Intrusion Detection System for PS-Poll DoS Attack in 802.11 Networks Using Real Time Discrete Event System

Wi-Fi devices have limited battery life because of which conserving battery life is imperative. The 802.11 Wi-Fi standard provides power management feature that allows stations(STAs) to enter into sleep state to preserve energy without any frame losses. After the STA wakes up, it sends a null data or PS-Poll frame to retrieve frame(s) buffered by the access point(AP), if any during its sleep period. An attacker can launch a power save denial of service(PS-DoS) attack on the sleeping STA(s) by transmitting a spoofed null data or PS-Poll frame(s) to retrieve the buffered frame(s) of the sleeping STA(s) from the AP causing frame losses for the targeted STA(s). Current approaches to prevent or detect the PS-DoS attack require encryption,change in protocol or installation of proprietary hardware. These solutions suffer from expensive setup, maintenance, scalability and deployment issues. The PS-DoS attack does not differ in semantics or statistics under normal and attack circumstances.So signature and anomaly based intrusion detection system(IDS) are unfit to detect the PS-DoS attack. In this paper we propose a timed IDS based on real time discrete event system(RTDES) for detecting PS-DoS attack. The proposed DES based IDS overcomes the drawbacks of existing systems and detects the PS-DoS attack with high accuracy and detection rate. The correctness of the RTDES based IDS is proved by experimenting all possible attack scenarios.

Hybrid-triggered consensus for multi-agent systems with time-delays,uncertain switching topologies, and stochastic cyber-attacks

We propose a new approach to discuss the consensus problem of multi-agent systems with time-varying delayed control inputs, switching topologies, and stochastic cyber-attacks under hybrid-triggered mechanism.A Bernoulli variable is used to describe the hybrid-triggered scheme, which is introduced to alleviate the burden of the network.The mathematical model of the closed-loop control system is established by taking the influences of time-varying delayed control inputs,switching topologies, and stochastic cyber-attacks into account under the hybrid-triggered scheme.A theorem as the main result is given to make the system consistent based on the theory of Lyapunov stability and linear matrix inequality.Markov jumps with uncertain rates of transitions are applied to describe the switch of topologies.Finally, a simulation example demonstrates the feasibility of the theory in this paper.

Further Analysis of Block Ciphers against Timing Attacks

Timing attacks break a cryptosystem by time measurement to recover keys. Most available countermeasures protect block ciphers based on the safety of modules. This paper gives a complete definition of timing attacks and studies the vulnerability of operations and modules on timing attacks. We present a method to transfer the security of the algorithm to that of secure operations by reduction. As a result, we hopefully tend to reconcile the provable security notions and modem cryptography with real-world implementations of block ciphers.

Timing Attack Analysis on AA_βCryptosystem

Timing attack is an attack on the implementation of a cryptographic primitive. The attack collects leaked secret data via certain implementation techniques either on software or hardware. This paper provides an analysis of a theoretical timing attack on the AAβ algorithm. The attack discussed in this paper gives avenues for secure implementation of AAβ against timing attacks. The simulation of the attack is important to provide invulnerability features for the algorithm in order to be implemented and embedded on applications. At the end of the attack, a method to overcome it will be introduced and it is called AAβ blinding.

A Novel Technique for Detection of Time Delay Switch Attack on Load Frequency Control

In this paper, we focus on the estimation of time delays caused by adversaries in the sensing loop (SL). Based on the literature review, time delay switch (TDS) attacks could make any control system, in particular a power control system, unstable. Therefore, future smart grids will have to use advanced methods to provide better situational awareness of power grid states keeping smart grids reliable and safe from TDS attacks. Here, we introduce a simple method for preventing time delay switch attack on networked control systems. The method relies on an estimator that will estimate and track time delays introduced by an adversary. Knowing the maximum tolerable time delay of the plant’s optimal controller for which the plant remains stable, a time-delay detector issues an alarm signal when the estimated time delay is larger than the minimum one and directs the system to alarm state. In an alarm state, the plant operates under the control of an emergency controller that is local to the plant and remains in this mode until the networked control system state is restored. This method is an inexpensive and simple way to guarantee that an industrial control system remains stable and secure.

Information Theoretic Distinguishers for Timing Attacks with Partial Profiles: Solving the Empty Bin Issue

In any side-channel attack, it is desirable to exploit all the available leakage data to compute the distinguisher’s values. The profiling phase is essential to obtain an accurate leakage model, yet it may not be exhaustive. As a result, information theoretic distinguishers may come up on previously unseen data, a phenomenon yielding empty bins. A strict application of the maximum likelihood method yields a distinguisher that is not even sound. Ignoring empty bins reestablishes soundness, but seriously limits its performance in terms of success rate. The purpose of this paper is to remedy this situation. In this research, we propose six different techniques to improve the performance of information theoretic distinguishers. We study them thoroughly by applying them to timing attacks, both with synthetic and real leakages. Namely, we compare them in terms of success rate, and show that their performance depends on the amount of profiling, and can be explained by a bias-variance analysis. The result of our work is that there exist use-cases, especially when measurements are noisy, where our novel information theoretic distinguishers (typically the soft-drop distinguisher) perform the best compared to known side-channel distinguishers, despite the empty bin situation.

