Secure and efficient elliptic curve cryptography resists side-channel attacks

An embedded cryptosystem needs higher reconfiguration capability and security. After analyzing the newly emerging side-channel attacks on elliptic curve cryptosystem （ECC）, an efficient fractional width-w NAF （FWNAF） algorithm is proposed to secure ECC scalar multiplication from these attacks. This algorithm adopts the fractional window method and probabilistic SPA scheme to reconfigure the pre-computed table, and it allows designers to make a dynamic configuration on pre-computed table. And then, it is enhanced to resist SPA, DPA, RPA and ZPA attacks by using the random masking method. Compared with the WBRIP and EBRIP methods, our proposals has the lowest total computation cost and reduce the shake phenomenon due to sharp fluctuation on computation performance.

Resistance against side channel attack for RSA cryptosystem

Based on the structure of the side channel attacks （SCAs） to RSA cryptosystem can resist the fault attack and combine with the randomization method for the message and secret exponent, a new implementation scheme of CRT-based （the Chinese remained theorem） RSA is proposed. The proposed scheme can prevent simple power analysis （SPA）, differential power analysis （DPA） and time attack, and is compatible with the existing RSA-CRT cryptosystem as well. In addition, an improvement for resisting fault attack is proposed, which can reduce extra computation time.

An Efficient Method against Side-Channel Attacks on ECC

Side-channel attacks （SCA） may exploit leakage information to break cryptosystems. In this paper we present a new SCA resistant Elliptic Curve scalar multiplication algorithm. The proposed algorithm, builds a sequence of bit-strings representing the scalar k, characterized by the fact that all bit-strings are different from zero; this property will ensure a uniform computation behavior for the algorithm, and thus will make it secure against simple power analysis attacks （SPA）. With other randomization techniques, the proposed countermeasures do not penalize the computation time. The proposed scheme is more efficient than MOEller＇s one, its cost being about 5% to 10% smaller than MOEller＇s one.

An Effective and Scalable VM Migration Strategy to Mitigate Cross-VM Side-Channel Attacks in Cloud

Co-residency of virtual machines(VMs) of different tenants on the same physical platform would possibly lead to cross-VM side-channel attacks in the cloud. While most of current countermeasures fail for real or immediate deployment due to their requirement for modification of virtualization structure, we adopt dynamic migration, an inherent mechanism of the cloud platform, as a general defense against this kind of threats. To this end, we first set up a unified practical information leakage model which shows the factors affecting side channels and describes the way they influence the damage due to side-channel attacks. Since migration is adopted to limit the time duration of co-residency, we envision this defense as an optimization problem by setting up an Integer Linear Programming(ILP) to calculate optimal migration strategy, which is intractable due to high computational complexity. Therefore, we approximate the ILP with a baseline genetic algorithm, which is further improved for its optimality and scalability. Experimental results show that our migration-based defense can not only provide excellent security guarantees and affordable performance cost in both theoretical simulation and practical cloud environment, but also achieve better optimality and scalability than previous countermeasures.

Side-Channel Attacks & Data Exfiltration Using Wall Outlet USB Power Adapters

The number and creativity of side channel attacks have increased dramatically in recent years. Of particular interest are attacks leveraging power line communication to 1) gather information on power consumption from the victim and 2) exfiltrate data from compromised machines. Attack strategies of this nature on the greater power grid and building infrastructure levels have been shown to be a serious threat. This project further explores this concept of a novel attack vector by creating a new type of penetration testing tool: an USB power adapter capable of remote monitoring of device power consumption and communicating through powerline communications.

Adaptive multilevel fuzzy-based authentication framework to mitigate Cache side channel attack in cloud computing

