Biblio
The paper considers the issue of assessing threats to information security in industrial automation and telecommunication systems in order to improve the efficiency of their security systems. A method for determining a quantitative indicator of threats is proposed, taking into account the probabilistic nature of the process of implementing negative impacts on objects of both industrial and telecommunications systems. The factors that contribute and (or) initiate them are also determined, the dependences of the formal definition of the quantitative indicator of threats are obtained. Methods for a quantitative threat assessment as well as the degree of this threat are presented in the form of a mathematical model in order to substantiate and describe the method for determining a threat to industrial automation systems. Recommendations necessary for obtaining expert assessments of negative impacts on the informatisation objects and information security systems counteracting are formulated to facilitate making decisions on the protection of industrial and telecommunication systems.
The use of biometrics in security applications may be vulnerable to several challenges of hacking. Thus, the emergence of cancellable biometrics becomes a suitable solution to this problem. This paper presents a one-way cancellable biometric transform that depends on 3D chaotic maps for face and fingerprint encryption. It aims to avoid cloning of original biometrics and allow the templates used by each user in different applications to be variable. The permutations achieved with the chaotic maps guarantee high security of the biometric templates, especially with the 3D implementation of the encryption algorithm. In addition, the paper presents a hardware implementation for this framework. The proposed algorithm also achieves good performance in the presence of low and moderate levels of noise. An experimental version of the proposed cancellable biometric system has been applied on FPGA model. The obtained results achieve a powerful performance of the proposed cancellable biometric system.
Voice communication is an important need in daily activities whether delivered with or without technology. Telecommunication technology has accommodated this need by providing a wide range of infrastructure, including large varieties of devices used as intermediary and end devices. One of the cellular technologies that is very widely used by the public is GSM (Global System for Mobile), while in the military, trunked radio is still popular. However, the security systems of GSM and trunked radio have limitations. Therefore, this paper proposes a platform to secure voice data over wireless mobile communication by providing end-to-end encryption. This platform is robust to noise, real-time and remains secure. The proposed encryption utilizes multicircular permutations rotated by expanded keys as dynamic keys to scramble the data. We carry out simulations and testbed implementation to prove that application of the proposed method is feasible.
A new approach to micro-Doppler signal analysis is presented in this article. Novel chirp rate estimators in the time-frequency domain were used for this purpose, which provided the chirp rate of micro-Doppler signatures, allowing the classification of objects in the urban environment. As an example verifying the method, a signal from a high-resolution radar with a linear frequency modulated continuous wave (FMCW) recording an echo reflected from a pedestrian was used to validate the proposed algorithms for chirp rate estimation. The obtained results are plotted on saturated accelerograms, giving an additional parameter dedicated for target classification in security systems utilizing radar sensors for target detection.
The recent malware outbreaks have shown that the existing end-point security solutions are not robust enough to secure the systems from getting compromised. The techniques, like code obfuscation along with one or more zero-days, are used by malware developers for evading the security systems. These malwares are used for large-scale attacks involving Advanced Persistent Threats(APT), Botnets, Cryptojacking, etc. Cryptojacking poses a severe threat to various organizations and individuals. We are summarising multiple methods available for the detection of malware.
Attackers create new threats and constantly change their behavior to mislead security systems. In this paper, we propose an adaptive threat detection architecture that trains its detection models in real time. The major contributions of the proposed architecture are: i) gather data about zero-day attacks and attacker behavior using honeypots in the network; ii) process data in real time and achieve high processing throughput through detection schemes implemented with stream processing technology; iii) use of two real datasets to evaluate our detection schemes, the first from a major network operator in Brazil and the other created in our lab; iv) design and development of adaptive detection schemes including both online trained supervised classification schemes that update their parameters in real time and learn zero-day threats from the honeypots, and online trained unsupervised anomaly detection schemes that model legitimate user behavior and adapt to changes. The performance evaluation results show that proposed architecture maintains an excellent trade-off between threat detection and false positive rates and achieves high classification accuracy of more than 90%, even with legitimate behavior changes and zero-day threats.
It is a well-known fact that nowadays access to sensitive information is being performed through the use of a three-tier-architecture. Web applications have become a handy interface between users and data. As database-driven web applications are being used more and more every day, web applications are being seen as a good target for attackers with the aim of accessing sensitive data. If an organization fails to deploy effective data protection systems, they might be open to various attacks. Governmental organizations, in particular, should think beyond traditional security policies in order to achieve proper data protection. It is, therefore, imperative to perform security testing and make sure that there are no holes in the system, before an attack happens. One of the most commonly used web application attacks is by insertion of an SQL query from the client side of the application. This attack is called SQL Injection. Since an SQL Injection vulnerability could possibly affect any website or web application that makes use of an SQL-based database, the vulnerability is one of the oldest, most prevalent and most dangerous of web application vulnerabilities. To overcome the SQL injection problems, there is a need to use different security systems. In this paper, we will use 3 different scenarios for testing security systems. Using Penetration testing technique, we will try to find out which is the best solution for protecting sensitive data within the government network of Kosovo.
