An Active Deception Defense Model Based on Address Mutation and Fingerprint Camouflage

The static and predictable characteristics of cyber systems give attackers an asymmetric advantage in gathering useful information and launching attacks.To reverse this asymmetric advantage,a new defense idea,called Moving Target Defense(MTD),has been proposed to provide additional selectable measures to complement traditional defense.However,MTD is unable to defeat the sophisticated attacker with fingerprint tracking ability.To overcome this limitation,we go one step beyond and show that the combination of MTD and Deception-based Cyber Defense(DCD)can achieve higher performance than either of them.In particular,we first introduce and formalize a novel attacker model named Scan and Foothold Attack(SFA)based on cyber kill chain.Afterwards,we develop probabilistic models for SFA defenses to provide a deeper analysis of the theoretical effect under different defense strategies.These models quantify attack success probability and the probability that the attacker will be deceived under various conditions,such as the size of address space,and the number of hosts,attack analysis time.Finally,the experimental results show that the actual defense effect of each strategy almost perfectly follows its probabilistic model.Also,the defense strategy of combining address mutation and fingerprint camouflage can achieve a better defense effect than the single address mutation.

Distributed Application Addressing in 6G Network

To ensure the extreme performances of the new 6G services,applications will be deployed at deep edge,resulting in a serious challenge of distributed application addressing.This paper traces back the latest development of mobile network application addressing,analyzes two novel addressing methods in carrier network,and puts forward a 6G endogenous application addressing scheme by integrating some of their essence into the 6G network architecture,combining the new 6G capabilities of computing&network convergence,endogenous intelligence,and communication-sensing integration.This paper further illustrates how that the proposed method works in 6G networks and gives preliminary experimental verification.

Enhanced DDoS Detection Using Advanced Machine Learning and Ensemble Techniques in Software Defined Networking

Detecting sophisticated cyberattacks,mainly Distributed Denial of Service(DDoS)attacks,with unexpected patterns remains challenging in modern networks.Traditional detection systems often struggle to mitigate such attacks in conventional and software-defined networking(SDN)environments.While Machine Learning(ML)models can distinguish between benign and malicious traffic,their limited feature scope hinders the detection of new zero-day or low-rate DDoS attacks requiring frequent retraining.In this paper,we propose a novel DDoS detection framework that combines Machine Learning(ML)and Ensemble Learning(EL)techniques to improve DDoS attack detection and mitigation in SDN environments.Our model leverages the“DDoS SDN”dataset for training and evaluation and employs a dynamic feature selection mechanism that enhances detection accuracy by focusing on the most relevant features.This adaptive approach addresses the limitations of conventional ML models and provides more accurate detection of various DDoS attack scenarios.Our proposed ensemble model introduces an additional layer of detection,increasing reliability through the innovative application of ensemble techniques.The proposed solution significantly enhances the model’s ability to identify and respond to dynamic threats in SDNs.It provides a strong foundation for proactive DDoS detection and mitigation,enhancing network defenses against evolving threats.Our comprehensive runtime analysis of Simultaneous Multi-Threading(SMT)on identical configurations shows superior accuracy and efficiency,with significantly reduced computational time,making it ideal for real-time DDoS detection in dynamic,rapidly changing SDNs.Experimental results demonstrate that our model achieves outstanding performance,outperforming traditional algorithms with 99%accuracy using Random Forest(RF)and K-Nearest Neighbors(KNN)and 98%accuracy using XGBoost.

Application Strategies of Automatic Addressable Single-Lamp Control Technology in Tunnel Lighting

The article mainly studies the application strategy of automatic addressable single-lamp control technology in tunnel lighting.It encompasses an introduction to this technology,an analysis of the tunnel lighting system using automatic addressable single-lamp control technology,and outlines the main development direction for this technology in modern tunnel lighting.The aim is to offer insights that can inform the rational deployment of this technology,thereby enhancing the lighting control effectiveness in modern tunnels and meeting their specific lighting requirements more effectively.