Cloud computing supports multitenancy to satisfy the users’demands for accessing resources and simultaneously it increases revenue for cloud providers.Cloud providers adapt multitenancy by virtualizing the resources,like CPU,network interfaces,peripherals,hard drives and memory using hypervisor to fulfill the demand.In a virtualized environment,many virtual machines(VMs)can run on the same core with the help of the hypervisor by sharing the resources.The VMs running on the same core are the target for the malicious or abnormal attacks like side channel attacks.Among various side channel attacks in cloud computing,cache-based side channel attack is one that leaks private information of the users based on the shared resources.Here,as the shared resource is the cache,a process can utilize the cache usage of another by cache contention.Cache sharing provides a way for the attackers to gain considerable information so that the key used for encryption can be inferred.Discovering this side channel attack is a challenging task.This requires identification of a feature that influences the attack.Even though there are various techniques available in the literature to mitigate such attacks,an effective solution to reduce the cache-based side channel attack is still an issue.Therefore,a novel fuzzy rule-based mechanism is integrated to detect the cache side channel attackers by monitoring the cache data access(CDA).The factor that determines the attack is CDA in a log file created by the framework during authorization.The proposed framework also utilizes certain security properties including ECC and hashing for the privacy preservation and the decision is made with the aid of a fuzzy logic system.

Side-Channel Attacks in a Real Scenario

Existing Side-Channel Attacks （SCAs） have several limitations and, rather than to be real attack methods, can only be considered to be security evaluation methods. Their limitations are mainly related to the sampling conditions, such as the trigger signal embedded in the source code of the encryption device, and the acquisition device that serves as the encryption-device controller. Apart from it being very difficult for an attacker to add a trigger into the original design before making an attack or to control the encryption device, there is a big gap in the capacity of existing SCAs to pose real threats to cipher devices. In this paper, we propose a new method, the sliding window SCA （SW-SCA）, which can be applied in scenarios in which the acquisition device is independent of the encryption device and for which the encryption source code requires no trigger signal or modification. First, we describe the main issues in existing SCAs, then we theoretically analyze the effectiveness and complexity of our proposed SW-SCA --a method that can incorporate a sliding-window mechanism into almost all of the existing non-profiled SCAs. The experimental results for both simulated and physical traces verify the effectiveness of the SW-SCA and the appropriateness of its theoretical complexity.

Randomized MILP framework for Securing Virtual Machines from Malware Attacks

Cloud computing involves remote server deployments with public net-work infrastructures that allow clients to access computational resources.Virtual Machines(VMs)are supplied on requests and launched without interactions from service providers.Intruders can target these servers and establish malicious con-nections on VMs for carrying out attacks on other clustered VMs.The existing system has issues with execution time and false-positive rates.Hence,the overall system performance is degraded considerably.The proposed approach is designed to eliminate Cross-VM side attacks and VM escape and hide the server’s position so that the opponent cannot track the target server beyond a certain point.Every request is passed from source to destination via one broadcast domain to confuse the opponent and avoid them from tracking the server’s position.Allocation of SECURITY Resources accepts a safety game in a simple format as input andfinds the best coverage vector for the opponent using a Stackelberg Equilibrium(SSE)technique.A Mixed Integer Linear Programming(MILP)framework is used in the algorithm.The VM challenge is reduced by afirewall-based controlling mechanism combining behavior-based detection and signature-based virus detection.The pro-posed method is focused on detecting malware attacks effectively and providing better security for the VMs.Finally,the experimental results indicate that the pro-posed security method is efficient.It consumes minimum execution time,better false positive rate,accuracy,and memory usage than the conventional approach.

Driftor: mitigating cloud-based side-channel attacks by switching and migrating multi-executor virtual machines

Co-residency of different tenants’ virtual machines(VMs) in cloud provides a good chance for side-channel attacks, which results in information leakage. However, most of current defense suffers from the generality or compatibility problem, thus failing in immediate real-world deployment. VM migration, an inherit mechanism of cloud systems, envisions a promising countermeasure, which limits co-residency by moving VMs between servers. Therefore, we first set up a unified practical adversary model, where the attacker focuses on effective side channels. Then we propose Driftor, a new cloud system that contains VMs of a multi-executor structure where only one executor is active to provide service through a proxy, thus reducing possible information leakage. Active state is periodically switched between executors to simulate defensive effect of VM migration. To enhance the defense, real VM migration is enabled at the same time. Instead of solving the migration satisfiability problem with intractable CIRCUIT-SAT, a greedy-like heuristic algorithm is proposed to search for a viable solution by gradually expanding an initial has-to-migrate set of VMs. Experimental results show that Driftor can not only defend against practical fast side-channel attack, but also bring about reasonable impacts on real-world cloud applications.

