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• W2516592349 abstract "Today's world's societies are becoming more and more dependent on open networks such as the Internet – where commercial activities, business transactions, and government services are realized. This has led to the fast development of new cyber threats and numerous information security issues which are exploited by cyber criminals. The inability to provide trusted secure services in contemporary computer network technologies has a tremendous socio-economic impact on global enterprises as well as individuals. Moreover, the frequently occurring international frauds impose the necessity to conduct the investigation of facts spanning across multiple international borders. Such examination is often subject to different jurisdictions and legal systems. A good illustration of the previously mentioned is the Internet, which has made it easier to perpetrate traditional crimes. It has acted as an alternate avenue for the criminals to conduct their activities, and launch attacks with relative anonymity. The increased complexity of the communications and the networking infrastructure is making investigation of the crimes difficult. Traces of illegal digital activities are often buried in large volumes of data, which are hard to inspect with the aim of detecting offenses and collecting evidence. Nowadays, the digital crime scene functions like any other network, with dedicated administrators functioning as the first responders. This poses new challenges for law enforcement policies and forces the computer societies to utilize digital forensics to combat the increasing number of cybercrimes. Forensic professionals must be fully prepared in order to be able to provide court admissible evidence. To make these goals achievable, forensic techniques should keep pace with new technologies. In this special issue, we are delighted to present a selection of 14 papers, which, in our opinion, will contribute to the enhancement of knowledge in cyber crime. The collection of high-quality research papers provides a view on the latest research advances and results in the field of digital forensics and to present the development of tools and techniques which assist the investigation process of potentially illegal cyber activity. In the first paper, Cyberterrorism targeting the general public through social media, Nicholas Ayres and Leandros A. Maglaras investigate whether a mimetic malware could be a viable method of attack against a population with respect to cyberterrorism. The presented research shows that although people are, in general, aware of cyberterrorism on their current level of fear of being a potential target of attack is relatively low. However, when presented with such a threat, their level of fear increased. The obtained results prove that a targeted mimetic virus can indeed have an effect on a population and is a potential attack method for cyberterrorism. The paper emphasizes also the importance of social media as a vessel of propagation of such threat. Next, in the paper entitled Effectiveness of File-Based Deduplication in Digital Forensics Sebastian Neuner, Martin Schmiedecker, and Edgar Weippl focus on introducing improvements to the standardized forensic process to reduce the amount of storage requirement for forensic investigations by using file whitelisting and cross-device deduplication. Authors approach is shown to be particularly useful in cases where investigation relies on referenced files in the file system. In the exemplary use case authors prove that file deduplication and file whitelisting can be successfully utilized to achieve 78% size reduction compared to the full data set which means saving about 700 gigabytes of storage capacity. Jawwad Shamsi, Sherali Zeadally, Fareha Sheikh, and Angelyn Flowers in Attribution in Cyberspace: Techniques and Legal Implications argue that only a few known cybercrimes have been successfully attributed to the actual attacker. To improve this situation authors propose three-level attribution framework to indicate various attributes and guidelines through which attribution can be instigated. The proposed framework is an initial step and in order to be successful it requires strong cooperation between different stake holders, government sponsored active cyber unit, existence of cyber laws, and cooperation among international community members. Next, two papers are focused on anomaly detection. In Evolutionary-based Packets Classification for Anomaly Detection in Web Layer, Rafał Kozik, Michał Choraś, and Witold Hołubowicz propose a novel detection method for modern web applications. First, authors observe that the majority of the state of the art solutions make an assumption about the packets' content, or how the data inside the payload is serialized. Then they propose an evolutionary-based approach to unsupervised and automated packets segmentation. On the top of their approach, authors apply several variants of machine-learned classifiers and statistics to prove that the proposed algorithm can improve the effectiveness of many well-known anomaly detection methods. In the second paper entitled DWT-based Anomaly Detection Method for Cyber Security of Wireless Sensor Networks Łukasz Saganowski, Tomasz Andrysiak, Rafał Kozik, and Michał Choraś introduce a discrete wavelet transformation-based anomaly detection approach for wireless sensor networks which is especially suited for deployment in critical infrastructures for measuring and/or monitoring purposes. The main authors' contribution is that the proposed anomaly detection is integrated with an effective SNORT-based pre-processor. Then DWT-based solution is applied to 25 network traffic parameters measured in a realistic testbed and most suitable parameters are indicated. It is worth noting that several papers from this special issue are devoted to information hiding techniques, which utilization is currently a raising trend among cybercriminals. Papers focus on both: proposing new methods and detection approaches. In the first paper entitled Pitch-based steganography for Speex voice codec, Artur Janicki devises an improved version of the HideF0 steganographic algorithm which is especially suitable for IP telephony. The proposed approach relies on approximation of the pitch-related parameter (F0) in speech signal regions where the pitch is monotonic enough to be linearly approximated with a low error. It also utilizes unused fields in the headers of the voice packets. Experiments conducted on all narrowband Speex codec modes show that an improvement in quality when compared with the originally proposed algorithm has been observed. The resulting steganographic bandwidths of HideF0 turns out to be around 200 bps at the expense of a steganographic cost of between 0.5 and 0.7 MOS, depending on the Speex mode. Hui Tian, Yanpeng