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Day to day life is more unsecure as per the hacking is concerned. Our data is not secure because it can be stolen, hacked, destroy, manipulate, password may forget, guess, Card, token, etc. To overcome this problem biometrics is used as a strong authentication system. The person should be present at the time of the instance. Biometric security is challenging task in day to day life because it is difficult...
In last few years human identification is very crucial area in security. Biometric recognition is the best solution over this. This consist of two types biometric systems: namely uni-biometric and multi-biometric systems. In the last eras uni-biotric systems are used for humanoid identification and security purpose. Now days the trends towards multi-biometric systems are used instead of uni-biometric...
Brain is a vital part of our body, without brain can't perform any task. Human beings are termed as an intelligence because of the unique properties of the human brain. When we want to do any activity, it generates the signals. On the basis of brain signal our body act accordingly. The signal pattern of brain to give the instruction to the organs is varies person to person. Therefore, by using single...
The rapid growth of biometric technologies and wide accessibility of capturing devices has resulted in biometric systems becoming increasingly common in different applications. This has led to the introduction of ATMs in countries like Japan that have adapted biometrics, whereby fingerprints are used instead of PINs. Whilst in South Africa, biometrics is still not regulated in financial sectors. South...
The use and deployment of Industrial Control Systems (ICS) have become standard across many industries, though the security of these important systems have not kept pace with their current Internet focused deployment technologies. This technology gap has exposed an exploitable vector for would be attackers as ICS protocols do not have security mechanisms in place to handle Internet connectivity. This...
In graph based extractive summarization the extraction of sentences can be determined by the importance of the words it contains and the association between the sentences. This method considers the word separately. It does not provide association link handling between the words. This paper addresses to what extent the integration of coreference resolution into the summarization process can improve...
Protecting Critical Infrastructures (CIs) against contemporary cyber attacks has become a crucial as well as complex task. Modern attack campaigns, such as Advanced Persistent Threats (APTs), leverage weaknesses in the organization's business processes and exploit vulnerabilities of several systems to hit their target. Although their life-cycle can last for months, these campaigns typically go undetected...
As a number of attacks such as Stuxnet and BlackEnergy targeting the control system of critical infrastructure have happened, the importance of security enhancement for the facilities such as industrial CPS (Cyber Physical System) has emerged. In this paper, by reflecting the characteristics of industrial CPS, we propose a packet diversity-based anomaly detection model which we can learn and conduct...
Although many anti-theft technologies are implemented, auto-theft is still increasing. Also, security vulnerabilities of cars can be used for auto-theft by neutralizing anti-theft system. This keyless auto-theft attack will be increased as cars adopt computerized electronic devices more. To detect auto-theft efficiently, we propose the driver verification method that analyzes driving patterns using...
Malicious Android applications are currently the biggest threat in the scope of mobile security. To cope with their exponential growth and with their deceptive and hideous behaviors, static analysis signature based approaches are not enough to timely detect and tackle brand new threats such as polymorphic and composition malware. This work presents BRIDEMAID, a novel framework for analysis of Android...
With rapid growth of LTE network and Voice-over-LTE(VoLTE), detecting and preventing security threats like Denial of Service attack becomes a necessary and urgent requirement. VoLTE is an voice solution based on Internet Protocol and 4G LTE technology, at the same time exposing many vulnerabilities when using packet-switched network. There are many heavy weighted detection systems using content analysis,...
In this paper, weighted fractional Fourier transform (WFRFT) is employed to safeguard the physical layer (PHY) security of wireless communications. By leveraging the features of WFRFT, we propose a PHY security modulation scheme, which significantly degrades the equivalent signal-to-noise ratio (SNR) of the unauthorized receiver while imposing no impact on the legitimate receiver. With the proposed...
We focus on automatic anomaly detection in SQL databases for security systems. Many logs of database systems, here the Townhall database, contain detailed information about users, like the SQL queries and the response of the database. A database is a list of log instances, where each log instance is a Cartesian product of feature values with an attached anomaly score. All log instances with the anomaly...
In this paper, we present a real-time face recognition system for home security service robot which can be applied to recognize the person's face in front and give a warning when the identity of the person is a stranger. Considering the complexity of the actual situation, there might be some errors causing by the following factors like the angle, the size, the environment and the illumination of the...
In recent years, we have seen huge growth of biometric systems incorporated in devices such as smartphones and security is one of the major concerns. In this work a multi-biometric template protected system is proposed, based on Bloom filers and binarized statistical image features (BSIF). Features are extracted from face and both periocular regions and templates protected using Bloom filters. Score...
Machine learning algorithms are widely used in cyber forensic biometric systems to analyze a subject's truthfulness in an interrogation. An analytical method (rather than experimental) to evaluate the security strength of these systems under potential cyber attacks is essential. In this paper, we formalize a theoretical method for analyzing the immunity of a machine learning based cyber forensic system...
In the Bitcoin network, lack of class labels tend to cause obscurities in anomalous financial behaviour interpretation. To understand fraud in the latest development of the financial sector, a multifaceted approach is proposed. In this paper, Bitcoin fraud is described from both global and local perspectives using trimmed k-means and kd-trees. The two spheres are investigated further through random...
The number of malware applications targeting the Android operating system has significantly increased in recent years. Malicious applications pose a significant threat to Android platform security. We propose ANASTASIA, a system to detect malicious Android applications through statically analyzing applications' behaviors. ANASTASIA provides a more complete coverage of security behaviors when compared...
The world wide web has grown exponentially over the previous decade in terms of its size that is currently over a billion sties, as well as the number of users. In fact, web usage has become pervasive to touch all aspects of our life, economy and education. These rapid advances have also significantly increase the vulnerabilities of websites that are being hacked on a daily basis. According to White...
In this paper, we propose a novel fingerprint learning algorithm based on maximum penalty graph criteria for radiometric identification. The transient signal and preamble signal of emitters are used for fingerprint feature extraction. The proposed algorithm is based on characterizing the interclass separability and discriminative features. It extracts the synthesized output of all the factors that...
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