Analysis of information leakage from encrypted Skype conversations

Voice over IP (VoIP) has experienced a tremendous growth over the last few years and is now widely used among the population and for business purposes. The security of such VoIP systems is often assumed, creating a false sense of privacy. This paper investigates in detail the leakage of information from Skype, a widely used and protected VoIP application. Experiments have shown that isolated phonemes can be classified and given sentences identified. By using the dynamic time warping (DTW) algorithm, frequently used in speech processing, an accuracy of 60% can be reached. The results can be further improved by choosing specific training data and reach an accuracy of 83% under specific conditions. The initial results being speaker dependent, an approach involving the Kalman filter is proposed to extract the kernel of all training signals.

STPA-SafeSec: Safety and Security Analysis for Cyber-Physical Systems

Cyber-physical systems tightly integrate physical processes and information and communication technologies. As today’s critical infrastructures, e.g., the power grid or water distribution networks, are complex cyber-physical systems, ensuring their safety and security becomes of paramount importance. Traditional safety analysis methods, such as HAZOP, are ill-suited to assess these systems. Furthermore, cybersecurity vulnerabilities are often not considered critical, because their effects on the physical processes are not fully understood. In this work, we present STPA-SafeSec, a novel analysis methodology for both safety and security. Its results show the dependencies between cybersecurity vulnerabilities and system safety. Using this information, the most effective mitigation strategies to ensure safety and security of the system can be readily identified. We apply STPA-SafeSec to a use case in the power grid domain, and highlight its benefits.

Progress and Research in Cybersecurity - Supporting a resilient and trustworthy system for the UK

Executive summary
Digital systems have transformed, and will continue to transform, our world. Supportive government policy, a strong research base and a history of industrial success make the UK particularly well-placed to realise the benefits of the emerging digital society. These benefits have already been substantial, but they remain at risk. Protecting the benefits and minimising the risks requires reliable and robust cybersecurity, underpinned by a strong research and translation system.
Trust is essential for growing and maintaining participation in the digital society. Organisations earn trust by acting in a trustworthy manner: building systems that are reliable and secure, treating people, their privacy and their data with respect, and providing credible and comprehensible information to help people understand how secure they are.
Resilience, the ability to function, adapt, grow, learn and transform under stress or in the face of shocks, will help organisations deliver systems that are reliable and secure. Resilient organisations can better protect their customers, provide more useful products and services, and earn people’s trust.
Research and innovation in industry and academia will continue to make important contributions to creating this resilient and trusted digital environment. Research can illuminate how best to build, assess and improve digital systems, integrating insights from different disciplines, sectors and around the globe. It can also generate advances to help cybersecurity keep up with the continued evolution of cyber risks.
Translation of innovative ideas and approaches from research will create a strong supply of reliable, proven solutions to difficult to predict cybersecurity risks. This is best achieved by maximising the diversity and number of innovations that see the light of day as products.
Policy, practice and research will all need to adapt. The recommendations made in this report seek to set up a trustworthy, self-improving and resilient digital environment that can thrive in the face of unanticipated threats, and earn the trust people place in it.
Innovation and research will be particularly important to the UK’s economy as it establishes a new relationship with the EU. Cybersecurity delivers important economic benefits, both by underpinning the digital foundations of UK business and trade and also through innovation that feeds directly into growth. The findings of this report will be relevant regardless of how the UK’s relationship to the EU changes.
Headline recommendations
● Trust: Governments must commit to preserving the robustness of encryption, including end-to-end encryption, and promoting its widespread use. Encryption is a foundational security technology that is needed to build user trust, improve security standards and fully realise the benefits of digital systems.
● Resilience: Government should commission an independent review of the UK’s future cybersecurity needs, focused on the institutional structures needed to support resilient and trustworthy digital systems in the medium and longer term. A self-improving, resilient digital environment will need to be guided and governed by institutions that are transparent, expert and have a clear and widely-understood remit.
● Research: A step change in cybersecurity research and practice should be pursued; it will require a new approach to research, focused on identifying ambitious high-level goals and enabling excellent researchers to pursue those ambitions. This would build on the UK's existing strengths in many aspects of cybersecurity research and ultimately help build a resilient and trusted digital sector based on excellent research and world-class expertise.
● Translation: The UK should promote a free and unencumbered flow of cybersecurity ideas from research to practical use and support approaches that have public benefits beyond their short term financial return. The unanticipated nature of future cyber threats means that a diverse set of cybersecurity ideas and approaches will be needed to build resilience and adaptivity. Many of the most valuable ideas will have broad security benefits for the public, beyond any direct financial returns.