Wu, Chin-Chen Chang, Yongfeng Huang, Jin Liu, Tian Wang, Yonghong Chen, and Yiqiao Cai in Steganalysis of Analysis-by-synthesis Speech Exploiting Pulse-position Distribution Characteristics introduce a Support Vector Machine-based detection of low bit-rate speech which utilizes statistic characteristics of pulse positions, that is, the probability distribution of pulse positions as a long-time distribution feature, Markov transition probabilities of pulse positions according to the short-time invariance characteristic of speech signals, and finally joint probability matrices characterizing the pulse-to-pulse correlation. The proposed steganalysis method is evaluated for the G.729a speech codec and compared with the state-of-the-art methods. Obtained experimental results reveal that the proposed method's detection performance is superior when compared with the previous steganalysis algorithms. The paper, Color Images Stegananalysis Using RGB Channel Geometric Transformation Measures by Hasan Abdulrahman, Marc Chaumont, Philippe Montesinos, and Baptiste Magnier, introduces steganalysis method for color images that is based on color feature correlation and machine learning classification. This approach relies on fusing features with those obtained from color-rich models which results in improved detectability of hidden messages. Authors use two types of features, computed between color image channels – first that reflects local Euclidean transformations and second that reflects mirror transformations. They also demonstrate the efficiency of the proposed detection method on three state-of-the-art steganography algorithms. The paper, A framework of adaptive steganography resisting JPEG compression and detection by Yi Zhang, Xiangyang Luo, Chunfang Yang, Dengpan Ye, and Fenlin Liu, describes a framework of adaptive steganography resisting JPEG compression and detection which aims at solving the issue of information loss in the process of image compression while applying image steganography to mobile intelligent terminals. The proposed framework uses the relationship between discrete cosine transform coefficients to determine the domain of messages embedding. Based on this framework, authors devise an adaptive steganography algorithm and perform its evaluation. Obtained experimental results for different payloads and quality factors of JPEG compression prove that when an algorithm is based on the framework, it has both a strong JPEG compression resistant ability and detection resistant performance. In the next paper, Micro protocol engineering for unstructured carriers: On the embedding of steganographic control protocols into audio transmissions, Matthias Naumann, Steffen Wendzel, Wojciech Mazurczyk, and Jörg Keller present techniques to embed micro protocol, that is, covert channel control protocol into an unstructured carrier which is audio streaming over the network. Two types of implementing the micro protocol: static and dynamic have been demonstrated. This allowed comparing the resulting performance and to measure the impact of both designs on the overt audio signal. On the basis of obtained experimental results, a micro protocol engineering approach for unstructured carriers has been devised. Another paper that is focused on analysis of micro protocols has been authored by Jaspreet Kaur, Steffen Wendzel, Omar Eissa, Jernej Tonejc, and Michael Meier. In Covert Channel-internal Control Protocols: Attacks and Defense, an interesting analysis of micro protocols has been conducted. First authors demonstrate that some potential attacks scenarios on micro protocols exist, and that if successful, they are able to break even sophisticated covert communication. The described attacks are based on the attacker's intentional interaction with the micro protocol specifics. Then, authors propose several defense techniques to make micro protocols immune against such threats. In Perfect undetectability of network steganography, Wojciech Frączek and Krzysztof Szczypiorski introduce StegBlocks that is a general approach for constructing network steganography techniques which defines the way in which the methods work, and at the same time it allows for the creation of methods for various carriers (network protocols). The paper encloses also the definition of perfectly undetectable network steganography which is derived from a classic steganography definition, and it covers the specific features of network steganography. Using this definition, authors argue that it is possible to create a network steganography method that is undetectable for the adversary with unlimited computational power. In the next article, DAT Detectors – Uncovering TCP/IP Covert Channels by Descriptive Analytics, Felix Iglesias, Robert Annessi, and Tanja Zseby propose descriptive analytics of traffic (DAT) detectors that utilize descriptive analytics for the detection of covert channels in TCP/IP communication networks. DAT detectors are envisioned to be an extension for network intrusion detection system and are aimed to perform fast and lightweight analysis of numerous flows. They transform communication data into flexible feature vectors that represent traffic as a set of extracted calculations and estimations. The detection approach relies mostly on the combined application of autocorrelation calculations and multimodality measures built upon kernel density estimations and Pareto charts. In the last of the presented articles, An assessment of automatic speaker verification vulnerabilities to replay spoofing attacks, Artur Janicki, Federico Alegre, and Nicholas Evans compare at a high level the threat of replay attacks to those of speech synthesis and voice conversion. This comparison is performed using strictly controlled protocols and with six different Automatic Speaker Verification systems. Presented experimental results prove that low-effort replay attacks are indeed a threat to speech synthesis and voice conversion. Basing on these findings, authors also introduce and assess two replay attack countermeasures: the local binary pattern analysis of speech spectrograms and an approach based on the detection of far-fields recordings. To summarize, we believe that this Special Issue will contribute to enhancing knowledge in Information and Communication Technology security and in Cyber Crime in particular. In addition, we also hope that the presented results will stimulate further research in the important areas of information and network security. We also want to thank the Editors-in-Chief of the Security and Communication Networks journal, the researchers contributing to the special issue, and excellent reviewers for their great help and support that made this special issue possible." @default.
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• W2516592349 title "Cyber Crime" @default.
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