Now showing 1 - 10 of 29
  • Publication
    MPM Job Scheduling Problem: a bi-objective approach
    (United Kingdom Simulation Society, 2013-02) ; ;
    This paper presents a Recurrent Neural Network approach for the multi purpose machines Job Shop Scheduling Problem. This case of JSSP can be utilized for the modelling of project portfolio management besides the well known adoption in factory environment. Therefore, each project oriented organization develops a set of projects and it has to schedule them as a whole. In this work, we extended a bi-objective system model based on the JSSP modelling and formulate dit as a combination of two recurrent neural networks. In addition, we designed an example within its neural networks that are focused on the Make span and the Total Weighted Tardiness objectives. Moreover, we present the findings of our approach using a set of well known benchmark instances and the discussion about them and the singularity that arises
      177
  • Publication
    A Cloud Forensic Readiness Model for Service Level Agreements Management
    (Academic Conferences and Publishing International Limited, 2015-07-03) ; ;
    Cloud computing is increasingly becoming a target of cyber-criminal attacks. Often the committedcrimes violate the Service Level Agreement (SLA) contracts, which must be respected by all the involvedparties. Cloud Forensics is a branch of Digital Forensic discipline dealing with crimes involving the Cloud. Amanner for leveraging some of the attacks is the provisioning of a Forensic Readiness capability, by performingsome activities before the crimes happen. In this paper we introduce a model aimed to represent themanagement of SLAs through a cloud system.
      395
  • Publication
    Virtual Machine Forensics by means of Introspection and Kernel Code Injection
    Virtual Machine Introspection offers the ability to access a virtual machine remotely and extract informationfrom it. Virtual machine introspection allows all processes, local data, and network traffic to be tracked andmade available to the investigation process. These properties offer the possibility to monitor a suspect virtualmachine (VM). Moreover, the access to a VM data is far from being trivial; there are various complex tasks tobe dealt with. For instance the returned data is in a raw format, and it is necessary to remap into a userfriendly representation (canonical representation). In this paper we propose a method of bridging thissemantic gap, and provide a graphical reconstruction of events. This proposal is essentially, the recreation ofa virtual machine at a remote location and the subsequent recreation of all processes, data, network traffic ina virtual machine as they occur in the original. This should be achieved in real-time, which will give anopportunity to quickly make decisions based on the evidence as we collect them in real-time. Our approachinvolves recreating a virtual machine and injecting into it all code and data within the original virtual machine,presenting an identical copy for examination. The approach proposed also has another advantage byallowing all data to be saved for further analysis and verification.
      548
  • Publication
    Prediction of NB-UVB phototherapy treatment response of psoriasis patients using data mining
    NB-UVB Phototherapy is one of the most commontreatments administrated by dermatologists for psoriasis patients.Although in general, the treatment results in improving thecondition, it also can worsen it. If a model can predict thetreatment response before hand, the dermatologists can adjustthe treatment accordingly. In this paper, we use data miningtechniques and conduct four experiments. The best performanceof all four experiments was obtained by the stacked classifiermade of hyper parameter tuned Random Forest, kSVM and ANNbase learners, learned using L1-Regularized Logistic Regressionsuper learner.
      472
  • Publication
    Distributed Clustering Algorithm for Spatial Data Mining
    Distributed data mining techniques and mainly distributed clustering are widely used in last decade because they deal with very large and heterogeneous datasets which cannot be gathered centrally. Current distributed clustering approaches are normally generating global models by aggregating local results that are obtained on each site. While this approach analyses the datasets on their locations the aggregation phase is complex, time consuming and may produce incorrect and ambiguous global clusters and therefore incorrect knowledge. In this paper we propose a new clustering approach for very large spatial datasets that are heterogeneous and distributed. The approach is based on K-means Algorithm but it generates the number of global clusters dynamically. It is not necessary to fix the number of clusters. Moreover, this approach uses a very sophisticated aggregation phase. The aggregation phase is designed in such away that the final clusters are compact and accurate while the overall process is efficient in time and memory allocation. Preliminary results show that the proposed approach scales up well in terms of running time, and result quality, we also compared it to two other clustering algorithms BIRCH and CURE and we show clearly this approach is much more efficient than the two algorithms.
