Design and Implementation of Novel BRISI Lightweight Cipher for Resource Constrained Devices

The Internet of Things (IoT) and cyber-physical systems (CPS) has grown exponentially over the recent years, has motivated the development and deployment of the low resource devices for a wide range of applications in the IoT. Many such resource constrained devices are deployed to match the heterogeneous application requirements of IoT and CPS systems, wherein privacy and security have emerged, as the most difficult challenges, as the constrained devices are not been designed to have security features. This paper presents a lightweight cipher, based on ARX (Addition-Modulo, Rotation and XOR) operations, Fiestel structure, an amalgamation of BRIGHT and SIMON structure, hence the name BRISI. The cipher encrypts 32-bit plaintext using 64-bit key. The software implementation is performed using MATLAB tool and it fulfils the Avalanche criterion, Key-sensitivity, correlation coefficient, entropy and histogram. The proposed design is simulated using Xilinx Vivado and is implemented on Nexys-4 DDR Artix-7 and Basys-3 Artix-7 FPGA family and is evaluated for (LUT and register) power and timing     

Advanced mobile and wearable systems

The recent spectacular progress in the microelectronic, information, communication, material and sensor technologies created a big stimulus towards development of smart communicating cyber-physical systems (CPS) and Internet of Things (IoT). CPS and IoT are undergoing an explosive growth to a large degree related to advanced mobile systems like smart automotive and avionic systems, mobile robots and wearable devices. The huge and rapidly developing markets of sophisticated mobile cyber-physical systems represent great opportunities, but these opportunities come with a price of unusual system complexity, as well as, stringent and difficult to satisfy requirements of many modern applications. Specifically, smart cars and various wearable systems to a growing degree involve big instant data from multiple complex sensors or other systems, and are required to provide continuous autonomous service in a long time. In consequence, they demand a guaranteed (ultra-)high performance and/or (ultra-)low energy consumption, while requiring a high reliability, safety and security. To adequately address these demands, sophisticated embedded computing and embedded design technologies are needed. After an introduction to modern mobile systems, this paper discusses the huge heterogeneous area of these systems, and considers serious issues and challenges in their design. Subsequently, it discusses the embedded computing and design technologies needed to adequately address the issues and overcome the challenges in order to satisfy the stringent requirements of the modern mobile systems.     

物联网安全测评技术综述

近年来,物联网大规模应用于智能制造、智能家居、智慧医疗等产业,物联网的安全问题日益突出,给物联网的发展带来了前所未有的挑战。安全测评技术是保障物联网安全的重要手段,在物联网应用的整个开发生命周期都需要进行安全测评工作,以保证物联网服务的安全性和健壮性。物联网节点面临计算能力、体积和功耗受限等挑战,智慧城市等应用场景提出了大规模泛在异构连接和复杂跨域的需求。本文首先总结了目前物联网中常用的安全测评方法和风险管理技术;然后从绿色、智能和开放三个方面分析物联网安全技术的发展现状和存在的安全问题,并总结了物联网安全测评面临的挑战以及未来的研究方向。     

信息物理融合系统(CPS)研究综述

信息物理融合系统(Cyber-Physical Systcms, CPS)是将计算资源与物理资源紧密结合与协调的产物,它将改变人类与物理世界的交互方式。作为物联网的演进,CPS已经引起了国内外相关科研机构、政府部门和社会的广泛关注。介绍和阐述了CPS的定义、系统结构和特性,重点研究和讨论了CPS的理论技术体系、对计算机科学领域带来的重大挑战以及研究现状,最后展望了CPS的研究动向。     

车联网：物联网在城市交通网络中的应用

阐述了“物联网”和“车辆网”这两个热门概念的内涵和外延。通过分析两者的发展历程、历史沿革和相互关系,比较它们在实际生活中的应用, 认为车联网可以看作物联网在城市交通网络中的典型应用,展望了车联网在服务与应用方面的美好愿景。以此为基础,讨论了车联网实现的关键技术,并介绍了一个过渡型构建方案。最后,详细讨论了在物联网和车联网领域里国内外学术研究现状。     

