Secure Distributed Dynamic State Estimation in Wide-Area Smart Grids

Smart grid is a large complex network with a myriad of vulnerabilities, usually operated in adversarial settings and regulated based on estimated system states. In this study, we propose a novel highly secure distributed dynamic state estimation mechanism for wide-area (multi-area) smart grids, composed of geographically separated subregions, each supervised by a local control center. We firstly propose a distributed state estimator assuming regular system operation, that achieves near-optimal performance based on the local Kalman filters and with the exchange of necessary information between local centers. To enhance the security, we further propose to (i) protect the network database and the network communication channels against attacks and data manipulations via a blockchain (BC)-based system design, where the BC operates on the peer-to-peer network of local centers, (ii) locally detect the measurement anomalies in real-time to eliminate their effects on the state estimation process, and (iii) detect misbehaving (hacked/faulty) local centers in real-time via a distributed trust management scheme over the network. We provide theoretical guarantees regarding the false alarm rates of the proposed detection schemes, where the false alarms can be easily controlled. Numerical studies illustrate that the proposed mechanism offers reliable state estimation under regular system operation, timely and accurate detection of anomalies, and good state recovery performance in case of anomalies

Security and Privacy for Green IoT-based Agriculture: Review, Blockchain solutions, and Challenges

open access articleThis paper presents research challenges on security and privacy issues in the field of green IoT-based agriculture. We start by describing a four-tier green IoT-based agriculture architecture and summarizing the existing surveys that deal with smart agriculture. Then, we provide a classification of threat models against green IoT-based agriculture into five categories, including, attacks against privacy, authentication, confidentiality, availability, and integrity properties. Moreover, we provide a taxonomy and a side-by-side comparison of the state-of-the-art methods toward secure and privacy-preserving technologies for IoT applications and how they will be adapted for green IoT-based agriculture. In addition, we analyze the privacy-oriented blockchain-based solutions as well as consensus algorithms for IoT applications and how they will be adapted for green IoT-based agriculture. Based on the current survey, we highlight open research challenges and discuss possible future research directions in the security and privacy of green IoT-based agriculture

The Data Breach Dilemma: Proactive Solutions for Protecting Consumers’ Personal Information

Data breaches are an increasingly common part of consumers’ lives. No institution is immune to the possibility of an attack. Each breach inevitably risks the release of consumers’ personally identifiable information and the strong possibility of identity theft. Unfortunately, current solutions for handling these incidents are woefully inadequate. Private litigation like consumer class actions and shareholder lawsuits each face substantive legal and procedural barriers. States have their own data security and breach notification laws, but there is currently no unifying piece of legislation or strong enforcement mechanism. This Note argues that proactive solutions are required. First, a national data security law—setting minimum data security standards, regulating the use and storage of personal information, and expanding the enforcement role of the Federal Trade Commission—is imperative to protect consumers’ data. Second, a proactive solution requires reconsidering how to minimize the problem by going to its source: the collection of personally identifiable information in the first place. This Note suggests regulating companies’ collection of Social Security numbers, and, eventually, using a system based on distributed ledger technology to replace the ubiquity of Social Security numbers

Cyberattacks on critical infrastructure: an economic perspective

The aim of this article is to analyze the economic aspects of cybersecurity of critical infrastructure defined as physical or virtual systems and assets that are vital to a country’s functioning and whose incapacitation or destruction would have a debilitating impact on national, economic, military and public security. The functioning of modern states, firms and individuals increasingly relies on digital or cyber technologies and this trend has also materialized in various facets of critical infrastructure. Critical infrastructure presents a new cybersecurity area of attacks and threats that requires the attention of regulators and service providers. Deploying critical infrastructure systems without suitable cybersecurity might make them vulnerable to intrinsic failures or malicious attacks and result in serious negative consequences. In this article a fuller view of costs and losses associated with cyberattacks that includes both private and external (social) costs is proposed. An application of the cost-benefit analysis or the Return on Security Investment (ROSI) indicator is presented to evaluate the worthiness of cybersecurity efforts and analyze the costs associated with some major cyberattacks in recent years. The “Identify, Protect, Detect, Respond and Recover” (IPDRR) framework of organizing cybersecurity efforts is also proposed as well as an illustration as to how the blockchain technology could be utilized to improve security and efficiency within a critical infrastructure

Performance Analysis of Blockchain-Enabled Security and Privacy Algorithms in Connected and Autonomous Vehicles: A Comprehensive Review

Strategic investment(s) in vehicle automation technologies led to the rapid development of technology that revolutionised transport services and reduced fatalities on a scale never seen before. Technological advancements and their integration in Connected Autonomous Vehicles (CAVs) increased uptake and adoption and pushed firmly for the development of highly supportive legal and regulatory and testing environments. However, systemic threats to the security and privacy of technologies and lack of data transparency have created a dynamic threat landscape within which the establishment and verification of security and privacy requirements proved to be an arduous task. In CAVs security and privacy issues can affect the resilience of these systems and hinder the safety of the passengers. Existing research efforts have been placed to investigate the security issues in CAVs and propose solutions across the whole spectrum of cyber resilience. This paper examines the state-of-the-art in security and privacy solutions for CAVs. It investigates their integration challenges, drawbacks and efficiencies when coupled with distributed technologies such as Blockchain. It has also listed different cyber-attacks being investigated while designing security and privacy mechanism for CAVs

Navigating the IoT landscape: Unraveling forensics, security issues, applications, research challenges, and future

Given the exponential expansion of the internet, the possibilities of security attacks and cybercrimes have increased accordingly. However, poorly implemented security mechanisms in the Internet of Things (IoT) devices make them susceptible to cyberattacks, which can directly affect users. IoT forensics is thus needed for investigating and mitigating such attacks. While many works have examined IoT applications and challenges, only a few have focused on both the forensic and security issues in IoT. Therefore, this paper reviews forensic and security issues associated with IoT in different fields. Future prospects and challenges in IoT research and development are also highlighted. As demonstrated in the literature, most IoT devices are vulnerable to attacks due to a lack of standardized security measures. Unauthorized users could get access, compromise data, and even benefit from control of critical infrastructure. To fulfil the security-conscious needs of consumers, IoT can be used to develop a smart home system by designing a FLIP-based system that is highly scalable and adaptable. Utilizing a blockchain-based authentication mechanism with a multi-chain structure can provide additional security protection between different trust domains. Deep learning can be utilized to develop a network forensics framework with a high-performing system for detecting and tracking cyberattack incidents. Moreover, researchers should consider limiting the amount of data created and delivered when using big data to develop IoT-based smart systems. The findings of this review will stimulate academics to seek potential solutions for the identified issues, thereby advancing the IoT field.Comment: 77 pages, 5 figures, 5 table