ICPS multi-target constrained comprehensive security control based on DoS attacks energy grading detection and compensation

Aiming at the industry cyber-physical system(ICPS)where Denial-of-Service(DoS)attacks and actuator failure coexist,the integrated security control problem of ICPS under multi-objective constraints was studied.First,from the perspective of the defender,according to the differential impact of the system under DoS attacks of different energies,the DoS attacks energy grading detection standard was formulated,and the ICPS comprehensive security control framework was constructed.Secondly,a security transmission strategy based on event triggering was designed.Under the DoS attack energy classification detection mechanism,for large-energy attacks,the method based on time series analysis was considered to predict and compensate for lost data.Therefore,on the basis of passive and elastic response to small energy attacks,the active defense capability against DoS attacks was increased.Then by introducing the conecomplement linearization algorithm,the calculation methods of the state and fault estimation observer and the integrated safety controller were deduced,the goal of DoS attack active and passive hybrid intrusion tolerance and actuator failure active fault tolerance were realized.Finally,a simulation example of a four-capacity water tank system was given to verify the validity of the obtained conclusions.

An Abnormal Network Flow Feature Sequence Prediction Approach for DDoS Attacks Detection in Big Data Environment

Distributed denial-of-service(DDoS)is a rapidly growing problem with the fast development of the Internet.There are multitude DDoS detection approaches,however,three major problems about DDoS attack detection appear in the big data environment.Firstly,to shorten the respond time of the DDoS attack detector;secondly,to reduce the required compute resources;lastly,to achieve a high detection rate with low false alarm rate.In the paper,we propose an abnormal network flow feature sequence prediction approach which could fit to be used as a DDoS attack detector in the big data environment and solve aforementioned problems.We define a network flow abnormal index as PDRA with the percentage of old IP addresses,the increment of the new IP addresses,the ratio of new IP addresses to the old IP addresses and average accessing rate of each new IP address.We design an IP address database using sequential storage model which has a constant time complexity.The autoregressive integrated moving average(ARIMA)trending prediction module will be started if and only if the number of continuous PDRA sequence value,which all exceed an PDRA abnormal threshold(PAT),reaches a certain preset threshold.And then calculate the probability that is the percentage of forecasting PDRA sequence value which exceed the PAT.Finally we identify the DDoS attack based on the abnormal probability of the forecasting PDRA sequence.Both theorem and experiment show that the method we proposed can effectively reduce the compute resources consumption,identify DDoS attack at its initial stage with higher detection rate and lower false alarm rate.

Sliding mode control and Lyapunov based guidance law with impact time constraints

This paper analyses the issue of impact time control of super-cavitation weapons impact fixed targets which mainly refer to the ships or submarines who lost power, but still have combat capability. Control over impact time constraints of guidance law(ITCG) is derived by using sliding mode control(SMC) and Lyapunov stability theorem. The expected impact time is realized by using the notion of attack process and estimated time-to-go to design sliding mode surface(SMS). ITCG contains equivalent and discontinuous guidance laws, once state variables arrive at SMS,the equivalent guidance law keeps the state variables on SMS,then the discontinuous guidance law enforces state variables to move and reach SMS. The singularity problem of ITCG is also analyzed. Theoretical analysis and numerical simulation results are given to test the effectiveness of ITCG designed in this paper.

TDOA-based Sybil attack detection scheme for wireless sensor networks

As wireless sensor networks （WSN） are deployed in fire monitoring, object tracking applications, security emerges as a central requirement. A case that Sybil node illegitimately reports messages to the master node with multiple non-existent identities （ID） will cause harmful effects on decision-making or resource allocation in these applications. In this paper, we present an efficient and lightweight solution for Sybil attack detection based on the time difference of arrival （TDOA） between the source node and beacon nodes. This solution can detect the existence of Sybil attacks, and locate the Sybil nodes. We demonstrate efficiency of the solution through experiments. The experiments show that this solution can detect all Sybil attack cases without missing.

