Reliable control strategy based on sliding mode observer against FDI attacks in smart grid

This paper is concerned with the reliable operation of cyber-physical systems under false data injection attacks. First of all, a robust adaptive sliding mode observer is designed to estimate the state of the power system; different from the traditional sliding mode observer, the observer we designed is not only robust to state errors but also can automatically adjust the parameter of attack identification. Secondly, a method of attack reconstruction has been given to estimate the actual attack signal. Finally, a reliable sliding mode control strategy is proposed to eliminate the impact of false data injection attacks; compared with the existing results, the designed defense strategy utilizes the reconstructed attack signal in the attack identification scheme and state error signal at the same time. Moreover, a power system with 3 generator buses and 6 load buses is taken as an simulation example to verify the availability of the proposed control strategy.     

Kernel-based adversarial attacks and defenses on support vector classification

While malicious samples are widely found in many application fields of machine learning, suitable countermeasures have been investigated in the field of adversarial machine learning. Due to the importance and popularity of Support Vector Machines (SVMs), we first describe the evasion attack against SVM classification and then propose a defense strategy in this paper. The evasion attack utilizes the classification surface of SVM to iteratively find the minimal perturbations that mislead the nonlinear classifier. Specially, we propose what is called a vulnerability function to measure the vulnerability of the SVM classifiers. Utilizing this vulnerability function, we put forward an effective defense strategy based on the kernel optimization of SVMs with Gaussian kernel against the evasion attack. Our defense method is verified to be very effective on the benchmark datasets, and the SVM classifier becomes more robust after using our kernel optimization scheme.     

Central Aggregator Intrusion Detection System for Denial of Service Attacks

Vehicle-to-grid technology is an emerging field that allows unused power from Electric Vehicles (EVs) to be used by the smart grid through the central aggregator. Since the central aggregator is connected to the smart grid through a wireless network, it is prone to cyber-attacks that can be detected and mitigated using an intrusion detection system. However, existing intrusion detection systems cannot be used in the vehicle-to-grid network because of the special requirements and characteristics of the vehicle-to-grid network. In this paper, the effect of denial-of-service attacks of malicious electric vehicles on the central aggregator of the vehicle-to-grid network is investigated and an intrusion detection system for the vehicle-to-grid network is proposed. The proposed system, central aggregator–intrusion detection system (CA-IDS), works as a security gateway for EVs to analyze and monitor incoming traffic for possible DoS attacks. EVs are registered with a Central Aggregator (CAG) to exchange authenticated messages, and malicious EVs are added to a blacklist for violating a set of predefined policies to limit their interaction with the CAG. A denial of service (DoS) attack is simulated at CAG in a vehicle-to-grid (V2G) network manipulating various network parameters such as transmission overhead, receiving capacity of destination, average packet size, and channel availability. The proposed system is compared with existing intrusion detection systems using different parameters such as throughput, jitter, and accuracy. The analysis shows that the proposed system has a higher throughput, lower jitter, and higher accuracy as compared to the existing schemes.     

KEELOQ加密算法安全性探究

文章首先简要介绍了KEELOQ加密算法的基本概念和在实践中的应用,通过分析KEELOQ加密算法的原理及特点,提出了攻击KEELOQ加密算法的具体方法。     

基于自抗扰技术的高超声速飞行器控制系统设计

高超声速飞行器在飞行过程中超燃冲压发动机对攻角及侧滑角有较严格的要求,为实现对攻角及侧滑角的精确控制,文章采用自抗扰控制技术设计了高超声速飞行器的攻角自动驾驶仪;首先建立高超声速飞行器控制系统的数学模型,然后采用扩张状态观测器对受扰对象的状态和干扰进行观测,并对状态误差采用非线性反馈,对观测的干扰进行补偿,从而实现对干扰的快速抑制和对指令的精确跟踪,最后仿真表明所设计的自动驾驶仪满足性能要求,验证了该方法的正确性。     

加强IDC网络安全 实现信息社会和谐

本文分析了当前IDC网络环境中存在的安全隐患及网络攻击的手段,针对IDC中心的网络实际情况,从理论上提出了网络安全设计的原则、安全防御的策略和措施,列举了解决网络安全问题的相关技术,探讨建立综合性的网络安全防御系统确保网络及信息的安全。     

基于IPv6网络安全研究

随着网络人数的不断增加,IPv6取代IPv4只是时间的问题,我们首先介绍了IPv6优于IPv4的特点,它之所以成为下一代网络发展的必然趋势的原因。其次介绍了在IPv6下,网络安全比现在存在哪些优势和技术,从而也带来了哪些新的安全隐患。最后我们举例说明在IPv6下如何实现网络入侵的流程。     

