Biblio
In this paper, we present an extensive evaluation of face recognition and verification approaches performed by the European COST Action MULTI-modal Imaging of FOREnsic SciEnce Evidence (MULTI-FORESEE). The aim of the study is to evaluate various face recognition and verification methods, ranging from methods based on facial landmarks to state-of-the-art off-the-shelf pre-trained Convolutional Neural Networks (CNN), as well as CNN models directly trained for the task at hand. To fulfill this objective, we carefully designed and implemented a realistic data acquisition process, that corresponds to a typical face verification setup, and collected a challenging dataset to evaluate the real world performance of the aforementioned methods. Apart from verifying the effectiveness of deep learning approaches in a specific scenario, several important limitations are identified and discussed through the paper, providing valuable insight for future research directions in the field.
Modern vehicles in Intelligent Transportation Systems (ITS) can communicate with each other as well as roadside infrastructure units (RSUs) in order to increase transportation efficiency and road safety. For example, there are techniques to alert drivers in advance about traffic incidents and to help them avoid congestion. Threats to these systems, on the other hand, can limit the benefits of these technologies. Securing ITS itself is an important concern in ITS design and implementation. In this paper, we provide a security model of ITS which extends the classic layered network security model with transportation security and information security, and gives a reference for designing ITS architectures. Based on this security model, we also present a classification of ITS threats for defense. Finally a proof-of-concept example with malicious nodes in an ITS system is also given to demonstrate the impact of attacks. We analyzed the threat of malicious nodes and their effects to commuters, like increasing toll fees, travel distances, and travel times etc. Experimental results from simulations based on Veins shows the threats will bring about 43.40% more total toll fees, 39.45% longer travel distances, and 63.10% more travel times.
In this paper we solve the problem of neural network technology development for e-mail messages classification. We analyze basic methods of spam filtering such as a sender IP-address analysis, spam messages repeats detection and the Bayesian filtering according to words. We offer the neural network technology for solving this problem because the neural networks are universal approximators and effective in addressing the problems of classification. Also, we offer the scheme of this technology for e-mail messages “spam”/“not spam” classification. The creation of effective neural network model of spam filtering is performed within the databases knowledge discovery technology. For this training set is formed, the neural network model is trained, its value and classifying ability are estimated. The experimental studies have shown that a developed artificial neural network model is adequate and it can be effectively used for the e-mail messages classification. Thus, in this paper we have shown the possibility of the effective neural network model use for the e-mail messages filtration and have shown a scheme of artificial neural network model use as a part of the e-mail spam filtering intellectual system.
This paper describes the technology of neural network application to solve the problem of information security incidents forecasting. We describe the general problem of analyzing and predicting time series in a graphical and mathematical setting. To solve this problem, it is proposed to use a neural network model. To solve the task of forecasting a time series of information security incidents, data are generated and described on the basis of which the neural network is trained. We offer a neural network structure, train the neural network, estimate it's adequacy and forecasting ability. We show the possibility of effective use of a neural network model as a part of an intelligent forecasting system.
A database is an organized collection of data. Though a number of techniques, such as encryption and electronic signatures, are currently available for the protection of data when transmitted across sites. Database security refers to the collective measures used to protect and secure a database or database management software from illegitimate use and malicious threats and attacks. In this paper, we create 6 types of method for more secure ways to store and retrieve database information that is both convenient and efficient. Confidentiality, integrity, and availability, also known as the CIA triad, is a model designed to guide policies for information security within the database. There are many cryptography techniques available among them, ECC is one of the most powerful techniques. A user wants to the data stores or request, the user needs to authenticate. When a user who is authenticated, he will get key from a key generator and then he must be data encrypt or decrypt within the database. Every keys store in a key generator and retrieve from the key generator. We use 256 bits of AES encryption for rows level encryption, columns level encryption, and elements level encryption for the database. Next two method is encrypted AES 256 bits random key by using 521 bits of ECC encryption and signature for rows level encryption and column level encryption. Last method is most secure method in this paper, which method is element level encryption with AES and ECC encryption for confidentiality and ECC signature use for every element within the database for integrity. As well as encrypting data at rest, it's also important to ensure confidential data are encrypted in motion over our network to protect against database signature security. The advantages of elements level are difficult for attack because the attacker gets a key that is lose only one element. The disadvantages need to thousands or millions of keys to manage.