Industry 4.0 as a Cyber-Physical System study

Advances in computation and communication are taking shape in the form of the Internet of Things, Machine-to-Machine technology, Industry 4.0, and Cyber-Physical Systems (CPS). The impact on engineering such systems is a new technical systems paradigm based on ensembles of collaborating embedded software systems. To successfully facilitate this paradigm, multiple needs can be identified along three axes: (i) online configuring an ensemble of systems, (ii) achieving a concerted function of collaborating systems, and (iii) providing the enabling infrastructure. This work focuses on the collaborative function dimension and presents a set of concrete examples of CPS challenges. The examples are illustrated based on a pick and place machine that solves a distributed version of the Towers of Hanoi puzzle. The system includes a physical environment, a wireless network, concurrent computing resources, and computational functionality such as, service arbitration, various forms of control, and processing of streaming video. The pick and place machine is of medium-size complexity. It is representative of issues occurring in industrial systems that are coming online. The entire study is provided at a computational model level, with the intent to contribute to the model-based research agenda in terms of design methods and implementation technologies necessary to make the next generation systems a reality.     

面向智慧城市的数据驱动信息物理系统安全威胁分析模型与方法

信息物理系统（CPS）是一个集成计算、通信和物理过程的混成系统,在智慧城市中占据至关重要的地位,其安全问题面临许多挑战.本文首先建立信息物理系统安全威胁分析模型,给出CPS各个组成部件的安全威胁,然后提出了信息物理系统的威胁关联分析方法,并以智能电网为例给出实验测试结果.结果表明,该方法能实现快速大规模安全威胁建模和自动化分析,为智慧城市中的关键信息基础设施提供技术支撑.最后,本文总结了智慧城市中信息物理系统的安全威胁研究进展和未来研究方向.     

物联网取证综述

物联网时代的到来为人们带来极大的便利,但也使得网络攻击的范围更广,带来了新的网络空间安全威胁.海量的物联网设备保留了丰富的数字痕迹,可以洞悉人们在家中和其他场所的各种行为,这对于数字取证具有重要意义.针对物联网取证展开深入讨论,从物联网取证的兴起、发展和研究现状入手,进一步探讨数字取证模型、1-2-3区域方法模型、并行...     

物联网安全威胁与安全模型

随着物联网应用的发展和普及利用,针对物联网的攻击事件日益增多且危害严重。目前面对物联网安全问题主要采用被动补救的方式,缺乏对物联网安全的体系化思考和研究。本论文首先介绍物联网系统架构和各实体的发展,然后分析物联网面临的多层次安全威胁,包括各实体自身的安全威胁,也包括跨域的安全威胁。其中,实体自身安全威胁涉及到云平台、设备端、管道、云端交互。物联网跨域安全威胁包含4个方面:多域级联攻击、物理域的冲突与叠加、信息域对物理域进行非预期的控制、信息域对物理域输入的理解不全面。在此基础上,论文研究了基于PDRR网络安全体系的物联网安全模型,包含安全防护、安全检测、响应、恢复4个维度。安全防护包含认证、授权与访问控制、通信加密等技术,需要考虑物联网种类繁多,规模巨大,异构等特点进行设计与实施。安全检测需要对各实体进行入侵检测、在线安全监测、脆弱性检测以及恶意代码检测。其中,在线安全监测获取系统内部设备、应用程序的行为、状态、是否存在已知脆弱性等。脆弱性检测偏向于对未知脆弱性进行深度挖掘。在响应阶段,除了配合相关部门机关完成安全行动资源配置、态势感知等响应工作外,还需要进行入侵事件的分析与响应,漏洞与恶意代码的公告与修复,以及安全防护加固与检测规则的更新。在恢复阶段,需要对关键数据进行恢复,并对系统进行升级与恢复。最后论文进行总结并提出值得关注的研究方向。     

Confidential smart-sensing framework in the IoT era

With the revolution of the Internet technology, smart-sensing applications and the Internet of Things (IoT) are coupled in critical missions. Wireless sensor networks (WSNs), for example, present the main enabling technology in IoT architectures and extend the spectrum of their smart applications. However, this technology has limited resources and suffers from several vulnerabilities and security issues. Since the wireless networks used by this technology are deployed in open areas, several challenges are faced by the service provider in terms of privacy and the quality of service. Encryption can be a good solution to preserve confidentiality and privacy, but it raises serious problems concerning time latency and performance. In this paper, we propose agile framework that enables authentication, confidentiality and integrity while collecting the sensed data by using elliptic curve cryptography.     

