Biblio

Due to the rise of huge population in mankind and the large variety of upcoming utilization of power, the energy requirement has substantially increased. Smart Grid is a very important part of the Smart Cities initiative and is one of the crucial components in distribution and reconciliation of energy. Security of the smart grid infrastructure, which is an integral part of the smart grid framework, intended at transitioning the conventional power grid system into a robust, reliable, adaptable and intelligent energy utility, is an impending problem that needs to be arrested quickly. With the increasingly intensifying integration of smart devices in the smart grid infrastructure with other interconnected applications and the communication backbone is compelling both the energy users and the energy utilities to thoroughly look into the privacy and security issues of the smart grid. In this paper, we present challenges of the existing security mechanisms deployed in the smart grid framework and we tried to bring forward the unresolved problems that would highlight the security aspects of Smart Grid as a challenging area of research and development in the future.

Smart grid consists of smart devices to control, record and analyze the grid power flow. All these devices belong to the latest technology, which is used to interact through the wireless network making the grid communication network vulnerable to cyber attack. This paper deals with a novel approach using altering the Internet Protocol (IP) address of the smart grid communication network using fuzzy logic according to the degree of node. Through graph theory approach Wireless Communication Network (WCN) is designed by considering each node of the system as a smart sensor. In this each node communicates with other nearby nodes for exchange of data. Whenever there is cyber intrusion the WCN change its IP using proposed fuzzy rules, where higher degree nodes are given the preference to change first with extreme IP available in the system. Using the proposed algorithm, different IEEE test systems are simulated and compared with existing Dynamic Host Configuration Protocol (DHCP). The fuzzy logic approach reduces the data loss and improves the system response time.

The deployment of smart devices in IoT applications are increasing with tremendous pace causing severe security concerns, as it trade most of private information. To counter that security issues in low resource applications, lightweight cryptographic algorithms have been introduced in recent past. In this paper we propose efficient hardware architecture of piccolo lightweight algorithm uses 64 bits block size with variable key size of length 80 and 128 bits. This paper introduces novel hardware architecture of piccolo-80, to supports high speed RFID security applications. Different design strategies are there to optimize the hardware metrics trade-off for particular application. The algorithm is implemented on different family of FPGAs with different devices to analyze the performance of design in 4 input LUTs and 6 input LUTs implementations. In addition, the results of hardware design are evaluated and compared with the most relevant lightweight block ciphers, shows the proposed architecture finds its utilization in terms of speed and area optimization from the hardware resources. The increment in throughput with optimized area of this architecture suggests that piccolo can applicable to implement for ultra-lightweight applications also.

Internet of Things is realized by a large number of heterogeneous smart devices which sense, collect and share data with each other over the internet in order to control the physical world. Due to open nature, global connectivity and resource constrained nature of smart devices and wireless networks the Internet of Things is susceptible to various routing attacks. In this paper, we purpose an architecture of Ensemble Learning based Network Intrusion Detection System named ELNIDS for detecting routing attacks against IPv6 Routing Protocol for Low-Power and Lossy Networks. We implement four different ensemble based machine learning classifiers including Boosted Trees, Bagged Trees, Subspace Discriminant and RUSBoosted Trees. To evaluate proposed intrusion detection model we have used RPL-NIDDS17 dataset which contains packet traces of Sinkhole, Blackhole, Sybil, Clone ID, Selective Forwarding, Hello Flooding and Local Repair attacks. Simulation results show the effectiveness of the proposed architecture. We observe that ensemble of Boosted Trees achieve the highest Accuracy of 94.5% while Subspace Discriminant method achieves the lowest Accuracy of 77.8 % among classifier validation methods. Similarly, an ensemble of RUSBoosted Trees achieves the highest Area under ROC value of 0.98 while lowest Area under ROC value of 0.87 is achieved by an ensemble of Subspace Discriminant among all classifier validation methods. All the implemented classifiers show acceptable performance results.

