12,428 research outputs found
Differential Privacy Techniques for Cyber Physical Systems: A Survey
Modern cyber physical systems (CPSs) has widely being used in our daily lives
because of development of information and communication technologies (ICT).With
the provision of CPSs, the security and privacy threats associated to these
systems are also increasing. Passive attacks are being used by intruders to get
access to private information of CPSs. In order to make CPSs data more secure,
certain privacy preservation strategies such as encryption, and k-anonymity
have been presented in the past. However, with the advances in CPSs
architecture, these techniques also needs certain modifications. Meanwhile,
differential privacy emerged as an efficient technique to protect CPSs data
privacy. In this paper, we present a comprehensive survey of differential
privacy techniques for CPSs. In particular, we survey the application and
implementation of differential privacy in four major applications of CPSs named
as energy systems, transportation systems, healthcare and medical systems, and
industrial Internet of things (IIoT). Furthermore, we present open issues,
challenges, and future research direction for differential privacy techniques
for CPSs. This survey can serve as basis for the development of modern
differential privacy techniques to address various problems and data privacy
scenarios of CPSs.Comment: 46 pages, 12 figure
Blockchain for Future Smart Grid: A Comprehensive Survey
The concept of smart grid has been introduced as a new vision of the
conventional power grid to figure out an efficient way of integrating green and
renewable energy technologies. In this way, Internet-connected smart grid, also
called energy Internet, is also emerging as an innovative approach to ensure
the energy from anywhere at any time. The ultimate goal of these developments
is to build a sustainable society. However, integrating and coordinating a
large number of growing connections can be a challenging issue for the
traditional centralized grid system. Consequently, the smart grid is undergoing
a transformation to the decentralized topology from its centralized form. On
the other hand, blockchain has some excellent features which make it a
promising application for smart grid paradigm. In this paper, we aim to provide
a comprehensive survey on application of blockchain in smart grid. As such, we
identify the significant security challenges of smart grid scenarios that can
be addressed by blockchain. Then, we present a number of blockchain-based
recent research works presented in different literatures addressing security
issues in the area of smart grid. We also summarize several related practical
projects, trials, and products that have been emerged recently. Finally, we
discuss essential research challenges and future directions of applying
blockchain to smart grid security issues.Comment: 26 pages, 13 figures, 5 table
Security for 4G and 5G Cellular Networks: A Survey of Existing Authentication and Privacy-preserving Schemes
This paper presents a comprehensive survey of existing authentication and
privacy-preserving schemes for 4G and 5G cellular networks. We start by
providing an overview of existing surveys that deal with 4G and 5G
communications, applications, standardization, and security. Then, we give a
classification of threat models in 4G and 5G cellular networks in four
categories, including, attacks against privacy, attacks against integrity,
attacks against availability, and attacks against authentication. We also
provide a classification of countermeasures into three types of categories,
including, cryptography methods, humans factors, and intrusion detection
methods. The countermeasures and informal and formal security analysis
techniques used by the authentication and privacy preserving schemes are
summarized in form of tables. Based on the categorization of the authentication
and privacy models, we classify these schemes in seven types, including,
handover authentication with privacy, mutual authentication with privacy, RFID
authentication with privacy, deniable authentication with privacy,
authentication with mutual anonymity, authentication and key agreement with
privacy, and three-factor authentication with privacy. In addition, we provide
a taxonomy and comparison of authentication and privacy-preserving schemes for
4G and 5G cellular networks in form of tables. Based on the current survey,
several recommendations for further research are discussed at the end of this
paper.Comment: 24 pages, 14 figure
Privacy-preserving data aggregation in resource-constrained sensor nodes in Internet of Things: A review
Privacy problems are lethal and getting more attention than any other issue
with the notion of the Internet of Things (IoT). Since IoT has many application
areas including smart home, smart grids, smart healthcare system, smart and
intelligent transportation and many more. Most of these applications are fueled
by the resource-constrained sensor network, such as Smart healthcare system is
powered by Wireless Body Area Network (WBAN) and Smart home and weather
monitoring systems are fueled by Wireless Sensor Networks (WSN). In the
mentioned application areas sensor node life is a very important aspect of
these technologies as it explicitly effects the network life and performance.
Data aggregation techniques are used to increase sensor node life by decreasing
communication overhead. However, when the data is aggregated at intermediate
nodes to reduce communication overhead, data privacy problems becomes more
vulnerable. Different Privacy-Preserving Data Aggregation (PPDA) techniques
have been proposed to ensure data privacy during data aggregation in
resource-constrained sensor nodes. We provide a review and comparative analysis
of the state of the art PPDA techniques in this paper. The comparative analysis
is based on Computation Cost, Communication overhead, Privacy Level, resistance
against malicious aggregator, sensor node life and energy consumption by the
sensor node. We have studied the most recent techniques and provide in-depth
analysis of the minute steps involved in these techniques. To the best of our
knowledge, this survey is the most recent and comprehensive study of PPDA
techniques.Comment: 9 page
Assessing the Privacy Cost in Centralized Event-Based Demand Response for Microgrids
Demand response (DR) programs have emerged as a potential key enabling
ingredient in the context of smart grid (SG). Nevertheless, the rising concerns
over privacy issues raised by customers subscribed to these programs constitute
a major threat towards their effective deployment and utilization. This has
driven extensive research to resolve the hindrance confronted, resulting in a
number of methods being proposed for preserving customers' privacy. While these
methods provide stringent privacy guarantees, only limited attention has been
paid to their computational efficiency and performance quality. Under the
paradigm of differential privacy, this paper initiates a systematic empirical
study on quantifying the trade-off between privacy and optimality in
centralized DR systems for maximizing cumulative customer utility. Aiming to
elucidate the factors governing this trade-off, we analyze the cost of privacy
in terms of the effect incurred on the objective value of the DR optimization
problem when applying the employed privacy-preserving strategy based on Laplace
mechanism. The theoretical results derived from the analysis are complemented
with empirical findings, corroborated extensively by simulations on a 4-bus MG
system with up to thousands of customers. By evaluating the impact of privacy,
this pilot study serves DR practitioners when considering the social and
economic implications of deploying privacy-preserving DR programs in practice.