Cybersecurity is one of critical issues in modern military operations. In cyber operations, security professionals depend on various information and security systems to mitigate cyber threats through enhanced cyber situational awareness. Cyber situational awareness can give decision makers mission completeness and providing appropriate timely decision support for proactive response. The crucial information for cyber situational awareness can be collected at network boundaries through deep packet inspection with security systems. Regular expression is regarded as a practical method for deep packet inspection that is considering a next generation intrusion detection and prevention, however, it is not commonly used by the reason of its resource intensive characteristics. In this paper, we describe our effort and achievement on regular expression processing capability in real time and an evaluation method with experimental result.
Industrial Control Systems (ICS) which among others are comprised of Supervisory Control and Data Acquisition (SCADA) and Distributed Control Systems (DCS) are used to control industrial processes. ICS have now been connected to other Information Technology (IT) systems and have as a result become vulnerable to Advanced Persistent Threats (APT). APTs are targeted attacks that use zero-day attacks to attack systems. Current ICS security mechanisms fail to deter APTs from infiltrating ICS. An analysis of possible solutions to deter APTs was done. This paper proposes the use of Artificial Immune Systems to secure ICS from APTs.
The number of detected and analyzed Advanced Persistent Threat (APT) campaigns increased over the last years. Two of the main objectives of such campaigns are to maintain long-term access to the environment of the target and to stay undetected. To achieve these goals the attackers use sophisticated and customized techniques for the lateral movement, to ensure that these activities are not detected by existing security systems. During an investigation of an APT campaign all stages of it are relevant to clarify important details like the initial infection vector or the compromised systems and credentials. Most of the currently used approaches, which are utilized within security systems, are not able to detect the different stages of a complex attack and therefore a comprehensive security investigation is needed. In this paper we describe a concept for a Security Investigation Framework (SIF) that supports the analysis and the tracing of multi-stage APTs. The concept includes different automatic and semi-automatic approaches that support the investigation of such attacks. Furthermore, the framework leverages different information sources, like log files and details from forensic investigations and malware analyses, to give a comprehensive overview of the different stages of an attack. The overall objective of the SIF is to improve the efficiency of investigations and reveal undetected details of an attack.
Recently, threat of previously unknown cyber-attacks are increasing because existing security systems are not able to detect them. Past cyber-attacks had simple purposes of leaking personal information by attacking the PC or destroying the system. However, the goal of recent hacking attacks has changed from leaking information and destruction of services to attacking large-scale systems such as critical infrastructures and state agencies. In the other words, existing defence technologies to counter these attacks are based on pattern matching methods which are very limited. Because of this fact, in the event of new and previously unknown attacks, detection rate becomes very low and false negative increases. To defend against these unknown attacks, which cannot be detected with existing technology, we propose a new model based on big data analysis techniques that can extract information from a variety of sources to detect future attacks. We expect our model to be the basis of the future Advanced Persistent Threat(APT) detection and prevention system implementations.
Persisting to ignore the consequences of Cyber Warfare will bring severe concerns to all people. Hackers and governments alike should understand the barriers of which their methods take them. Governments use Cyber Warfare to give them a tactical advantage over other countries, defend themselves from their enemies or to inflict damage upon their adversaries. Hackers use Cyber Warfare to gain personal information, commit crimes, or to reveal sensitive and beneficial intelligence. Although both methods can provide ethical uses, the equivalent can be said at the other end of the spectrum. Knowing and comprehending these devices will not only strengthen the ability to detect these attacks and combat against them but will also provide means to divulge despotic government plans, as the outcome of Cyber Warfare can be worse than the outcome of conventional warfare. The paper discussed the concept of ethics and reasons that led to use information technology in military war, the effects of using cyber war on civilians, the legality of the cyber war and ways of controlling the use of information technology that may be used against civilians. This research uses a survey methodology to overlook the awareness of Arab citizens towards the idea of cyber war, provide findings and evidences of ethics behind the offensive cyber warfare. Detailed strategies and approaches should be developed in this aspect. The author recommended urging the scientific and technological research centers to improve the security and develop defending systems to prevent the use of technology in military war against civilians.