基于多源数据聚合的神经网络侧信道攻击

基于深度学习的侧信道攻击需要针对密码算法的每一个密钥字节建模并训练,数据采集和模型训练开销大.针对该问题,提出一种基于多源数据聚合的神经网络侧信道攻击方法.为筛选具有良好泛化效果的密钥字节泄露数据进行数据聚合,以AES-128算法为例,先基于16个密钥字节的泄露数据训练16个单密钥字节模型,分别实现对16个密钥字节的恢复;其次,设计一种打分机制评估各单密钥字节模型的泛化效果,通过得分排序筛选出对各密钥字节恢复效果最好的单密钥字节模型;最后,以筛选模型所对应的各密钥字节泄露数据集构建多源数据聚合模型进行训练,实现密钥恢复.实验测试结果表明,多源数据聚合模型具有良好的泛化效果,有效提高了密钥恢复的准确率和效率,降低了恢复密钥所需的能量迹数量,其在采集能量迹较少的情况下依然具有较好的攻击效果.

Performance of Analysis Cognitive Radio with Cooperative Sensing under Malicious Attacks over Nakagami Faded Channels

The different realistic propagation channels are faced frequently the multipath fading environments. The main goal of this system design (cognitive radio network) is to improve the efficiency of spectrum access on a non-interfering basis. This system achieves high utilization for the limited spectrum in order to fulfill needs for all users’ demands which are considered as a problem in wireless communications due to rapidly increasing in wireless applications and service. This system is exposed to attack due to the vulnerabilities existence in this system. So, the main outcome of this paper is to investigate the performance of the cooperative sensing in cognitive radio networks under malicious attacks over different channel impairments, and to illustrate the most suitable individual probability of detection in real faded channel by using Nakagami model. This paper illustrates the effectiveness of the attacks and fading on the performance of spectrum sensing process.

温针灸联合西药治疗风寒袭络型周围性面瘫疗效观察及对面神经功能、表情肌弹性的影响

目的:观察温针灸联合西药治疗风寒袭络型周围性面瘫的疗效及对面神经功能和表情肌弹性的影响。方法:选取94例周围性面瘫患者,按随机数字表法分为观察组及对照组各47例。对照组予以西药治疗,观察组在对照组基础上实施温针灸治疗。2组疗程均为2周。比较2组临床疗效,比较2组治疗前后中医证候评分、面肌表面肌电图指标值、面动脉血流动力学指标值[面动脉舒张末期流速(Vd)、收缩期峰值流速(Vs)、阻力指数(RI)]、表情肌弹性模量值、House-Brackmann(H-B)评分、面部残疾指数躯体功能评分(FDIS)的变化。结果:观察组临床疗效总有效率为95.74%,对照组为82.98%,2组临床疗效比较,差异有统计学意义(P<0.05)。治疗后,2组口角歪斜、面肌瘫痪、眼不能闭、鼻唇沟变浅、味觉减退、耳后疼痛中医证候评分均较治疗前下降(P<0.05),观察组上述6项评分均低于对照组(P<0.05)。治疗后,2组额肌、眼轮匝肌、口轮匝肌表面肌电信号潜伏期均较治疗前缩短,波幅均较治疗前增大,差异均有统计学意义(P<0.05);观察组上述3项表面肌电信号潜伏期均短于对照组,波幅均高于对照组,差异均有统计学意义(P<0.05)。治疗后,2组患侧面动脉Vd、Vs指标值均较治疗前升高,RI指标值均较治疗前下降,差异均有统计学意义(P<0.05);观察组Vd、Vs指标值均高于对照组(P<0.05),RI指标值低于对照组(P<0.05)。治疗后,2组额肌、降口角肌、降下唇肌弹性模量值均较治疗前增加(P<0.05),观察组上述3项弹性模量值均高于对照组(P<0.05)。治疗后,2组H-B评分均较治疗前下降,FDIS评分均较治疗前升高,差异均有统计学意义(P<0.05);观察组H-B评分低于对照组,FDIS评分高于对照组,差异均有统计学意义(P<0.05)。结论:温针灸联合西药治疗风寒袭络型周围性面瘫可改善血液循环和面神经功能,恢复表情肌弹性,缓解临床症状。