The Internet of Things (IoT) is changing the way we interact with everyday objects. "Smart" devices will reduce energy use, keep our homes safe, and improve our health. However, as recent attacks have shown, these devices also create tremendous security vulnerabilities in our computing networks. Securing all of these devices is a daunting task. In this paper, we argue that IoT device communications should be default-off and desired network communications must be explicitly enabled. Unlike traditional networked applications or devices like a web browser or PC, IoT applications and devices serve narrowly defined purposes and do not require access to all services in the network. Our proposal, Bark, a policy language and runtime for specifying and enforcing minimal access permissions in IoT networks, exploits this fact. Bark phrases access control policies in terms of natural questions (who, what, where, when, and how) and transforms them into transparently enforceable rules for IoT application protocols. Bark can express detailed rules such as "Let the lights see the luminosity of the bedroom sensor at any time" and "Let a device at my front door, if I approve it, unlock my smart lock for 30 seconds" in a way that is presentable and explainable to users. We implement Bark for Wi-Fi/IP and Bluetooth Low Energy (BLE) networks and evaluate its efficacy on several example applications and attacks.

Robots are sophisticated form of IoT devices as they are smart devices that scrutinize sensor data from multiple sources and observe events to decide the best procedural actions to supervise and manoeuvre objects in the physical world. In this paper, localization of the robot is addressed by QR code Detection and path optimization is accomplished by Dijkstras algorithm. The robot can navigate automatically in its environment with sensors and shortest path is computed whenever heading measurements are updated with QR code landmark recognition. The proposed approach highly reduces computational burden and deployment complexity as it reflects the use of artificial intelligence to self-correct its course when required. An Encrypted communication channel is established over wireless local area network using SSHv2 protocol to transfer or receive sensor data(or commands) making it an IoT enabled Robot.

The growing pervasiveness of Internet of Things (IoT) expands the attack surface by connecting more and more attractive attack targets, i.e. embedded devices, to the Internet. One key component in securing these devices is software integrity checking, which typically attained with Remote Attestation (RA). RA is realized as an interactive protocol, whereby a trusted party, verifier, verifies the software integrity of a potentially compromised remote device, prover. In the vast majority of IoT applications, smart devices operate in swarms, thus triggering the need for efficient swarm attestation schemes.In this paper, we present WISE, the first intelligent swarm attestation protocol that aims to minimize the communication overhead while preserving an adequate level of security. WISE depends on a resource-efficient smart broadcast authentication scheme where devices are organized in fine-grained multi-clusters, and whenever needed, the most likely compromised devices are attested. The candidate devices are selected intelligently taking into account the attestation history and the diverse characteristics (and constraints) of each device in the swarm. We show that WISE is very suitable for resource-constrained embedded devices, highly efficient and scalable in heterogenous IoT networks, and offers an adjustable level of security.

Recent advances in pervasive computing have caused a rapid growth of the Smart Home market, where a number of otherwise mundane pieces of technology are capable of connecting to the Internet and interacting with other similar devices. However, with the lack of a commonly adopted set of guidelines, several IT companies are producing smart devices with their own proprietary standards, leading to highly heterogeneous Smart Home systems in which the interoperability of the present elements is not always implemented in the most straightforward manner. As such, understanding the cyber risk of these cyber-physical systems beyond the individual devices has become an almost intractable problem. This paper tackles this issue by introducing a Smart Home reference architecture which facilitates security analysis. Being composed by three viewpoints, it gives a high-level description of the various functions and components needed in a domestic IoT device and network. Furthermore, this document demonstrates how the architecture can be used to determine the various attack surfaces of a home automation system from which its key vulnerabilities can be determined.

