Abstract:Attacks involving unauthorized access and modification of systems resources pose serious threats in modern computing environments. It is essential to develop novel and practical techniques to counter such threats. This special issue features four original papers focusing on various aspects of security issues. Each paper was reviewed by at least two experts in security and some of the papers underwent two rounds of reviews.

Abstract:Source location privacy, which means to protect source sensors' locations from being leaked out of observed network tra±c, is an emerging research topic in wireless sensor networks, because it cannot be fully addressed by traditional cryptographic mechanisms, such as encryption and authentication. Current source location privacy schemes, assuming either a local or global attack model, have limitations. For example, schemes under a global attack model are subject to a so called `01' attack, during which an attacker can potentially identify sources of real messages. Targeting on tackling this attack, we propose two perturbation schemes, one based on Uniform Distribution and the other based on Gaussian Distribution. We analyze the security properties of these two schemes. We also simulate and compare them with previous schemes, with results showing that the proposed perturbation schemes can improve sensor source location privacy significantly. Furthermore, it is realized that an attacker may employ more intelligent statistical tools, such as Univariate Distribution based Reconstruction (UDR), to analyze the traffic generation patterns and find out real sources. We propose a Risk Region (RR) based technique, to prevent the attacker from successfully doing this. Performance evaluation shows that the RR-based scheme increases the errors of the attacker, so that the attacker is not able to accurately derive real messages as well as their sources.

Abstract:Due to rapidly increasing complex attacks, networks become more and more insecure. How to accurately predict the future security situation of networks is thus an important research issue. Forecasting security situation can improve the awareness of network states and provide decision support to threat analysis and network planning. This paper provides a combination model of neural networks to predict the security situation of computer networks. Our contribution is in two aspects. On the one hand, we select several single neural network models including Backward Propagation (BP) network, Elman network, and Radial Basis Function (RBF) network to construct the combination model. On the other hand, we use the entropy method to determine the weights of each single model in the combination model. Experimental results show that the proposed combination model can predict the security situation of networks more e?ectively than any single neural network.

Abstract:Recently, Liu et al. have proved a class of 2k-variable Boolean functions to have optimal algebraic immunity and good immunity to fast algebraic attacks. In this paper, we proceed to study those functions in aspect of correlation immunity and nonlinearity and through restrictions to those functions we propose two sub-classes of 2k-variable Boolean functions with good cryptographic properties. To the best of our knowledge, this is the first time whole classes of Boolean functions with high nonlinearity, 1-correlation immunity and good immunity against FAA can be found.

Abstract:The increasing transistor count on a single chip provides an unprecedented amount of resources for chip designers. Unfortunately, the power consumed by each transistor does not shrink similarly, decreasing the amount of transistors that can be on simultaneously. This utilization wall leaves a growing percentage of transistors dark, or powered-off, as the chip cannot (a) provide the necessary current or (b) maintain a low operating temperature. To account for dark silicon, the computer architecture community has begun taking advantage of the wealth of available transistors to design efficient, time-sharing systems, often through specialized architectures. Meanwhile, security is quickly becoming a first-tier design constraint, increasing the need for hardware security mechanisms, in order to maintain high levels of availability and to detect and protect from intrusion. As we move into the many-core environment, many of these security mechanisms will need to be integrated on-chip. In a chip-multiprocessor environment, security will be necessary as multiple programs or users are sharing resources, thus facilitating attacks. In both a single-user and multiple-user environment, designers can build specialized hardware to provide support for security functions, such as authenticity, cryptography, and intrusion detection. In this paper, we survey current hardware security trends and provide insight on how future chip designs can leverage dark silicon for more secure designs. We provide preliminary designs and discuss future challenges and opportunities in dark silicon security. The merging of hardware security and dark silicon will facilitate efficient, fast, and secure designs.