Multi Level Key Exchange and Encryption Protocol for Internet of Things (IoT)

The burgeoning network communications for multiple applications such as commercial, IoT, consumer devices, space, military, and telecommunications are facing many security and privacy challenges. Over the past decade, the Internet of Things (IoT) has been a focus of study. Security and privacy are the most important problems for IoT applications and are still facing huge difficulties. To promote this high-security IoT domain and prevent security attacks from unauthorized users, keys are frequently exchanged through a public key exchange algorithm. This paper introduces a novel algorithm based on Elliptic Curve Cryptography(ECC) for multi-level Public Key Exchange and Encryption Mechanism. It also presents a random number generation technique for secret key generation and a new authentication methodology to enhance the security level. Finally, in terms of security, communication and computational overhead, the performance analysis of the proposed work is compared with the existing protocols.     

Data Security Storage Model of the Internet of Things Based on Blockchain

With the development of information technology, the Internet of Things (IoT) has gradually become the third wave of the worldwide information industry revolution after the computer and the Internet. The application of the IoT has brought great convenience to people’s production and life. However, the potential information security problems in various IoT applications are gradually exposed and people pay more attention to them. The traditional centralized data storage and management model of the IoT is easy to cause transmission delay, single point of failure, privacy disclosure and other problems, and eventually leads to unpredictable behavior of the system. Blockchain technology can effectively improve the operation and data security status of the IoT. Referring to the storage model of the Fabric blockchain project, this paper designs a data security storage model suitable for the IoT system. The simulation results show that the model is not only effective and extensible, but also can better protect the data security of the Internet of Things.     

物联网安全威胁与安全模型CSCD

随着物联网应用的发展和普及利用,针对物联网的攻击事件日益增多且危害严重。目前面对物联网安全问题主要采用被动补救的方式,缺乏对物联网安全的体系化思考和研究。本论文首先介绍物联网系统架构和各实体的发展,然后分析物联网面临的多层次安全威胁,包括各实体自身的安全威胁,也包括跨域的安全威胁。其中,实体自身安全威胁涉及到云平台、设备端、管道、云端交互。物联网跨域安全威胁包含4个方面:多域级联攻击、物理域的冲突与叠加、信息域对物理域进行非预期的控制、信息域对物理域输入的理解不全面。在此基础上,论文研究了基于PDRR网络安全体系的物联网安全模型,包含安全防护、安全检测、响应、恢复4个维度。安全防护包含认证、授权与访问控制、通信加密等技术,需要考虑物联网种类繁多,规模巨大,异构等特点进行设计与实施。安全检测需要对各实体进行入侵检测、在线安全监测、脆弱性检测以及恶意代码检测。其中,在线安全监测获取系统内部设备、应用程序的行为、状态、是否存在已知脆弱性等。脆弱性检测偏向于对未知脆弱性进行深度挖掘。在响应阶段,除了配合相关部门机关完成安全行动资源配置、态势感知等响应工作外,还需要进行入侵事件的分析与响应,漏洞与恶意代码的公告与修复,以及安全防护加固与检测规则的更新。在恢复阶段,需要对关键数据进行恢复,并对系统进行升级与恢复。最后论文进行总结并提出值得关注的研究方向。     

物联网设备漏洞挖掘技术研究综述

随着物联网设备的迅速发展和广泛应用,物联网设备的安全也受到了严峻的考验。安全漏洞大量存在于物联网设备中,而通用漏洞挖掘技术不再完全适用于物联网设备。近几年,针对物联网设备漏洞的挖掘技术逐渐成为热点。本文将分析物联网设备漏洞挖掘技术面临的挑战与机遇,然后从静态分析,动态模糊测试,以及同源性分析三个方面来介绍物联网设备漏洞挖掘技术的研究进展。最后本文将对今后该领域的研究重点和方向进行讨论和展望。     

物联网无线协议安全综述

近些年来,随着物联网的快速发展,其应用场景涵盖智慧家庭、智慧城市、智慧医疗、智慧工业以及智慧农业.相比于传统的以太网,物联网能够将各种传感设备与网络结合起来,实现人、电脑和物体的互联互通.形式多样的物联网协议是实现物联网设备互联互通的关键,物联网协议拥有不同的协议栈,这使得物联网协议往往能表现出不同的特性.目前应用较广...     