Moreover, it stimulates further research on exploring more efficient approaches
with bounded performance guarantees for optimizing energy procurement of MGs
without infringing the privacy of customers on demand side
Achieving Differential Privacy against Non-Intrusive Load Monitoring in Smart Grid: a Fog Computing approach
Fog computing, a non-trivial extension of cloud computing to the edge of the
network, has great advantage in providing services with a lower latency. In
smart grid, the application of fog computing can greatly facilitate the
collection of consumer's fine-grained energy consumption data, which can then
be used to draw the load curve and develop a plan or model for power
generation. However, such data may also reveal customer's daily activities.
Non-intrusive load monitoring (NILM) can monitor an electrical circuit that
powers a number of appliances switching on and off independently. If an
adversary analyzes the meter readings together with the data measured by an
NILM device, the customer's privacy will be disclosed. In this paper, we
propose an effective privacy-preserving scheme for electric load monitoring,
which can guarantee differential privacy of data disclosure in smart grid. In
the proposed scheme, an energy consumption behavior model based on Factorial
Hidden Markov Model (FHMM) is established. In addition, noise is added to the
behavior parameter, which is different from the traditional methods that
usually add noise to the energy consumption data. The analysis shows that the
proposed scheme can get a better trade-off between utility and privacy compared
with other popular methods
Energy and Information Management of Electric Vehicular Network: A Survey
The connected vehicle paradigm empowers vehicles with the capability to
communicate with neighboring vehicles and infrastructure, shifting the role of
vehicles from a transportation tool to an intelligent service platform.
Meanwhile, the transportation electrification pushes forward the electric
vehicle (EV) commercialization to reduce the greenhouse gas emission by
petroleum combustion. The unstoppable trends of connected vehicle and EVs
transform the traditional vehicular system to an electric vehicular network
(EVN), a clean, mobile, and safe system. However, due to the mobility and
heterogeneity of the EVN, improper management of the network could result in
charging overload and data congestion. Thus, energy and information management
of the EVN should be carefully studied. In this paper, we provide a
comprehensive survey on the deployment and management of EVN considering all
three aspects of energy flow, data communication, and computation. We first
introduce the management framework of EVN. Then, research works on the EV
aggregator (AG) deployment are reviewed to provide energy and information
infrastructure for the EVN. Based on the deployed AGs, we present the research
work review on EV scheduling that includes both charging and vehicle-to-grid
(V2G) scheduling. Moreover, related works on information communication and
computing are surveyed under each scenario. Finally, we discuss open research
issues in the EVN
Review of Smart Meter Data Analytics: Applications, Methodologies, and Challenges
The widespread popularity of smart meters enables an immense amount of
fine-grained electricity consumption data to be collected. Meanwhile, the
deregulation of the power industry, particularly on the delivery side, has
continuously been moving forward worldwide. How to employ massive smart meter
data to promote and enhance the efficiency and sustainability of the power grid
is a pressing issue. To date, substantial works have been conducted on smart
meter data analytics. To provide a comprehensive overview of the current
research and to identify challenges for future research, this paper conducts an
application-oriented review of smart meter data analytics. Following the three
stages of analytics, namely, descriptive, predictive and prescriptive
analytics, we identify the key application areas as load analysis, load
forecasting, and load management. We also review the techniques and
methodologies adopted or developed to address each application. In addition, we
also discuss some research trends, such as big data issues, novel machine
learning technologies, new business models, the transition of energy systems,
and data privacy and security.Comment: IEEE Transactions on Smart Grid, 201
Internet of Cloud: Security and Privacy issues
The synergy between the cloud and the IoT has emerged largely due to the
cloud having attributes which directly benefit the IoT and enable its continued
growth. IoT adopting Cloud services has brought new security challenges. In
this book chapter, we pursue two main goals: 1) to analyse the different
components of Cloud computing and the IoT and 2) to present security and
privacy problems that these systems face. We thoroughly investigate current
security and privacy preservation solutions that exist in this area, with an
eye on the Industrial Internet of Things, discuss open issues and propose
future directionsComment: 27 pages, 4 figure
When Energy Trading meets Blockchain in Electrical Power System: The State of the Art
With the rapid growth of renewable energy resources, the energy trading began
to shift from centralized to distributed manner. Blockchain, as a distributed
public ledger technology, has been widely adopted to design new energy trading
schemes. However, there are many challenging issues for blockchain-based energy
trading, i.e., low efficiency, high transaction cost, security & privacy
issues. To tackle with the above challenges, many solutions have been proposed.
In this survey, the blockchain-based energy trading in electrical power system
is thoroughly investigated. Firstly, the challenges in blockchain-based energy
trading are identified. Then, the existing energy trading schemes are studied
and classified into three categories based on their main focus: energy
transaction, consensus mechanism, and system optimization. And each category is
presented in detail. Although existing schemes can meet the specific energy
trading requirements, there are still many unsolved problems. Finally, the
discussion and future directions are given
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