Conformal Human–Machine Integration Using Highly Bending‑Insensitive,Unpixelated,and Waterproof Epidermal Electronics Toward Metaverse

Efficient and flexible interactions require precisely converting human intentions into computer-recognizable signals,which is critical to the breakthrough development of metaverse.Interactive electronics face common dilemmas,which realize highprecision and stable touch detection but are rigid,bulky,and thick or achieve high flexibility to wear but lose precision.Here,we construct highly bending-insensitive,unpixelated,and waterproof epidermal interfaces(BUW epidermal interfaces)and demonstrate their interactive applications of conformal human–machine integration.The BUW epidermal interface based on the addressable electrical contact structure exhibits high-precision and stable touch detection,high flexibility,rapid response time,excellent stability,and versatile“cut-and-paste”character.Regardless of whether being flat or bent,the BUW epidermal interface can be conformally attached to the human skin for real-time,comfortable,and unrestrained interactions.This research provides promising insight into the functional composite and structural design strategies for developing epidermal electronics,which offers a new technology route and may further broaden human–machine interactions toward metaverse.

A Scalable Interconnection Scheme in Many-Core Systems

Recent architectures of multi-core systems may have a relatively large number of cores that typically ranges from tens to hundreds;therefore called many-core systems.Such systems require an efficient interconnection network that tries to address two major problems.First,the overhead of power and area cost and its effect on scalability.Second,high access latency is caused by multiple cores’simultaneous accesses of the same shared module.This paper presents an interconnection scheme called N-conjugate Shuffle Clusters(NCSC)based on multi-core multicluster architecture to reduce the overhead of the just mentioned problems.NCSC eliminated the need for router devices and their complexity and hence reduced the power and area costs.It also resigned and distributed the shared caches across the interconnection network to increase the ability for simultaneous access and hence reduce the access latency.For intra-cluster communication,Multi-port Content Addressable Memory(MPCAM)is used.The experimental results using four clusters and four cores each indicated that the average access latency for a write process is 1.14785±0.04532 ns which is nearly equal to the latency of a write operation in MPCAM.Moreover,it was demonstrated that the average read latency within a cluster is 1.26226±0.090591 ns and around 1.92738±0.139588 ns for read access between cores from different clusters.

Comparative Evaluation of Data Mining Algorithms in Breast Cancer

Unchecked breast cell growth is one of the leading causes of death in women globally and is the cause of breast cancer.The only method to avoid breast cancer-related deaths is through early detection and treatment.The proper classification of malignancies is one of the most significant challenges in the medical industry.Due to their high precision and accuracy,machine learning techniques are extensively employed for identifying and classifying various forms of cancer.Several data mining algorithms were studied and implemented by the author of this review and compared them to the present parameters and accuracy of various algorithms for breast cancer diagnosis such that clinicians might use them to accurately detect cancer cells early on.This article introduces several techniques,including support vector machine(SVM),K star(K∗)classifier,Additive Regression(AR),Back Propagation Neural Network(BP),and Bagging.These algorithms are trained using a set of data that contains tumor parameters from breast cancer patients.Comparing the results,the author found that Support Vector Machine and Bagging had the highest precision and accuracy,respectively.Also,assess the number of studies that provide machine learning techniques for breast cancer detection.

Shared Cache Based on Content Addressable Memory in a Multi-Core Architecture

Modern shared-memory multi-core processors typically have shared Level 2(L2)or Level 3(L3)caches.Cache bottlenecks and replacement strategies are the main problems of such architectures,where multiple cores try to access the shared cache simultaneously.The main problem in improving memory performance is the shared cache architecture and cache replacement.This paper documents the implementation of a Dual-Port Content Addressable Memory(DPCAM)and a modified Near-Far Access Replacement Algorithm(NFRA),which was previously proposed as a shared L2 cache layer in a multi-core processor.Standard Performance Evaluation Corporation(SPEC)Central Processing Unit(CPU)2006 benchmark workloads are used to evaluate the benefit of the shared L2 cache layer.Results show improved performance of the multicore processor’s DPCAM and NFRA algorithms,corresponding to a higher number of concurrent accesses to shared memory.The new architecture significantly increases system throughput and records performance improvements of up to 8.7%on various types of SPEC 2006 benchmarks.The miss rate is also improved by about 13%,with some exceptions in the sphinx3 and bzip2 benchmarks.These results could open a new window for solving the long-standing problems with shared cache in multi-core processors.

