shiunko compared with placebo group (69% and 22% reduction, resp.). The overall rate of lesion reduction during the four weeks of treatment was significantly faster in the Shiunko group. Shiunko provided significant effect on wound closure in patients with ulcerated lesion. The clinical efficacy and tolerability of Shiunko were comparable to placebo with regard to its clinicoparasitological response (cure rate and parasitological clearance). Results of this preliminary study may ...
International Journal of Trust Management in Computing and Communications, 2015
In electronic commerce (e-commerce) environment, trust management has been identified as vital co... more In electronic commerce (e-commerce) environment, trust management has been identified as vital component for establishing and maintaining successful relational exchanges between the trading partners. As trust management systems depend on the feedbacks provided by the trading partners, they are fallible to strategic manipulation of the rating attacks. Therefore, in order to improve the reliability of the trust management systems, an approach that addresses feedback-related vulnerabilities is paramount. This paper proposes an approach for identifying and actioning of falsified feedbacks to make trust management systems robust against rating manipulation attacks. The viability of the proposed approach is studied experimentally and the results of various simulation experiments show that the proposed approach can be highly effective in identifying falsified feedbacks.
2013 12th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, 2013
ABSTRACT In this paper, an approach for profiling email-born phishing activities is proposed. Pro... more ABSTRACT In this paper, an approach for profiling email-born phishing activities is proposed. Profiling phishing activities are useful in determining the activity of an individual or a particular group of phishers. By generating profiles, phishing activities can be well understood and observed. Typically, work in the area of phishing is intended at detection of phishing emails, whereas we concentrate on profiling the phishing email. We formulate the profiling problem as a clustering problem using the various features in the phishing emails as feature vectors. Further, we generate profiles based on clustering predictions. These predictions are further utilized to generate complete profiles of these emails. The performance of the clustering algorithms at the earlier stage is crucial for the effectiveness of this model. We carried out an experimental evaluation to determine the performance of many classification algorithms by incorporating clustering approach in our model. Our proposed profiling email-born phishing algorithm (ProEP) demonstrates promising results with the RatioSize rules for selecting the optimal number of clusters.
Autonomic middleware services will play an important role in the management of resources and dist... more Autonomic middleware services will play an important role in the management of resources and distributed workloads in emerging distributed computing environments. In this paper, we address the problem of autonomic grid resource scheduling and propose a scheduling infrastructure that is capable of self-management in the face of dynamic behavior inherent to this kind of systems.
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Papers by Jemal Hussein