Abstract—The cyber-physical nature of the smartgrid has rendered it vulnerable to a multitude of attacks that can occur at its communication, networking, and physical entry points. Such cyber-physical attacks can have detrimental effects on the operation of the grid as exemplified by the recent attack which caused a blackout of the Ukranian power grid. Thus, to properly secure the smartgrid, it is of utmost importance to: a) understand its underlying vulnerabilities and associated threats, b) quantify their effects, and c) devise appropriate securitysolutions. In this paper, the key threats targeting the smartgrid are first exposed while assessing their effects on the operation and stability of the grid. Then, the challenges involved in understanding these attacks and devising defense strategies against them are identified. Potential solution approaches that can help mitigate these threats are then discussed. Last, a number of mathematical tools that can help in analyzing and implementing securitysolutions are introduced. As such, this paper will provide the first comprehensive overview on smartgridsecurity.
attackers to infiltrate into their systems. They forget that they (users) and cybercriminals use the same source (internet), where they are exploited knowingly or unknowingly. A hacker is anyone with the technical knowledge and expertise who intrudes into a system in an unauthorized manner. A security hacker is someone who uses his/her knowledge to break into a computer system. They are also known as crackers (Lee, M. 2015). This normally results in substantial financial loss and identity theft. These hackers deploy malicious malware in various forms to take away important credentials, steal valuable information, search for a systems’ back door, or “use you” to make an even a bigger gain, they must first get you or your computer to do something maliciously, like executing a code (Taylor et al, 2015).
The future generation of the electrical network is known as the smartgrid. The distribution domain of the smartgrid intelligently supplies electricity to the end-users with the aid of the decentralized Distribution Automation (DA) in which intelligent control functions are distributed and accomplished via real-time communication between the DA components. Internet-based communication via the open protocols is the latest trend for decentralized DA communication. Internet communication has many benefits, but it exposes the critical infrastructure’s data to cyber-securitythreats. Security attacks may not only make DA services unreachable but may also result in undesirable physical consequences and serious damage to the distribution network environment. Therefore, it is compulsory to protect DA communication against such attacks. There is no single model for securing DA communication. In fact, the security level depends on several factors such as application requirements, communication media, and, of course, the cost. There are several smartgridsecurity frameworks and standards, which are under development by different organizations. However, smartgrid cyber-security field has not yet reached full maturity and, it is still in the early phase of its progress. Security protocols in IT and computer networks can be utilized to secure DA communication because industrial ICT standards have been designed in accordance with Open Systems Interconnection model. Furthermore, state-of-the-art DA concepts such as Active distribution network tend to integrate processing data into IT systems.
Abstract—Cloud Computing has emerged as a new paradigm of computing that builds on the foundations of Distributed Computing, Grid Computing, and Virtualization. Cloud computing is Internet- accessible business model with flexible resource allocation on demand, and computing on pay-per-use as utilities. Cloud computing has grown to provide a promising business concept for computing infrastructure, where concerns are beginning to grow about how safe an environment is. Security is one of the major issues in the cloud-computing environment. In this paper we investigate some prime security attacks and possible solutions for clouds: XML Signature Wrapping attacks, Browser Security, and Vendor Lock-in.
In this paper, we have surveyed several attacks which occur in the several different layers in the ad-hoc networks. We have also reviewed about the several security concepts in an adhoc network. We have also scrutinized the securitychallenges and the ways to overcome those challenges in the ad-hoc network. A brief abstract of the characteristics of the mobile ad-hoc network is also been discussed. Lot of research is still under discussion about the securitythreats in a mobile adhoc network and the solutions to overcome them. Finally, this survey report can be very well used for the research works based on the security and its challenges in MANET’s.
Student, Dept. of C.S.E, Institute of Technology Guru Ghasidas University, Bilaspur, Chhattisgarh, India 1 Assistant Professor, Dept. of C.S.E, Institute of Technology Guru Ghasidas University, Bilaspur, Chhattisgarh, India 2 ABSTRACT: The Internet of Things gives a technologically optimistic view of the future where most of the objects will make intelligent communications with each other through the internet anywhere anytime .Although it really makes really appreciable progress in this field, there still uncertainties lingers with its security concepts of its usage which is still date the major topic of concern in the design of IoT architectures. This paper portrays a general survey of all the security issues in the field of IoT along with the analysis of the various architecture of IoT. The study defines various security measures, its requirements and the challenges that come along with the implementation of IoT. We discuss securitythreats and the solutions related to it on each layer of the IoT architecture to make this technology more secure and popular and spread it globally.