Emerging computing relies heavily on secure backend storage for the massive size of big data originating from the Internet of Things (IoT) smart devices to the Cloud-hosted web applications. Structured Query Language (SQL) Injection Attack (SQLIA) remains an intruder's exploit of choice to pilfer confidential data from the back-end database with damaging ramifications. The existing approaches were all before the new emerging computing in the context of the Internet big data mining and as such will lack the ability to cope with new signatures concealed in a large volume of web requests over time. Also, these existing approaches were strings lookup approaches aimed at on-premise application domain boundary, not applicable to roaming Cloud-hosted services' edge Software-Defined Network (SDN) to application endpoints with large web request hits. Using a Machine Learning (ML) approach provides scalable big data mining for SQLIA detection and prevention. Unfortunately, the absence of corpus to train a classifier is an issue well known in SQLIA research in applying Artificial Intelligence (AI) techniques. This paper presents an application context pattern-driven corpus to train a supervised learning model. The model is trained with ML algorithms of Two-Class Support Vector Machine (TC SVM) and Two-Class Logistic Regression (TC LR) implemented on Microsoft Azure Machine Learning (MAML) studio to mitigate SQLIA. This scheme presented here, then forms the subject of the empirical evaluation in Receiver Operating Characteristic (ROC) curve.

In this paper, a distributed architecture for the implementation of smart city has been proposed to facilitate various smart features like solid waste management, efficient urban mobility and public transport, smart parking, robust IT connectivity, safety and security of citizens and a roadmap for achieving it. How massive volume of IoT data can be analyzed and a layered architecture of IoT is explained. Why data integration is important for analyzing and processing of data collected by the different smart devices like sensors, actuators and RFIDs is discussed. The wireless sensor network can be used to sense the data from various locations but there has to be more to it than stuffing sensors everywhere for everything. Why only the sensor is not sufficient for data collection and how human beings can be used to collect data is explained. There is some communication protocols between the volunteers engaged in collecting data to restrict the sharing of data and ensure that the target area is covered with minimum numbers of volunteers. Every volunteer should cover some predefined area to collect data. Then the proposed architecture model is having one central server to store all data in a centralized server. The data processing and the processing of query being made by the user is taking place in centralized server.

IoT (Internet of Things) is a network of interconnected devices, designed to collect and exchange data which can then turn it into information, eventually into wisdom. IoT is a region where digital world converges with physical world. With the evolution of IoT, it is expected to create substantial impact on human lives. IoT ecosystem produces and exchanges sizeable data due to which IoT becomes an attractive target for adversary. The large-scale interconnectivity leads to various potential risk related to information security. Security assurance in IoT ecosystem is one of the major challenges to address. In this context, embedded security becomes a key issue in IoT devices which are constrained in terms of processing, power, memory and bandwidth. The focus of this paper is on the recommended design considerations for constrained IoT devices with the objective to achieve security by default. Considering established set of protocols along with best practices during design and development stage can address majority of security challenges.

In the Internet of Things (IoT), smart devices are connected using various communication protocols, such as Wi-Fi, ZigBee. Some IoT devices have multiple built-in communication modules. If an IoT device equipped with multiple communication protocols is compromised by an attacker using one communication protocol (e.g., Wi-Fi), it can be exploited as an entry point to the IoT network. Another protocol (e.g., ZigBee) of this IoT device could be used to exploit vulnerabilities of other IoT devices using the same communication protocol. In order to find potential attacks caused by this kind of cross-protocol devices, we group IoT devices based on their communication protocols and construct a graphical security model for each group of devices using the same communication protocol. We combine the security models via the cross-protocol devices and compute hidden attack paths traversing different groups of devices. We use two use cases in the smart home scenario to demonstrate our approach and discuss some feasible countermeasures.

Software-defined networks provide new facilities for deploying security mechanisms dynamically. In particular, it is possible to build and adjust security chains to protect the infrastructures, by combining different security functions, such as firewalls, intrusion detection systems and services for preventing data leakage. It is important to ensure that these security chains, in view of their complexity and dynamics, are consistent and do not include security violations. We propose in this paper an automated strategy for supporting the verification of security chains in software-defined networks. It relies on an architecture integrating formal verification methods for checking both the control and data planes of these chains, before their deployment. We describe algorithms for translating specifications of security chains into formal models that can then be verified by SMT1 solving or model checking. Our solution is prototyped as a package, named Synaptic, built as an extension of the Frenetic family of SDN programming languages. The performances of our approach are evaluated through extensive experimentations based on the CVC4, veriT, and nuXmv checkers.

