Security analysis and enhancement of one-way hash based low-cost authentication protocol (OHLCAP)

Choi et al. recently proposed an efficient RFID authentication protocol for a ubiquitous computing environment, OHLCAP(One-Way Hash based Low-Cost Authentication Protocol). However, this paper reveals that the protocol has several security weaknesses : 1) traceability based on the leakage of counter information, 2) vulnerability to an impersonation attack by maliciously updating a random number, and 3) traceability based on a physically-attacked tag. Finally, a security enhanced group-based authentication protocol is presented.

Molecular dynamics study of dynamic buckling properties of nanowires with defects

Based on the embedded atom method (EAM) and molecular dynamics (MD) method, the deformation properties of Cu nanowires with different single defects under dynamic compression have been studied. The mechanical behaviours of the perfect nanowire are first studied, and the critical stress decreases with the increase of the nanowire’s length, which is well agreed with the modified Euler theory. We then consider the effects to the buckling phenomenon resulted from different defects. It is found that obvious decrease of the critical stress is resulted from different defects, and the largest decrease is found in nanowire with the surface vertical defect. Surface defects are found exerting larger influence than internal defects. The buckling duration is found shortened due to different defects except the nanowire with surface horizon defect, which is also found possessing the largest deflection. Different deflections are also observed for different defected nanowires. It is find that due to surface defects, only deflection in one direction is happened, but for internal defects, more complex deflection circumstances are observed.

Exploration of the defect’s effect on the mechanical properties of different orientated nanowires

Molecular dynamics (MD) simulations have been carried out to investigate the defect’s effect on the mechanical properties of copper nanowire with different crystallographic orientations, under tensile deformation. Three different crystallographic orientations have been considered. The deformation mechanism has been carefully discussed. It is found that the Young’s modulus is insensitive to the defect, even when the nanowire’s crystallographic orientation is different. However, due to the defect’s effect, the yield strength and yield strain appear a large decrease. The defects have played a role of dislocation sources, the slips or stacking faults are first generated around the locations of the defects. The necking locations have also been affected by different defects. Due to the surface defect, the plastic deformation has received a large influence for the <001>/{110} and <110> orientated nanowires, and a relative small influence is seen for the <111> nanowire.

Mechanical properties of cold-formed steels at elevated temperatures

Mechanical properties have an important role in the fire safety design of cold-formed steel structures due to the rapid reduction in mechanical properties such as yield strength and elastic modulus under fire conditions and associated reduction to the load carrying capacities. Hence there is a need to fully understand the deterioration characteristics of yield strength and elastic modulus of cold-formed steels at elevated temperatures. Although past research has produced useful experimental data on the mechanical properties of cold-formed steels at elevated temperatures, such data do not yet cover different cold-formed steel grades and thicknesses. Therefore, an experimental study was undertaken to investigate the elevated temperature mechanical properties of two low and high strength steels with two thicknesses that are commonly used in Australia. Tensile coupon tests were undertaken using a steady state test method for temperatures in the range 20–700 °C. Test results were compared with the currently available reduction factors for yield strength and elastic modulus, and stress–strain curves, based on which further improvements were made. For this purpose, test results of many other cold-formed steels were also used based on other similar studies undertaken at the Queensland University of Technology. Improved equations were developed to predict the yield strength and elastic modulus reduction factors and stress–strain curves of a range of cold-formed steel grades and thicknesses used in Australia. This paper presents the results of this experimental study, comparisons with the results of past research and steel design standards, and the new predictive equations.

Psychometric properties of the parents' fever management scale in a Turkish population

Aim: This paper reports a study designed to assess the psychometric properties (validity and reliability) of a Turkish version of the Australian Parents’ Fever Management Scale (PFMS). Background: Little is known about childhood fever management among Turkish parents. No scales to measure parents’ fever management practices in Turkey are available. Design: This is a methodological study. Methods: Eighty parents, of febrile children aged six months to five years, were randomly selected from the paedaitric hospital and two community family health centers in Sakarya, Turkey. The PFMS was back translated; language equivalence and content validity were validated. PFMS and socio-demographic data were collected in 2009. Means and standard deviations were calculated for interval level data and p values greater than 0.05 were considered statistically significant. Unrotated principal component analysis was used to determine construct validity and Cronbach’s coefficient alpha determined the internal consistency reliability. Results: The PFMS was psychometrically sound in this population. Construct validity, confirmed by confirmatory factor analysis [KMO 0.812, Bartlett’s Specificity (χ² = 182.799, df=28, P < 0·001)] revealed the Turkish version to be comprised of the eight original PFMS items. Internal consistency reliability coefficient was 0.80 and the scale’s total-item correlation coefficients ranged from 0.15 to 0.66 and were significant (p<0.001). Interestingly parents reported high scores on the PFMS 34.52±4.60 (range 8-40 with 40 indicating a high burden of care for febrile children). Conclusion: The PFMS was as psychometrically robust in a Turkish population as in an Australian population and is, therefore, a useful tool for health professionals to identify parents’ practices, provide targeted education thereby in reducing the unnecessary burden of care they place on themselves when caring for a febrile child. Relevance to clinical practice. Testing in different populations, cultures and healthcare systems will further assist in reporting the PFMS usefulness in clinical practice and research.

A learning-based approach to reactive security

Despite the conventional wisdom that proactive security is superior to reactive security, we show that reactive security can be competitive with proactive security as long as the reactive defender learns from past attacks instead of myopically overreacting to the last attack. Our game-theoretic model follows common practice in the security literature by making worst-case assumptions about the attacker: we grant the attacker complete knowledge of the defender’s strategy and do not require the attacker to act rationally. In this model, we bound the competitive ratio between a reactive defense algorithm (which is inspired by online learning theory) and the best fixed proactive defense. Additionally, we show that, unlike proactive defenses, this reactive strategy is robust to a lack of information about the attacker’s incentives and knowledge.

Open problems in the security of learning

Machine learning has become a valuable tool for detecting and preventing malicious activity. However, as more applications employ machine learning techniques in adversarial decision-making situations, increasingly powerful attacks become possible against machine learning systems. In this paper, we present three broad research directions towards the end of developing truly secure learning. First, we suggest that finding bounds on adversarial influence is important to understand the limits of what an attacker can and cannot do to a learning system. Second, we investigate the value of adversarial capabilities-the success of an attack depends largely on what types of information and influence the attacker has. Finally, we propose directions in technologies for secure learning and suggest lines of investigation into secure techniques for learning in adversarial environments. We intend this paper to foster discussion about the security of machine learning, and we believe that the research directions we propose represent the most important directions to pursue in the quest for secure learning.