Abstract. Low-cost Radio Frequency Identification (RFID) tags affixed to consumer items as smart labels are emerging as one of the most per- vasive computing technology in history. This can have huge security im- plications. The present article surveys the most important technical se- curity challenges of RFID systems. We first provide a brief summary of the most relevant standards related to this technology. Next, we present an overview about the state of the art on RFID security, addressing both the functional aspects and the security risks and threats associated to its use. Finally, we analyze the main securitysolutions proposed until date. Keywords: RFID Security, Pervasive Computing, Ubiquitous Comput- ing, Security and Privacy.
In the 2012 first quarterly report from Trend Micro , it was pointed out that the large diffusion of mobile devices and the increase in awareness of the principal cyber threats have resulted in an increase in the interest of cybercrime in the mobile sector. Another significant interest is concentrated on the threat in terms of the rapid spread of botnets based on mobile devices, favored by the total almost absence of protection and the difficulty of tracing the agents composing the network. If these exploits are targeted by well-established hacker groups such as Anonymous, it will pose a bigger threat to organizations and smart environments that protect highly sensitive data, targeting companies and individuals for various political and financial reasons.
solutions to the ever increasing demand of energy. Maximizing energy utilization is basic need for the coming generation to survive. Now a day’s researcher are emphasizing on the implementation of smartgrid all across the globe to meet the energy demands in most efficient and reliable fashion. The methodology needs to be accepted globally with little concern on its reliability, durability, flexibility, adaptability, performance and many other factors . Above mentioned factors must be kept in mind while analysing any system. Smartgrid is one such kind of system where we find huge data transfer on various network, like grid to grid, vehicle to grid, one machine to another and many more. Looking into this fact there is a strong urge to practice energy in the best possible manner. Along with benefits there remains a major issue to the smartgrid is privacy and security. As data transfer is vulnerable to data theft and misuse of the same, hence the key to the successful implementation of smartgrid lies in the identification of best solution for security and privacy.
Many quite different stakeholders are involved, namely traditional large- scale commodity providers, distribution network operators (utilities), typical consumers, emerging small-scale producers, metering service providers, IT com- ponent developers/providers, and several regulatory and standardization insti- tutions. Most of these parties have no strong background in IT security. This may be one explanation why the smart metering infrastructure rolled out so far in many countries is plainly insecure, and why — even despite of the efforts by various groups involved — in the recent definition of the German regula- tions the mentioned security architecture problems regarding the integration of hardware security modules in smart meter gateways and PKI have not been properly addressed and solved. Moreover, part of the stakeholders have conflict- ing economic interests, while for an overall solution, they need to co-operate in non-trivial ways both during the definition and the deployment of smartgrid related solutions. This is certainly one of the main reasons for the major delays we are currently experiencing, such that no running large-scale secure solution is in existence these days.
Smart Meters within the SmartGrid, are expected to be able to provide detailed consumption information about the home they are connected to in 15-minute intervals (compared to one month as is the case with the traditional grid) . Such a development becomes synonymous to the collection and transmission of greater volumes of consumption data from Smart Home appliances and creates a major risk against customer privacy. During the transmission of this data from appliances to the EMS an eavesdropping attack  by an adversary for example, could result in valuable consumption data leaking to the adversary who can then process them to infer a lot about a customer’s lifestyle. Such processing of the data collected could mean passing them through a load profiling algorithm or through a use mode detection algorithm for example. In the first case an adversary can infer what devices are on at any given time (since each device has a distinctive load signature) . In the second case specific information about the operation of the devices that are on can be revealed as well (eg. the channel a TV is tuned on!) . By repeatedly collecting such information an adversary could actually intrude in a customer’s private life (Low Impact), knowing when he wakes up, when he goes to sleep, when he leaves for work, in what room he is at any given moment, when nobody is at home, even where the customer travels to (by collecting charging data from his PEV). This information could help an adversary plan more severe attacks against a customer (burglary, theft, kidnapping) (Moderate Impact). Presence information can also be inferred through traffic analysis attacks that do not reveal the data as such but their sending patterns (devices that are on send consumption messages more often) .