Software-defined networks provide new facilities for deploying security mechanisms dynamically. In particular, it is possible to build and adjust security chains to protect the infrastructures, by combining different security functions, such as firewalls, intrusion detection systems and services for preventing data leakage. It is important to ensure that these security chains, in view of their complexity and dynamics, are consistent and do not include security violations. We propose in this paper an automated strategy for supporting the verification of security chains in software-defined networks. It relies on an architecture integrating formal verification methods for checking both the control and data planes of these chains, before their deployment. We describe algorithms for translating specifications of security chains into formal models that can then be verified by SMT1 solving or model checking. Our solution is prototyped as a package, named Synaptic, built as an extension of the Frenetic family of SDN programming languages. The performances of our approach are evaluated through extensive experimentations based on the CVC4, veriT, and nuXmv checkers.

Generative policies enable devices to generate their own policies that are validated, consistent and conflict free. This autonomy is required for security policy generation to deal with the large number of smart devices per person that will soon become reality. In this paper, we discuss the research issues that have to be addressed in order for devices involved in security enforcement to automatically generate their security policies - enabling policy-based autonomous security management. We discuss the challenges involved in the task of automatic security policy generation, and outline some approaches based om machine learning that may potentially provide a solution to the same.

Efficient trust management between nodes in a huge network is an essential requirement in modern networks. This work shows few generic primitive protocols for creating a trusted link between nodes by deploying unclonable physical tokens as Secret Unknown Ciphers. The proposed algorithms are making use of the clone-resistant physical identity of each participating node. Several generic node authentication protocols are presented. An intermediate node is shown to be usable as a mediator to build trust without having influence on the resulting security chain. The physical clone-resistant identities are using our early concept of Secret Unknown Cipher (SUC) technique. The main target of this work is to show the particular and efficient trust-chaining in large networks when SUC techniques are involved.

The Internet of Things (IoT) devices perform security-critical operations and deal with sensitive information in the IoT-based systems. Therefore, the increased deployment of smart devices will make them targets for cyber attacks. Adversaries can perform malicious actions, leak private information, and track devices' and their owners' location by gaining unauthorized access to IoT devices and networks. However, conventional security protocols are not primarily designed for resource constrained devices and therefore cannot be applied directly to IoT systems. In this paper, we propose Boot-IoT - a privacy-preserving, lightweight, and scalable security scheme for limited resource devices. Boot-IoT prevents a malicious device from joining an IoT network. Boot-IoT enables a device to compute a unique identity for authentication each time the device enters a network. Moreover, during device to device communication, Boot-IoT provides a lightweight mutual authentication scheme that ensures privacy-preserving identity usages. We present a detailed analysis of the security strength of BootIoT. We implemented a prototype of Boot-IoT on IoT devices powered by Contiki OS and provided an extensive comparative analysis of Boot-IoT with contemporary authentication methods. Our results show that Boot-IoT is resource efficient and provides better scalability compared to current solutions.

Internet of things (IOT) is a kind of advanced information technology which has drawn societies' attention. Sensors and stimulators are usually recognized as smart devices of our environment. Simultaneously IOT security brings up new issues. Internet connection and possibility of interaction with smart devices cause those devices to involve more in human life. Therefore, safety is a fundamental requirement in designing IOT. IOT has three remarkable features: overall perception, reliable transmission and intelligent processing. Because of IOT span, security of conveying data is an essential factor for system security. Hybrid encryption technique is a new model that can be used in IOT. This type of encryption generates strong security and low computation. In this paper, we have proposed a hybrid encryption algorithm which has been conducted in order to reduce safety risks and enhancing encryption's speed and less computational complexity. The purpose of this hybrid algorithm is information integrity, confidentiality, non-repudiation in data exchange for IOT. Eventually suggested encryption algorithm has been simulated by MATLAB software and its speed and safety efficiency were evaluated in comparison with conventional encryption algorithm.