Efficient chosen-ciphertext secure certificateless threshold key encapsulation mechanism

As a practical extension of our previous work on certificateless threshold cryptosystem, this paper proposes the first direct certificateless threshold key encapsulation mechanism that inherits the same trust level of the original scheme and removes the length limitation of a traditional public key encryption. Security against threshold chosen-ciphertext attacks are proved in a random oracle model under a new assumption. It tolerates the Type I adversary that can replace public keys and the Type II adversary that has access to the system’s master key. The implied encapsulation scheme is very efficient when compared to the most efficient schemes in a traditional public key cryptosystem, and it is slightly more efficient in terms of key length and encapsulation speed when compared to the identity-based cryptosystems that have the same ciphertext overhead. Finally, we describe several potential modifications of our scheme.     

Assessing canopy mortality during a mountain pine beetle outbreak using GeoEye-1 high spatial resolution satellite data

Continuing, severe outbreaks of mountain pine beetle (Dendroctonus ponderosae) across western North America have resulted in widespread mortality of lodgepole pine (Pinus contorta). Multiple studies have used high spatial resolution satellite data to map areas of beetle kill; these studies have largely focused on mapping red canopy cover associated with recent tree mortality and have not examined mapping gray canopy cover that occurs after red needles have dropped. The work presented here examines the use of newly available GeoEye-1 data for mapping both red and gray canopy area in southeastern Wyoming lodgepole pine forest. A 0.5 m spatial resolution, pan-sharpened GeoEye-1 image was used to classify areas of green, red, and gray canopy cover. Reference data were collected at twelve 500 m² field plots. Shadow-normalized green, red, and gray canopy area from classified GeoEye-1 data closely agreed with field-estimated green, red, and gray canopy area. Mean absolute error in canopy cover for the twelve sample plots was 8.3% for the green class, 5.4% for the red class, and 7.2% for the gray class. When all twelve plots were aggregated, remotely sensed estimates of green, red, and gray cover were within 1.7% of the field-estimated cover. Our results demonstrate that high spatial resolution spaceborne multispectral data are a promising tool for mapping canopy mortality caused by mountain pine beetle outbreaks.     

Continuous wavelet analysis for the detection of green attack damage due to mountain pine beetle infestation

Mountain pine beetle (Dendroctonus ponderosae Hopkins) is the most destructive insect infesting mature pine forests in North America and has devastated millions of hectares of forest in western Canada. Past studies have demonstrated the use of multispectral imagery for remote identification and mapping of visible or red attack damage in forests. This study aims to detect pre-visual or green attack damage in lodgepole pine needles by means of hyperspectral measurements, particularly via continuous wavelet analysis. Field measurements of lodgepole pine stands were conducted at two sites located northwest of Edmonton, Alberta, Canada. In June and August of 2007, reflectance spectra (350-2500 nm) were collected for 16 pairs of trees. Each of the 16 tree pairs included one control tree (healthy), and one stressed tree (girdled to simulate the effects of beetle infestation). In addition, during the period of June through October 2008, spectra were collected from 15 pairs of control- and beetle-infested trees. Spectra derived from these 31 tree pairs were subjected to a continuous wavelet transform, generating a scalogram that compiles the wavelet power as a function of wavelength location and scale of decomposition. Linear relationships were then explored between the wavelet scalograms and chemical properties or class labels (control and non-control) of the sample populations in order to isolate the most useful distinguishing spectral features that related to infested or girdled trees vs. control trees.A deficit in water content is observed in infested trees while an additional deficit in chlorophyll content is seen for girdled trees. The measurable water deficit of infested and girdled tree samples was detectable from the wavelet analysis of the reflectance spectra providing a novel method for the detection of green attack. The spectral features distinguishing control and infested trees are predominantly located between 950 and 1390 nm from scales 1 to 8. Of those, five features between 1318 to 1322 nm at scale 7 are consistently found in the July and August 2008 datasets. These features are located at longer wavelengths than those investigated in previous studies (below 1100 nm) and provide new insights into the potential remote detection of green attack. Spectral features that distinguish control and girdled trees were mostly observed between 1550 and 2370 nm from scales 1 to 5. The differing response of girdled and infested trees appears to indicate that the girdling process does not provide a perfect simulation of the effects caused by beetle infestation.It remains to be determined if the location of the 1318-1322 nm features, near the edge of a strong atmospheric water absorption band, will be sufficiently separable for use in airborne detection of green attack. A plot comparing needle water content and wavelet power at 1320 nm reveals considerable overlap between data derived from both infested and control samples, though the groups are statistically separable. This obstacle may preclude a high accuracy separation of healthy and infected single individuals, but establishing threshold identification levels may provide an economical, efficient and expeditious method for discriminating between healthy and infested tree populations.