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Security is one of the top concerns of any enterprise. Most security practitioners in enterprises rely on correlation rules to detect potential threats. While the rules are intuitive to design, each rule is independently defined per log source, unable to collectively address heterogeneity of data from a myriad of enterprise networking and security logs. Furthermore, correlation rules do not look for...
Countering network threats, particularly intrusions, is a challenging area of research in the field of information security. Intruders use sophisticated mechanisms to hide the attack payload and break the detection techniques. To overcome that, various unsupervised learning approaches from the field of machine learning and pattern recognition have been employed. The most popularly used method is Principal...
This study investigated the effectiveness of e-learning and blended learning for airport security officers (screeners) aimed at increasing their detection of novel prohibited items in X-ray images of passenger bags. 80 screeners from a large European airport conducted a simulated X-ray baggage screening task (SXBST). Based on hit- and false alarm rates, d-prime, age, gender and job experience, four...
Smartphone ecosystems are considered as a unique source due to the large number of apps which in turn makes an extensive use of personal data. Currently, there is no privacy and security preservation mechanism in smartphone ecosystems to enable users to compare apps in terms of privacy and security protection level, and to alarm them regarding the invasive issues (in terms of privacy and security)...
Machine learning has become one of the go-to methods for solving problems in the field of networking. This development is driven by data availability in large-scale networks and the commodification of machine learning frameworks. While this makes it easier for researchers to implement and deploy machine learning solutions on networks quickly, there are a number of vital factors to account for when...
The mitigation of insider threats against databases is a challenging problem as insiders often have legitimate access privileges to sensitive data. Therefore, conventional security mechanisms, such as authentication and access control, may be insufficient for the protection of databases against insider threats and need to be complemented with techniques that support real-time detection of access anomalies...
Deep learning techniques have demonstrated the ability to perform a variety of object recognition tasks using visible imager data; however, deep learning has not been implemented as a means to autonomously detect and assess targets of interest in a physical security system. We demonstrate the use of transfer learning on a convolutional neural network (CNN) to significantly reduce training time while...
Industrial Control System (ICS) is used to monitor and control critical infrastructures. Programmable logic controllers (PLCs) are major components of ICS, which are used to form automation system. It is important to protect PLCs from any attacks and undesired incidents. However, it is not easy to apply traditional tools and techniques to PLCs for security protection and forensics because of its unique...
In 2013, Tams et al. proposed a method to determine directed reference points in fingerprints based on a mathematical model of typical orientation fields of tented arch type fingerprints. Although this Tented Arch Reference Point (TARP) method has been used successfully for pre-alignment in biometric cryptosystems, its accuracy does not yet ensure satisfactory error rates for single finger systems...
Existing work on identifying security requirements relies on training binary classification models using domain-specific data sets to achieve a high accuracy. Considering that domain-specific data sets are often not readily available, we propose a domain-independent model for classifying security requirements based on two key ideas. First, we train our model on the description of weaknesses from the...
In this paper, we take up the second RE17 data challenge: the identification of requirements types using the "Quality attributes (NFR)" dataset provided. We studied how accurately we can automatically classify requirements as functional (FR) and non-functional (NFR) in the dataset with supervised machine learning. Furthermore, we assessed how accurately we can identify various types of NFRs,...
For measuring and creating a complex physical protection system of a facility, it is important to take into consideration its characteristics not only inside the fence, but it is inevitable to examine, classify its surrounding objects as well. In other words, it is necessary to evaluate risk factors lying outside accurately in the light of risk analysis. The security leader broadens the knowledge...
The continuing success of synchrophasors has ushered in new subdomains of power system applications for real-time situational awareness, online decision support, and robust system control. In this paper, an adaptive decision-tree-based systematic method for open-loop regional voltage control is developed. This approach employs voltage security assessment method to generate voltage secure and insecure...
Machine learning has been a detection technique used by many security vendors for some time now. With the enhancement brought by GPUs, many security products can now use different deep learning methods and forms of neural networks for malware classification. However, these new methods, as powerful as they are, are also limited by the amount of memory a GPU has or by the constant need of transferring...
In recent years, there has been a growing interest in the modelling of crime commission processes, in particular crime scripting, in physical and cyber spaces. This article aims to demonstrate the limits of unstructured scripting approaches, and advocates the development of more systematic techniques. For this, we examined he differences and similarities between various scripts. Twenty-one participants...
This paper presents a method to analyse the various identities of a user and thus determine if any synthetic identity theft has been committed. Here three type of data is taken i.e., Input dataset (X), Normal dataset (Y) and Target Dataset (Z) are taken. The various identities used may be text or string data such as Candidate's Name, Date of Birth, Time of Birth Place of Birth, Home Address, Father's...
Network infrastructures are in jeopardy of suffering nowadays since a number of attacks have been developed and grown up enormously. In order to get rid of such security threats, a defense mechanism is much sought-after. This paper proposes an improved model of intrusion detection by using two-level classifier ensemble. The proposed model is made up of a PSO-based feature selection technique and a...
With the rapid development of mobile Internet, android system becomes the absolute overlord of the operating system, which has an unparalleled influence to the smart phone industry, but also closely related with people's lives. However, the feature of open source and lacking of regulatory of Android system led to a lot of security risks. Because of the widespread use of Android Intent Mechanism, the...
According to the second national sample survey of disabled people, the number of disabled people reaches 82,960,000 in China, which accounts 6.34% of the total population In the same year, the number of disabled people from Beijing is 999,000, which accounts for 6.49% of all populations of the city. If calculated according to the proportion, the number of people of disabled people would be reach 1,409,000...
Surveillance systems play a critical role in security and surveillance. A surveillance system with cameras that work in the visible spectrum is sufficient for most cases. However, problems may arise during the night, or in areas with less than ideal illumination conditions. Cameras with thermal infrared technology can be a better option in these situations since they do not rely on illumination to...
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