SQL-type queries that operate over time and buffer windows). Commonly streams are implemented as tuples with well-defined structure . Stream tuples are stamped with date of its occurrence. Also containing name value pair describing different attributes. Essential to stream processing is Streaming Analytics, or the ability to continuously calculate mathematical or statistical analytics on the fly within the stream (e.g. continuous queries). Windowing is a mechanism used in stream computing to perform operations such as join, sum, AVG on these moving streams. Windows can be defined physically (in terms of Time) or logically (in terms of number of elements). They have fixed or moving boundaries, leading to different types of windows (e.g. fixed window, moving window, land mark window) . Stream processing solutions are designed to handle high volume in real time with a scalable, highly available and fault tolerant architecture. This enables analysis of data in motion. The data flow graph of a stream processor consists of stream source; filter, operators and stream sink as shown in Fig. 1. (a). A stream processing application is a collection of operators connected by streams.
C-DAX uses an Information Centric Network (ICN) architecture that operates on top of the IP pro- tocol. An ICN is well-suited to the challenges of the electrical grid since it is a distributed approach that aims to be highly scalable and more resilient to disruptions and failures [Ahl+12]. The flavor of ICN used in C-DAX is the Publish-Subscribe Internet Routing Paradigm [Ain+09]. C-DAX clients host smartgrid applications and can play multiple roles as subscriber or publisher. For instance, a sensor device might be a publisher of sensor data, while a smart meter can publish measurements and subscribe to a data feed of energy prices. C-DAX provides the middle-ware to these publisher and subscriber clients for the interaction with the C-DAX cloud. The C-DAX cloud is responsible for routing and delivering the messages from publishers to subscribers in a safe, reliable and scalable manner. The cloud consists of a network of so-called C-DAX nodes, hosts located, for example, at distribution substations. Examples of clients are (smart) utility meters, Phasor Measurement Units (PMUs) and Intelligent Electronic Devices (IEDs).
Since threats are constantly evolving, protection demands advanced cyber security technologies. By providing comprehensive, real-time threat intelligence, cyber securitysolutions can pro- tect systems against cyber threats across mul- tiple vectors. Intended to collect information from devices, networks and applications, secu- rity information and event management (SIEM) systems are often focused on security events to identify risks and threats based on analysis of both internal and external data. Such sys- tems are deployed within secure and isolated facilities, or in broadly distributed zones, which is critical for obtaining situational awareness across zones. SIEM systems col- lect and aggregate information from cyber systems and then provide information about risks and threats through an automated process supporting decision-making. Application whitelisting can complement tradi- tional malware protection technologies like anti-virus and is a valuable alternative when such traditional technologies cannot be deployed. Application whitelisting through a list of authorized files ensures that only allowed files are executed. Non-authorized software (e.g., malware) cannot be executed on systems that have this technology deployed.
“As stated by the Federal Energy Regulatory Commission cyber attacks can damage As stated by the Federal Energy Regulatory Commission, cyber attacks can damage generation and distribution facilities in ways that cause widespread disruption of electric service and undermine our government, economy, and the health and safety of millions of citizens. We selected N-Dimension Solutions Inc. as the official cyber security partner of Hometown Connections because the firm offers a deep knowledge of cyber security a Hometown Connections because the firm offers a deep knowledge of cyber security, a proven methodology, and a commitment to addressing the unique requirements of public power systems of all sizes.”
The classifier Operation Architecture is subdivided into the input data, the method, and the output or control variables. Operation architecture in this work refers not only to the mathematical or conceptual model of the “control architecture” but includes the requirements on communication capabilities as well. The operation architecture has a direct effect on the system security and resilience (Drayer 2018) and therefore is an important classifier for smartgridsolutions. It comprises the SGAM zones operation, station, field and process in the function, information and component layer of the SGAM (CEN-CENELEC-ETSI 2012). In Nieße (2015) a classification of coordination paradigms is provided based on the location in which data is processed and where control decisions are made. This was developed for the classification of agent-based systems, but can be applied to classify the realization of power system operation methods in general. In the following, when discussing an operation unit, we mean the entity, in which information is processed and decisions for the operation are made.