一种基于模板的RSA-CRT模约减攻击方法

目前针对RSA-CRT的建模类攻击研究较少,本文以模约减操作为研究对象,提出了一种针对RSA-CRT实现的模板攻击方法.该方法的核心是解决了如何由模约减后中间值的汉明重量恢复RSA-CRT私钥的难题.该方法的特点是基于模约减后中间值的汉明重量模型建模,通过采集选择密文模约减的能量迹进行模板匹配获取模约减后中间值的汉明重量,由汉明重量变化值恢复中间值,进一步恢复RSA-CRT算法的私钥.另外,该方法的优点在于理想情况下,基于中间值汉明重量模型建立的模板之间可以共用,且对中间值以多少位大小建模没有限制,可以选择字节大小,64位大小,甚至私钥p相同大小,实际环境中可根据泄露信息情况进行选取.最后,本文选择对中间值的最低字节进行建模,验证了该方法的可行性,并给出了防护建议.

面向SIMD指令集的SM4算法比特切片优化

SM4算法是中国自主设计的商用分组密码算法,其加解密计算性能成为影响信息系统数据机密性保障的重要因素之一.现有SM4算法优化主要面向硬件设计和软件查表等方向展开研究,分别存在依赖特定硬件环境、效率低下且易遭受侧信道攻击等问题.比特切片技术通过对输入数据重组实现了并行化高效分组密码处理,可以抵御针对缓存的侧信道攻击.然而现有切片分组密码研究对硬件平台相关性强、处理器架构支持单一,并且并行化处理流水启动较慢,面向小规模数据的加解密操作难以充分发挥单指令多数据(single instruction multiple data,SIMD)等先进指令集的优势.针对上述问题,首先提出了一种跨平台的通用切片分组密码算法模型,支持面向不同的处理器指令字长提供一致化的通用数据切片方法.在此基础上,提出了一种面向SIMD指令集的细粒度切片并行处理SM4优化算法,通过细粒度明文切片重组与线性处理优化有效缩短算法启动时间.实验结果表明,相比通用SM4算法,优化的SM4比特切片算法加密速率最高可达438.0 MBps,加密每字节所需的时钟周期最快高达7.0 CPB(cycle/B),加密性能平均提升80.4%~430.3%.

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。

uBlock算法的低延迟一阶门限实现方法

目前已有文献给出了uBlock分组密码算法的侧信道防护方案,但是这些方案不仅延迟较高,难以适用于低延迟高吞吐场景,而且在毛刺探测模型下缺乏可证明安全性.针对这一问题,本文给出了在毛刺探测模型下具有可证明安全性的uBlock算法的低延迟门限实现方案.此外,我们引入了Changing of the Guards技术来避免防护方案在执行过程中需要额外随机数.对于防护方案的安全性,我们用自动化评估工具SILVER验证了S盒的毛刺探测安全性,并用泄露评估技术TVLA(Test Vector Leakage Assessment)验证了防护方案的整个电路的安全性.最后,我们用Design Compiler工具对防护方案的性能消耗情况进行了评估.评估结果显示,与序列化实现方式的uBlock防护方案相比,我们的防护方案的延迟能够减少约95%.

针对ZUC算法硬件实现的相关能量攻击与多粒度时域敏感区域检测

本文通过合理分解模加操作,优化流水线结构,构建ZUC算法硬件实现,并基于FPGA开发板搭建ZUC算法功耗采集平台.构建粗细粒度时域敏感区域的泄漏检测方法,利用移动平均算子,发掘高信噪比风险区域,采用自相关滤波器与峰值检测算子,发掘具有明显重复特征的运算区间,并对泄漏高风险区域进行标定,实现高精度的泄漏风险定位.通过分析ZUC算法的脆弱性,本文提出一种基于选择初始向量IV的CPA攻击方案,对输入的IV信息进行选择,通过固定部分明文的方法有效提高采集信号的信噪比,并采集实际3000条功耗曲线,在算法初始化首轮,成功提取8 bit密钥信息,从而证明该方案的有效性,对ZUC算法的硬件实现进行侧信道防护是必要的.总结ZUC算法侧信道防护方案,对比方案优劣.