Modified Adhoc On-Demand Distance Vector for Trust Evaluation And Attack Detection

Recently,Wireless Sensor Network(WSN)becomes most potential technologies for providing improved services to several data gathering and track-ing applications.Because of the wireless medium,multi-hop communication,absence of physical protectivity,and accumulated traffic,WSN is highly vulner-able to security concerns.Therefore,this study explores a specific type of DoS attack identified as a selective forwarding attack where the misbehaving node in the network drops packet on a selective basis.It is challenging to determine if packet loss is caused by a collision in the medium access path,poor channel quality,or a selective forwarding assault.Identifying misbehaving nodes at the earliest opportunity is an acceptable solution for performing secure routing in such networks.As a result,in this study effort,we present a unique Modified Ad Hoc On-Demand Distance Vector(AODV)Routing protocol depending upon the One time password(OTP)method that employs the RSA algorithm.Finally,a trust evaluation process determines which approach is the most optimal.Accord-ing to the simulationfindings of the suggested routing protocol and comparison with existing routing protocols provided in this article,the proposed work is both efficient and cost-effective.

计及DoS攻击和通信时滞的电力系统负荷频率控制

针对电力系统通信网络中存在的时滞和DoS攻击现象,本文提出了基于采样特性的电力系统离散负荷频率控制方案。首先,计及电力系统负荷波动的情况,在多区域电力系统负荷频率控制系统(LFC)模型的基础上,将通信网络中DoS攻击的危害量化为采样信号连续丢失数,并分别考虑通信网络中通信时滞和输出信号采样特性,建立包含输出状态反馈控制器的电力系统LFC模型。其次,基于此模型,利用含有控制命令更新周期、DoS攻击导致的最大采样信号连续丢失数、通信时滞、H_(∞)稳定指标的双边闭环Lyapunov泛函、LMI技术,提出LFC系统满足一定H_(∞)指标的稳定准则,并给出离散状态输出反馈LFC控制器的设计及求解方法。最后,本文以单区域和双区域LFC系统为例进行了仿真验证。结果表明:与已有文献方法相比,本文方法在保持系统H_(∞)渐近稳定前提下,能够容忍更大的通信时滞,且结果的保守性更低;同时可以看出本文所设计的控制器在保证H_(∞)稳定性能的基础上,对一定能量限制的DoS攻击具有弹性的防御性能。因此本文方案的有效性和优越性得到了验证。

Generalized Attack Model for Networked Control Systems, Evaluation of Control Methods

Networked Control Systems (NCSs) have been implemented in several different industries. The integration with advanced communication networks and computing techniques allows for the enhancement of efficiency of industrial control systems. Despite all the advantages that NCSs bring to industry, they remain at risk to a spectrum of physical and cyber-attacks. In this paper, we elaborate on security vulnerabilities of NCSs, and examine how these vulnerabilities may be exploited when attacks occur. A general model of NCS designed with three different controllers, i.e., proportional-integral-derivative (PID) controllers, Model Predictive control (MPC) and Emotional Learning Controller (ELC) are studied. Then three different types of attacks are applied to evaluate the system performance. For the case study, a networked pacemaker system using the Zeeman nonlinear heart model (ZHM) as the plant combined with the above-mentioned controllers to test the system performance when under attacks. The results show that with Emotional Learning Controller (ELC), the pacemaker is able to track the ECG signal with high fidelity even under different attack scenarios.

盐渍土环境下考虑耐久性损伤的输电塔风振时程分析

长期服役于盐渍土环境下的输电塔耐久性损伤较为严重,当其材料力学性能退化到一定程度时,在强风作用下,输电塔可能会发生破坏,危害线路的安全运行。基于±800kV天中线特高压直流输电工程直线塔,考虑基础钢筋锈蚀、基础混凝土侵蚀、输电塔杆塔钢材锈蚀以及基础箍筋的约束效应,在ABAQUS有限元软件中建立塔-线-基础耦合模型,研究不同风攻角和材料耐久性损伤对塔身动力响应的影响。结果表明:90°风攻角下塔身顺风向位移最大,为最不利风向基本工况;90°风攻角下输电塔塔顶顺风向位移响应贡献主要以背景分量为主,但共振分量也有一定贡献,主要以输电塔1阶振型频率为主,且随着服役时间的增加,振型频率逐渐降低,相应响应的贡献程度逐渐提高;相同风荷载作用下,随着服役时间的增加,塔身位移逐渐增大,相同服役时间下,随着塔身高度的增加,塔身位移响应峰值增长速度变快,结构振动更加明显,材料耐久性损伤对输电塔的位移响应影响较大。