      1092
  • Publication
    Smartphone Forensic Analysis: A Case Study for Obtaining Root Access of an Android Samsung S3 Device and Analyse the Image without an Expensive Commercial Tool
    (Scientific Research Publishing, 2014) ; ;
    Smartphone is a very useful and compact device that fits in persons pocket, but at the same time itcan be used as a tool for criminal activities. In this day and age, people increasingly rely on smartphones rather than desktop computers or laptops to exchange messages, share videos and audiomessages. A smartphone is almost equivalent in its application to a PC, hence there are securityrisks associated with its use such as carrying out a digital crime or becoming a victim of one. Criminalscan use smartphones for a number of activities. Namely, committing a fraud over e-mail,harassment via text messages, drug trafficking, child pornography, communications related to narcotics,etc. It is a great challenge for forensic experts to extract data from a smartphone for forensic purposes that can be used as evidence in the court of law. In this case study, I show how to obtain the root access of Samsung S3 phone, how to create DD image and then how to examine DD image via commercial tool like UFED physical analyzer trial version which doesnt support Android devices. I will extract the messages for Viber on trial version of UFED Physical analyzer.
      1874
  • Publication
    Data Mining Techniques Applied to Wireless Sensor Networks for Early Forest Fire Detection
    Nowadays, forest fires are a serious threat to the environment and human life. The monitoring system for forest fires should be able to make a real-time monitoring of the target region and the early detection of fire threats. In this paper, we propose a new approach based on the integration of Data Mining techniques into sensor nodes for forest fire detection. This approach is based on the clustered WSN where each sensor node will individually decide on detecting fire using a classifier of Data Mining techniques. When a fire is detected, the correspondent node will send an alert through its cluster-head which will pass through gateways and other cluster-heads until it will reach the sink in order to inform the firefighters. We use the CupCarbon simulator to validate and evaluate our proposed approach. Through extensive simulation experiments, we show that our approach can provide a fast reaction to forest fires while consuming energy efficiently.
    Scopus© Citations 24  1044
  • Publication
    The State of the Art Forensic Techniques in Mobile Cloud Environment: A Survey, Challenges and Current Trends
    Smartphones have become popular in recent days due to the accessibility of a wide range of applications.These sophisticated applications demand more computing resources in a resource constraint smartphone.Cloud computing is the motivating factor for the progress of these applications. The emerging mobile cloud computing introduces a new architecture to offload smartphone and utilize cloud computing technology to solve resource requirements. The popularity of mobile cloud computing is an opportunity for misuse and unlawful activities. Therefore, it is a challenging platform for digital forensic investigations due to the non availabilityof methodologies, tools and techniques. The aim of this work is to analyze the forensic tools and methodologies for crime investigation in a mobile cloud platform as it poses challenges in proving the evidence.
    Scopus© Citations 25  852
  • Publication
    Efficiency of Network Event logs as Admissible Digital Evidence
    The large number of event logs generated in atypical network is increasingly becoming an obstacle for forensicinvestigators to analyze and use to detect and verify maliciousactivities. Research in the area of network forensics is trying toaddress the challenge of using network logs to reconstruct attackscenarios by proposing events correlation models. In this paperwe introduce and examine a new network forensics model thatmakes network event-logs admissible in the court of low. The ideaof our model is to collect available logs from connected networkdevices and then apply Support Vectors Machine (SVMs) in orderto filter out anomaly intrusion, and re-route these logs to a centralrepository where a event-logs management functions are applied.
    Scopus© Citations 3  479
  • Publication
    Automatic Timeline Construction For Computer Forensics Purposes
    (Institute of Electrical and Electronics Engineers, 2014-09) ; ; ;
    To determine the circumstances of an incident, investigators need to reconstruct events that occurred in the past. The large amount of data spread across the crime scene makes this task very tedious and complex. In particular, the analysis of the reconstructed timeline, due to the huge quantity of events that occurred on a digital system, is almost impossible and leads to cognitive overload. Therefore, it becomes more and more necessary to develop automatic tools to help or even replace investigators in some parts of the investigation. This paper introduces a multi-layered architecture designed to assist the investigative team in the extraction of information left in the crime scene, the construction of the timeline representing the incident and the interpretation of this latter.
    Scopus© Citations 13  500