x86处理器向量条件访存指令安全脆弱性分析

单指令多数据流(Single Instruction stream,Multiple Data streams,SIMD)是一种利用数据级并行提高处理器性能的技术,旨在利用多个处理器并行执行同一条指令增加数据处理的吞吐量.随着大数据、人工智能等技术的兴起,人们对数据并行化处理的需求不断提高,这使得SIMD技术愈发重要.为了支持SIMD技术,Intel和AMD等x86处理器厂商从1996年开始在其处理器中陆续引入了MMX(MultiMedia Extensions)、SSE(Streaming SIMD Extensions)、AVX(Advanced Vector eXtensions)等SIMD指令集扩展.通过调用SIMD指令,程序员能够无需理解SIMD技术的硬件层实现细节就方便地使用它的功能.然而,随着熔断、幽灵等处理器硬件漏洞的发现,人们逐渐认识到并行优化技术是一柄双刃剑,它在提高性能的同时也能带来安全风险.本文聚焦于x86 SIMD指令集扩展中的VMASKMOV指令,对它的安全脆弱性进行了分析.本文的主要贡献如下:(1)利用时间戳计数器等技术对VMASKMOV指令进行了微架构逆向工程,首次发现VMASKMOV指令与内存页管理和CPU Fill Buffer等安全风险的相关性;(2)披露了一个新的处理器漏洞EvilMask,它广泛存在于Intel和AMD处理器上,并提出了3个EvilMask攻击原语:VMASKMOVL+Time(MAP)、VMASKMOVS+Time(XD)和VMASKMOVL+MDS,可用于实施去地址空间布局随机化攻击和进程数据窃取攻击;(3)给出了2个EvilMask概念验证示例(Proof-of-Concept,PoC)验证了EvilMask对真实世界的信息安全危害;(4)讨论了针对EvilMask的防御方案,指出最根本的解决方法是在硬件层面上重新实现VMASKMOV指令,并给出了初步的实现方案.

基于机器学习的多目标缓存侧信道攻击检测模型

当前缓存侧信道攻击检测技术主要针对单一攻击模式,对2~3种攻击的检测方法有限,无法全面覆盖;此外,尽管对单一攻击的检测精度高,但随着攻击数增加,精度下降,容易产生误报。为了有效检测缓存侧信道攻击,利用硬件性能计数器(HPC)采集不同的缓存侧信道攻击特征,结合机器学习算法,提出一种基于机器学习的多目标缓存侧信道攻击检测模型。首先,分析不同缓存侧信道攻击方式的相关特征,精选关键特征并收集数据集;其次,进行独立的训练,建立针对每种攻击方式的检测模型;最后,在检测时将测试数据并行送入多个模型中,根据检测结果判断是否存在某种缓存侧信道攻击。实验结果显示,所提模型在检测Flush+Reload、Flush+Flush和Prime+Probe这3种缓存侧信道攻击时,分别达到99.91%、98.69%和99.54%的高准确率,即使在同时存在多种攻击的情况下,也能准确识别各种攻击方式。

基于射频侧信道的密码芯片安全测评方法

侧信道攻击是针对密码芯片的主要威胁之一,对密码芯片进行抗侧信道攻击能力的评估已成为密码测评的重要内容.CC标准是当前认可度最高的密码评估认证标准之一,但仅对传统的侧信道测评方法进行规范,难以应对未来可能出现的侧信道攻击.射频侧信道是一种新型的泄露途径,CC标准未将该侧信道纳入测评的执行内容.基于以上问题,本文基于射频侧信道的泄露原理设计并搭建了原型测评平台,该平台可一体化实现射频侧信道信号的采集、预处理和分析工作.在测评实验阶段,以一款执行AES加密通信的蓝牙SOC作为待测芯片,采用测试向量泄露评估技术(test vector leakage assessment,TVLA)对其S盒运算过程进行泄露评估,单字节泄露t值最大可达43.97,最远的泄露距离为10米左右;其次采用Profile攻击方法对其实施抗攻击测试,利用25000条泄露曲线在攻击距离为5米处成功恢复了AES算法的全部密钥,测试结果进一步验证了该测评平台的科学性和可行性.本文的工作可为密码测评标准的完善提供新依据,为安全测评人员提供新的测评思路.