We consider transmissions of secure messages over a burst erasure wiretap channel under decoding delay constraint. For block codes we introduce and study delay optimal secure burst erasure correcting (DO-SBE) codes that provide perfect security and recover a burst of erasures of a limited length with minimum possible delay. Our explicit constructions of DO-SBE block codes achieve maximum secrecy rate. We also consider a model of a burst erasure wiretap channel for the streaming setup, where in any sliding window of a given size, in a stream of encoded source packets, the eavesdropper is able to observe packets in an interval of a given size. For that model we obtain an information theoretic upper bound on the secrecy rate for delay optimal streaming codes. We show that our block codes can be used for construction of delay optimal burst erasure correcting streaming codes which provide perfect security and meet the upper bound for a certain class of code parameters.
The network coding optimization based on niche genetic algorithm can observably reduce the network overhead of encoding technology, however, security issues haven't been considered in the coding operation. In order to solve this problem, we propose a network coding optimization scheme for niche algorithm based on security performance (SNGA). It is on the basis of multi-target niche genetic algorithm(NGA)to construct a fitness function which with k-secure network coding mechanism, and to ensure the realization of information security and achieve the maximum transmission of the network. The simulation results show that SNGA can effectively improve the security of network coding, and ensure the running time and convergence speed of the optimal solution.
The method of assessment of degree of compliance of divisions of the complex distributed corporate information system to a number of information security indicators is offered. As a result of the methodology implementation a comparative assessment of compliance level of each of the divisions for the corporate information security policy requirements may be given. This assessment may be used for the purpose of further decision-making by the management of the corporation on measures to minimize risks as a result of possible implementation of threats to information security.
In this research paper author surveys the need of data protection from intelligent systems in the private and public sectors. For this, she identifies that the Smart Information Security Intel processes needs to be the suggestive key policy for both sectors of governance either public or private. The information is very sensitive for any organization. When the government offices are concerned, information needs to be abstracted and encapsulated so that there is no information stealing. For this purposes, the art of skill set and new optimized technology needs to be stationed. Author identifies that digital bar-coded air port like security using conveyor belts and digital bar-coded conveyor boxes to scan switched ON articles like internet of things needs to be placed. As otherwise, there can potentially be data, articles or information stealing from the operational sites where access is unauthorized. Such activities shall need to be scrutinized, minutely. The biometric such as fingerprints, iris, voice and face recognition pattern updates in the virtual data tables must be taken to keep data entry-exit log up to-date. The information technicians of the sentinel systems must help catch the anomalies in the professional working time in private and public sectors if there is red flag as indicator. The author in this research paper shall discuss in detail what we shall station, how we shall station and what all measures we might need to undertake to safeguard the stealing of sensitive information from the organizations like administration buildings, government buildings, educational schools, hospitals, courts, private buildings, banks and all other offices nation-wide. The TO-BE new processes shall make the AS-IS office system more information secured, data protected and personnel security stronger.
The problems of random numbers application to the information security of data, communication lines, computer units and automated driving systems are considered. The possibilities for making up quantum generators of random numbers and existing solutions for acquiring of sufficiently random sequences are analyzed. The authors found out the method for the creation of quantum generators on the basis of semiconductor electronic components. The electron-quantum generator based on electrons tunneling is experimentally demonstrated. It is shown that it is able to create random sequences of high security level and satisfying known NIST statistical tests (P-Value\textbackslashtextgreater0.9). The generator created can be used for formation of both closed and open cryptographic keys in computer systems and other platforms and has great potential for realization of random walks and probabilistic computing on the basis of neural nets and other IT problems.
Disaster is an unexpected event in a system lifetime, which can be made by nature or even human errors. Disaster recovery of information technology is an area of information security for protecting data against unsatisfactory events. It involves a set of procedures and tools for returning an organization to a state of normality after an occurrence of a disastrous event. So the organizations need to have a good plan in place for disaster recovery. There are many strategies for traditional disaster recovery and also for cloud-based disaster recovery. This paper focuses on using cloud-based disaster recovery strategies instead of the traditional techniques, since the cloud-based disaster recovery has proved its efficiency in providing the continuity of services faster and in less cost than the traditional ones. The paper introduces a proposed model for virtual private disaster recovery on cloud by using two metrics, which comprise a recovery time objective and a recovery point objective. The proposed model has been evaluated by experts in the field of information technology and the results show that the model has ensured the security and business continuity issues, as well as the faster recovery of a disaster that could face an organization. The paper also highlights the cloud computing services and illustrates the most benefits of cloud-based disaster recovery.