NVM Storage in IoT Devices: Opportunities and Challenges

Edge storage stores the data directly at the data collection point, and does not need to transmit the collected data to the storage central server through the network. It is a critical technology that supports applications such as edge computing and 5G network applications, with lower network communication overhead, lower interaction delay and lower bandwidth cost. However, with the explosion of data and higher real-time requirements, the traditional Internet of Things (IoT) storage architecture cannot meet the requirements of low latency and large capacity. Non-volatile memory (NVM) presents new possibilities regarding this aspect. This paper classifies the different storage architectures based on NVM and compares the system goals, architectures, features, and limitations to explore new research opportunities. Moreover, the existing solutions to reduce the write latency and energy consumption and increase the lifetime of NVM IoT storage devices are analyzed. Furthermore, we discuss the security and privacy issues of IoT devices and compare the mainstream solutions. Finally, we present the opportunities and challenges of building IoT storage systems based on NVM.     

Correction to: Uniform and scalable sampling of highly configurable systems

Empirical Software Engineering - Testing Internet of Things (IoT) systems is challenging. This is not only because of the various aspects of IoT systems, such as software, hardware, and network...     

NBC-MAIDS: Naïve Bayesian classification technique in multi-agent system-enriched IDS for securing IoT against DDoS attacks

Internet of Things (IoT) makes physical objects and devices interact with each other through wireless technologies. IoT is expected to deliver a significant role in our lives in near future. However, at the current stage, IoT is vulnerable to various kinds of security threats just like other wired and wireless networks. Our work mainly focuses on protecting an IoT infrastructure from distributed denial-of-service attacks generated by the intruders. We present a new approach of using Naïve Bayes classification algorithm applied in intrusion detection systems (IDSs). IDSs are deployed in the form of multi-agents throughout the network to sense the misbehaving or irregular traffic and actions of nodes. In the paper, we also discuss the fundamental concepts related to our work and recent research done in similar area.     

物联网技术及其安全性研究

针对物联网_技术的发展趋势问题,基于物联网的体系结构和关键技术,分析了物联网的安全需求与相关特性,构建了一个以RFID安全和隐私保护为重点的物联网安全框架,提出了应对物联网所面临的安全挑战的解决途径,最后对物联网未来发展趋势作了展望.     

Artificial Algae Optimization with Deep Belief Network Enabled Ransomware Detection in IoT Environment

The Internet of Things (IoT) has gained more popularity in research because of its large-scale challenges and implementation. But security was the main concern when witnessing the fast development in its applications and size. It was a dreary task to independently set security systems in every IoT gadget and upgrade them according to the newer threats. Additionally, machine learning (ML) techniques optimally use a colossal volume of data generated by IoT devices. Deep Learning (DL) related systems were modelled for attack detection in IoT. But the current security systems address restricted attacks and can be utilized outdated datasets for evaluations. This study develops an Artificial Algae Optimization Algorithm with Optimal Deep Belief Network (AAA-ODBN) Enabled Ransomware Detection in an IoT environment. The presented AAA-ODBN technique mainly intends to recognize and categorize ransomware in the IoT environment. The presented AAA-ODBN technique follows a three-stage process: feature selection, classification, and parameter tuning. In the first stage, the AAA-ODBN technique uses AAA based feature selection (AAA-FS) technique to elect feature subsets. Secondly, the AAA-ODBN technique employs the DBN model for ransomware detection. At last, the dragonfly algorithm (DFA) is utilized for the hyperparameter tuning of the DBN technique. A sequence of simulations is implemented to demonstrate the improved performance of the AAA-ODBN algorithm. The experimental values indicate the significant outcome of the AAA-ODBN model over other models.