Analysis of Bayesian classification-based approaches for Android malware detection

Mobile malware has been growing in scale and complexity spurred by the unabated uptake of smartphones worldwide. Android is fast becoming the most popular mobile platform resulting in sharp increase in malware targeting the platform. Additionally, Android malware is evolving rapidly to evade detection by traditional signature-based scanning. Despite current detection measures in place, timely discovery of new malware is still a critical issue. This calls for novel approaches to mitigate the growing threat of zero-day Android malware. Hence, the authors develop and analyse proactive machine-learning approaches based on Bayesian classification aimed at uncovering unknown Android malware via static analysis. The study, which is based on a large malware sample set of majority of the existing families, demonstrates detection capabilities with high accuracy. Empirical results and comparative analysis are presented offering useful insight towards development of effective static-analytic Bayesian classification-based solutions for detecting unknown Android malware.

Editorial: Special Issue on Secure Physical Layer Communications

In wireless networks, the broadcast nature of the propagation medium makes the communication process vulnerable to malicious nodes (e.g. eavesdroppers) which are in the coverage area of the transmission. Thus, security issues play a vital role in wireless systems. Traditionally, information security has been addressed in the upper layers (e.g. the network layer) through the design of cryptographic protocols. Cryptography-based security aims to design a protocol such that it is computationally prohibitive for the eavesdropper to decode the information. The idea behind this approach relies on the limited computational power of the eavesdroppers. However, with advances in emerging hardware technologies, achieving secure communications relying on protocol-based mechanisms alone become insufficient. Owing to this fact, a new paradigm of secure communications has been shifted to implement the security at the physical layer. The key principle behind this strategy is to exploit the spatial-temporal characteristics of the wireless channel to guarantee secure data transmission without the need of cryptographic protocols.

Securing the smart grid

The availability of electricity is fundamental to modern society. It is at the top of the list of critical infrastructures and its interruption can have severe consequences. This highly important system is now evolving to become more reliable, efficient, and clean. This evolving infrastructure has become known as the smart grid; and these future smart grid systems will rely heavily on ICT. This infrastructure will require many servers and due to the nature of the grid, many of these systems will be geographically diverse requiring communication links. At the heart of this ICT infrastructure will be security. At each level of the smart grid from smart metering right through to remote sensing and control networks, security will be a key factor for system design consideration. With an increased number of ICT systems in place the security risk also increases. In this paper the authors discuss the changing nature of security in relation to the smart grid by looking at the move from legacy systems to more modern smart grid systems. The potential planes of attack for future smart grid systems are identified, and the general anatomy of a cyber-attack is presented. The authors then introduce the various threat levels of different types of attack and the mitigation techniques that could be put in place for each. Finally, the authors' introduce a Phasor Measurement Unit (PMU) communication system (operated by the authors) that can be used as a test-bed for some of the proposed future security research.

High accuracy android malware detection using ensemble learning

With over 50 billion downloads and more than 1.3 million apps in Google’s official market, Android has continued to gain popularity amongst smartphone users worldwide. At the same time there has been a rise in malware targeting the platform, with more recent strains employing highly sophisticated detection avoidance techniques. As traditional signature based methods become less potent in detecting unknown malware, alternatives are needed for timely zero-day discovery. Thus this paper proposes an approach that utilizes ensemble learning for Android malware detection. It combines advantages of static analysis with the efficiency and performance of ensemble machine learning to improve Android malware detection accuracy. The machine learning models are built using a large repository of malware samples and benign apps from a leading antivirus vendor. Experimental results and analysis presented shows that the proposed method which uses a large feature space to leverage the power of ensemble learning is capable of 97.3 % to 99% detection accuracy with very low false positive rates.