The threats described in section III, have managed to be detected successfully by a number of IDSs proposed. On the other hand, the threats, described in Section IV, are yet to be addressed in any way. Furthermore, the new emerging technologies and components used in HAN have made the bottom layer of the SmartGrid an entity that needs to be equally secured. The attack scenarios clearly illustrate the criticality of this entity the high likelihood of a possible attack affecting the SmartGrid being initiated from the Smart Home part. These two entities need to be considered as a whole and not as separate. One of the most effective securitysolutions in mitigating such types of threats is the usage of Intrusion Detection Systems (IDS). As a result, a potential IDS solution could be developed to detect these new threats. This IDS shall follow a distributed approach, due to the system’s broadness and complexity, so the network can be effectively monitored. A vast amount of audit data shall be collected, focusing on the application layer, to detect any kind of potential unauthorised activity as soon as possible before it is spread to the higher layers of the network. In that way, the protection of such a critical infrastructure can be increased.
Another key concern raised by consumer groups is the safety impact of the RF signals transmitted by the smart meter to communicate with the equipment on the pole (Wamsted, 2012). In North America, smartgrid initiatives primarily require the development of a communications infrastructure or network parallel to the power grid (Larsen, 2009). Many of these parallel networks have employed wireless communications from the home to the pole through a RF technology. There are several RF technologies under consideration, from wi-fi and Z-Wave to ZigBee (Mulligan, 2011). ZigBee is emerging as the predominant choice; this RF technology functions in the ISM frequency of 915MHz in North America and provides a secure wireless mesh network (Swirbul, 2011). The utilities have chosen this technology over a physical infrastructure as it is low cost, quick to deploy, and can be secured (Swirbul, 2011). In addition, it meets several technical requirements, including speed, security, and IP support (Mulligan, 2011). The ZigBee Alliance is setting standards to allow In-Home Devices (IHD) to directly connect via ZigBee, potentially placing RF devices in the home (Fodor, 2011). Regardless of the final RF standard, there is a definite preference on the part of utilities for RF-based connections over hard-line wired interfaces.
The fundamental requirement for authentication design is to provide efficient multicast authentication schemes for the SmartGrid applications. Therefore, few recent works [106–108] are designed toward this objective, i.e., fast mul- ticast authentication protocols for power control systems. The most straightforward multicast authentication scheme is to use public key based authentication, which is also recommended by a recent security standard for sub- station communication, IEC 62351 . In public key based multicast authentication, all receivers share the pub- lic key of the sender. The sender signs a message with its own private key, then each receiver uses the sender’s public key to verify the message. The scheme is communication- efficient as only one authenticator is appended to the mes- sage; however, it is quite computationally inefficient (e.g. RSA in Table 12) for embedded devices in power systems. An intuitive alterative is to use computationally efficient symmetric key instead of public key. However, sharing only one symmetric key across a multicast group cannot guarantee adequate security, because when multiple nodes share a single key, it is easy for an attacker that has ob- tained the key by compromising a node to masquerade as a different sender and inject fake information into the network.
We perform a further literature review. The focus here is to analyse publications of market research institutes, such as Gartner, IDC, Juniper Research. For the selection of relevant publications we use the following keywords: “security”, “security product”, “security software”, and “security solution” combined with “market”, “mobile”, “mobile device”, “smart phone”, and “smartphone”. All identified security software solutions together with their important facts were summarised in a table. We also describe the identified classifications of security software solution for smartphones and try to unify these classifications. Finally, we check if all security software solutions can be categorised into our unified classifications. To identify security software solutions we considered the manufactures of mobile security software solutions that are named in the „Magic Quadrant for Endpoint Protection Platforms“, „Magic Quadrant for Mobile Device Management Software“ and „Magic Quadrant for User Authentication” of Gartner Inc. [18, 19, 20].