Smart grid is an evolving new power system framework with ICT driven power equipment massively layered structure. The new generation sensors, smart meters and electronic devices are integral components of smart grid. However, the upcoming deployment of smart devices at different layers followed by their integration with communication networks may introduce cyber threats. The interdependencies of various subsystems functioning in the smart grid, if affected by cyber-attack, may be vulnerable and greatly reduce efficiency and reliability due to any one of the device not responding in real time frame. The cyber security vulnerabilities become even more evident due to the existing superannuated cyber infrastructure. This paper presents a critical review on expected cyber security threats in complex environment and addresses the grave concern of a secure cyber infrastructure and related developments. An extensive review on the cyber security objectives and requirements along with the risk evaluation process has been undertaken. The paper analyses confidentiality and privacy issues of entire components of smart power system. A critical evaluation on upcoming challenges with innovative research concerns is highlighted to achieve a roadmap of an immune smart grid infrastructure. This will further facilitate R&d; associated developments.

A smart city uses information technology to integrate and manage physical, social, and business infrastructures in order to provide better services to its dwellers while ensuring efficient and optimal utilization of available resources. With the proliferation of technologies such as Internet of Things (IoT), cloud computing, and interconnected networks, smart cities can deliver innovative solutions and more direct interaction and collaboration between citizens and the local government. Despite a number of potential benefits, digital disruption poses many challenges related to information security and privacy. This paper proposes a security framework that integrates the blockchain technology with smart devices to provide a secure communication platform in a smart city.

Wireless Mesh Network (WMN) is a promising wireless network architecture having potential of last few miles connectivity. There has been considerable research work carried out on various issues like design, performance, security etc. in WMN. Due to increasing interest in WMN and use of smart devices with bandwidth hungry applications, WMN must be designed with objective of energy efficient communication. Goal of this paper is to summarize importance of energy efficiency in WMN. Various techniques to bring energy efficient solutions have also been reviewed.

Novel Internet services are emerging around an increasing number of sensors and actuators in our surroundings, commonly referred to as smart devices. Smart devices, which form the backbone of the Internet of Things (IoT), enable alternative forms of user experience by means of automation, convenience, and efficiency. At the same time new security and safety issues arise, given the Internet-connectivity and the interaction possibility of smart devices with human's proximate living space. Hence, security is a fundamental requirement of the IoT design. In order to remain interoperable with the existing infrastructure, we postulate a security framework compatible to standard IP-based security solutions, yet optimized to meet the constraints of the IoT ecosystem. In this ongoing work, we first identify necessary components of an interoperable secure End-to-End communication while incorporating Public-key Cryptography (PKC). To this end, we tackle involved computational and communication overheads. The required components on the hardware side are the affordable hardware acceleration engines for cryptographic operations and on the software side header compression and long-lasting secure sessions. In future work, we focus on integration of these components into a framework and the evaluation of an early prototype of this framework.

Novel Internet services are emerging around an increasing number of sensors and actuators in our surroundings, commonly referred to as smart devices. Smart devices, which form the backbone of the Internet of Things (IoT), enable alternative forms of user experience by means of automation, convenience, and efficiency. At the same time new security and safety issues arise, given the Internet-connectivity and the interaction possibility of smart devices with human's proximate living space. Hence, security is a fundamental requirement of the IoT design. In order to remain interoperable with the existing infrastructure, we postulate a security framework compatible to standard IP-based security solutions, yet optimized to meet the constraints of the IoT ecosystem. In this ongoing work, we first identify necessary components of an interoperable secure End-to-End communication while incorporating Public-key Cryptography (PKC). To this end, we tackle involved computational and communication overheads. The required components on the hardware side are the affordable hardware acceleration engines for cryptographic operations and on the software side header compression and long-lasting secure sessions. In future work, we focus on integration of these components into a framework and the evaluation of an early prototype of this framework.