LETTERS

Your comments are welcome!Please feel free to contact us with your personal stories or vivid pictures!Address:24 Baiwanzhuang St.,Xicheng Dist.,Beijing,100037 E-mail:chinatodaynews@aliyun.com I am a professor at Renmin University in Beijing and former head of the Beijing office of Spanish news agency Agencia EFE.

Challenges and Countermeasures for Integrating the Protection of Environmental Rights into Actions for Addressing Climate Change

Climate change,which is the result of human activities,has wide-ranging impact.It poses a serious threat to human rights.Environmental rights are where the protection of the ecological environment and the development of human rights intersect.In view of the close relationship between the actions for addressing climate change and environmental rights,China should integrate the protection of environmental rights into the actions for addressing climate change,so as to achieve simultaneous development of both.In the process of coping with climate change,the right to climate stability that mainly pursues a“harmless”environment and the right to a more livable climate that pursues a“beautiful eco-environment”are specific manifestations of environmental rights and should be the priority of protection efforts.However,there are still some obstacles to achieving the coordinated development of the efforts to address climate change and the protection of environmental rights because traditional rights protection methods mainly give individuals subjective rights with the power to claim and are thus difficult to meet the needs of environmental rights protection in the context of climate change,and there are inherent value differences between responding to climate change and the realization of other human rights.Building a multi-level national obligation system to address climate change,giving full play to the role of courts in responding to climate change through moderate judicial activism,and coordinating the efforts to cope with climate change and the development of human rights under the guidance of a holistic system view are effective ways to overcome the aforementioned difficulties.

An Analysis of Chinese Address Terms From the Perspective of Speech Act Theory

Address terms are an important resource for conveying relationships.In daily interactions,the use of address terms is unavoidable.Therefore,the choose of address terms is particularly critical to make communicate smoothly with people.Previous scholars have studied address terms from a wide range of perspectives.But there is not much research on Chinese address terms based on speech act theory,which is put forward by John Langshaw Austin.By observing communicative conversations,several findings have been emerged from the analysis.They are professional title,affectionate address terms,and common address terms.These findings express the existential significance of address terms,which are the premise for people to maximize their illocutionary act when communicating.Correct understanding and grasp of the use of address terms is conductive to unfolding the communicative dialogue more smoothly.

CAM辅助的哈希表查找性能分析

现有大规模IP流处理方式中,哈希机制极具优势而在高速网络环境下被广泛采用,但其查找性能直接受限于访存次数。该文主要研究了CAM(Content Addressable Memory)辅助的哈希表(CAHT)查找性能。利用合理的近似,推导了单函数CAHT查找时平均访存次数的理论下限;结合单函数CAHT的分析结论给出了多函数CAHT查找时达到平均访存次数最小的条件。最后,使用实际网络数据验证了分析结果的有效性,为准确评估CAHT处理能力提供了必要的理论依据。

一种支持多维资源描述的高效P2P路由算法

在分析现有P2P(peer to peer)路由算法的基础上,提出了一种基于二阶矩定位、支持多维资源数据描述的高效资源路由算法——FAN(flabellate addressable network)路由算法.FAN算法将节点映射到统一的多维笛卡尔空间,并以节点相对空间原点的二阶矩作为子空间管理和资源搜索的依据.FAN路由算法具有O(log(N/k))的高路由效率,在节点加入和退出FAN网络时,更新路由信息的代价为O(klog(N/k)).实验结果表明,FAN路由算法具有路由效率高、维护代价小的优点,是一种P2P环境中支持多维资源数据描述的高效结构化资源路由算法.而且,目前部分基于CAN(content-addressable network)网络的改进算法也可以在FAN网络中适用,并获得更好的路由效率和更低的维护代价.