高并发异构数据库SQL注入攻击检测方法与仿真

异构数据库具有数据量规模庞大、多样性等特点。在高并发条件下,数据库系统会承受大量的查询请求,使得检测出SQL注入攻击数据不具备实时效应。因此,提出高并发异构数据库SQL注入攻击检测方法。通过清洗异构数据库,采用主成分分析方法对数据降维;采用词频-逆文档频率(Term Frequency Inverse Document Frequency,TFIDF)算法对异构数据库攻击数据量化,并提取攻击特征;结合支持向量机(Support Vector Machine,SVM)方法对特征分类,实现异构数据库SQL注入攻击检测。实验结果表明,上述方法检测SQL注入攻击时,当待检测数据量较大时,耗时仅为53ms,且能够适配于所有SQL注入攻击类型。

氯盐与硫酸盐复合侵蚀下钢筋混凝土锈裂行为

为评估海洋、盐湖等环境中钢筋混凝土结构耐久性,通过试验与理论相结合探究氯盐与硫酸盐复合侵蚀下钢筋混凝土锈裂特性。通电腐蚀5%(质量分数)NaCl、5%NaCl+5%Na_(2)SO_(4)溶液中钢筋混凝土试件,对比分析混凝土表观形貌、钢筋锈蚀特征。设计伴随的混凝土腐蚀试验,类比保护层腐蚀劣化,分析混凝土力学性能。结果表明:硫酸盐的存在改变胀裂前混凝土形貌,使得单一氯盐侵蚀下的“白须”消失,表面粉化并出现盐结晶,延长胀裂时间;复合侵蚀下钢筋锈蚀率低于单一氯盐侵蚀,二者均显著低于法拉第定律理论值;锈胀裂缝宽度与钢筋锈蚀率线性相关,硫酸盐的存在增大裂缝随钢筋锈蚀发展的速率;通电环境中,受腐蚀混凝土的抗压强度先升高后降低,劈裂抗拉强度不断降低。提出受腐蚀混凝土的抗拉强度演化经验公式。在经典锈胀模型的基础上考虑锈蚀产物对裂缝的填充作用,并将硫酸盐的影响考虑至混凝土抗拉强度、钢筋腐蚀电流密度中,建立复合侵蚀下钢筋混凝土胀裂时间预测模型,并验证了模型的有效性。

视场角限制下的攻击时间和角度三维矢量制导律设计

为了提高导弹精确打击目标的能力,控制攻击时间和攻击角度三维制导问题在实际应用中具有重要的意义。针对这一问题,本文基于三维矢量制导模型提出了一种视场角约束下的攻击时间和攻击角度控制律。首先,通过将平面矢量制导律扩展至三维空间,提出了一种三维矢量攻击角度约束制导律;其次,在上述制导指令的拦截分量中引入剩余时间偏置项,设计了一种在视场角约束下的三维矢量制导律,并进行了稳定性分析。保证导弹能在视场角约束的条件下,以期望的攻击时间和角度击中目标,并且误差均小于0.01;最后,通过数值模拟验证了所设计制导律的正确性和有效性。

基于局部扰动的时间序列预测对抗攻击

时间序列预测模型已广泛应用于日常生活中的各个行业,针对这些预测模型的对抗攻击关系到各行业数据的安全性.目前,时间序列的对抗攻击多在全局范围内进行大规模扰动,导致对抗样本易被感知.同时,对抗攻击的效果会随着扰动幅度的降低而明显下降.因此,如何在生成不易察觉的对抗样本的同时保持较好的攻击效果,是当前时间序列预测对抗攻击领域亟需解决的问题之一.首先提出一种基于滑动窗口的局部扰动策略,缩小对抗样本的扰动区间;其次,使用差分进化算法寻找最优攻击点位,并结合分段函数分割扰动区间,进一步降低扰动范围,完成半白盒攻击.和已有的对抗攻击方法在多个不同深度模型上的对比实验表明,所提出的方法能够生成不易感知的对抗样本,并有效改变模型的预测趋势,在股票交易、电力消耗、太阳黑子观测和气温预测这4个具有挑战性的任务中均取得了较好的攻击效果.

处理器时间侧信道攻防技术综述

现代处理器优化机制众多,设计人员在追求性能提升时,往往忽略背后的安全风险。时间侧信道攻击因其影响面广且隐蔽性好已成为最主要的安全威胁之一。随着瞬态执行攻击的出现,时间侧信道攻击的能力被进一步扩展,计算系统的安全基础被动摇。为此,处理器厂商及安全人员提出了大量防御机制。这些机制具有不同的防护能力及性能开销。与此同时,新的瞬态执行漏洞和隐蔽信道也不断被发现,已提出的防御机制被不断突破。围绕处理器时间侧信道攻防技术的博弈日益激烈。本文从基本攻击原理出发,对现有时间侧信道攻击进行了归纳总结,并在此基础上进一步分析了相关防御机制的保护能力和性能瓶颈,从而梳理出时间侧信道攻防技术的发展趋势,为未来软硬件系统开发和安全技术探索提供参考。