基于XML和COM(MAPI)的通用地址簿设计

步入信息时代,邮箱、传真机已经成为人们通信的重要平台,一般的传真机、邮箱都携带自身的地址簿,并不是所有邮箱、传真机的地址簿都可以兼容。通用的地址簿,对于开发一个邮件系统或传真机的驱动就可以直接采用,提高效率以及代码的重用性。目前使用较多的地址簿有Microsoft的WAB(Windows address book)、Outlook Address Book等,但有些地址簿不兼容,即一种地址簿格式不能导入到另一种地址簿中,通过Microsoft提供的MAPI(Messaging Application Programming Interface)探讨了如何使用这种COM组件技术和XML来实现一个简单的支持多种格式的地址簿管理工具。

ARP协议简介及ARP木马防治

介绍了ARP协议的工作原理。针对ARP的特点,在局域网内查找感染ARP木马的主机,提出防治ARP木马的相关办法。

网络地址转换器友好通讯构件的设计与实现

为了解决IPv4地址匮乏问题,网络中部署了大量的NAT设备,而NAT的部署破坏了Internet端到端的特性,并给不断发展的网络多媒体应用带来了障碍。针对该问题,提出一套系统化的NAT穿透方案,实现了一种具有NAT穿透能力的构件,可平滑地植入现有的流媒体产品中,并降低软件开发的复杂度,从而可很好地解决NAT部署带给流媒体的障碍。

NAT专网下的数据流穿透研究与实现

设置NAT能有效防止外部用户访问局域网内部资源,但却给同机构不同地域局域网间访问带来很多限制,已布署的实时流媒体软件因不具备NAT穿透功能,从而导致传输受阻,单方面地去改造这些流媒体软件,将会引发诸如:时间、成本、安全性等一系列问题。本文提供的agent原型,利用端口映射机制,代理穿透通道并对它们进行动态分配、释放及安全认证,从而打破NAT屏障。Agent同时提供很好的可扩展性,可方便集成到其它传输系统之中,具有极高的使用价值。

我国涉外人员英文名片的撰写和翻译

名片，根据其持有者不同的交际意图，英语中可分别称作ｖｉｓｉｔｉｎｇｃａｒｄ，ｃａｌｉｎｇｃａｒｄ，ｎａｍｅｃａｒｄ，ｂｕｓｉｎｅｓｓｃａｒｄ，或干脆简称为ｃａｒｄ。按照《现代汉语词典》的释义，它是指“旧时拜访人或跟人相互联系时所用的长方形纸片，上面印...

Web服务寻址以及在WSE中的实现

SOAP协议规范了Web服务之间传递消息的规范格式,保证了服务间的消息交换不受底层传输协议的影响.但SOAP协议在设计时并没有规范Web服务之间的寻址问题,影响了Web服务的传输中立特性.WS-Addressing在web服务寻址上提供了传输中立的机制,通过WS-Addressing服务寻址与传输协议无关,Web服务访问不再局限于HTTP协议.WSE完全支持WS-Addressing,并降低了基于WS-Addressing的Web服务程序开发的过程.

VRRP路由协议介绍及配置

作为信息化应用的载体——计算机网络的可靠性受到越来越多的重视.VRRP(虚拟路由器冗余协议)是一种选择协议,它的优势在于不需要在终端进行动态路由和路由发现协议的配置,即可获得一个高可靠性的缺省路由通道.通过以S9300系列交换机为载体,分析和研究VRRP虚拟路由器冗余性协议的原理和配置,实现园区网络的路由冗余.