Computer Security

Health center data implicates a large scale of individual health records and is immensely concealment sensory. In the virtual era of large-size data, the increasingly different health informatization causes it important that health data needs to be stored precisely and securely. However, daily health data transactions carry the risk of privacy leaks that make sharing difficult. Moreover, the recently permitted blockchain applications suffer from deficient performance and lack of privacy. This study presents a privacy-preserving and secure sharing and storage system for public health centers based on the blockchain method to dispose of these issues. This system utilizes a hash-256-based access controller and transaction signature with the consensus policy and provides security to share and store health data in the blockchain. In this approach, blockchain guarantees scalability, privacy, integrity, and availability for data retention. Also, this paper measures the performance of transactions with supporting confidentiality-preserving and shows the average transaction time and acceptable latency when accessing health data.

Today is the era of the Internet of Things (IoT). The recent advances in hardware and information technology have accelerated the deployment of billions of interconnected, smart and adaptive devices in critical infrastructures like health, transportation, environmental control, and home automation. Transferring data over a network without requiring any kind of human-to-computer or human-to-human interaction, brings reliability and convenience to consumers, but also opens a new world of opportunity for intruders, and introduces a whole set of unique and complicated questions to the field of Digital Forensics. Although IoT data could be a rich source of evidence, forensics professionals cope with diverse problems, starting from the huge variety of IoT devices and non-standard formats, to the multitenant cloud infrastructure and the resulting multi-jurisdictional litigations. A further challenge is the end-to-end encryption which represents a trade-off between users' right to privacy and the success of the forensics investigation. Due to its volatile nature, digital evidence has to be acquired and analyzed using validated tools and techniques that ensure the maintenance of the Chain of Custody. Therefore, the purpose of this paper is to identify and discuss the main issues involved in the complex process of IoT-based investigations, particularly all legal, privacy and cloud security challenges. Furthermore, this work provides an overview of the past and current theoretical models in the digital forensics science. Special attention is paid to frameworks that aim to extract data in a privacy-preserving manner or secure the evidence integrity using decentralized blockchain-based solutions. In addition, the present paper addresses the ongoing Forensics-as-a-Service (FaaS) paradigm, as well as some promising cross-cutting data reduction and forensics intelligence techniques. Finally, several other research trends and open issues are presented, with emphasis on the need for proactive Forensics Readiness strategies and generally agreed-upon standards.

The usefulness of patterns to optimize the environmental impact of business processes and their infrastructure has already been described in literature. However, due to the abstract description of pattern solutions, the individual application of patterns has to be done manually which is time consuming, complex, and error-prone. In this work, we show how the Green Compensation pattern can be applied automatically to different individual Cloud-based business processes in order to lower the negative environmental impact of the employed Virtual Machines without any manual effort. We show how our Management Planlet Framework can be used to implement this concrete refined pattern solution in a reusable way.

The environmental impact of doing business becomes an increasingly relevant aspect for organizations, not only because of legal requirements but also because more customers care about environmental influences. Most organizations, however, do not have comprehensive knowledge on how to restructure their business processes accordingly. In previous work we proposed green business process patterns that address the environmental impact explicitly as one possible solution. Beyond those patterns, we now provide environmentally relevant patterns derived from existing patterns of different domains. In this work, we present a set of such patterns related to automated business processes. The identified patterns support stakeholders when analyzing their business processes with respect to the environmental impact and, therefore, supporting green business process reengineering.

With the growing adoption of Cloud Computing, automated deployment and provisioning systems for Cloud applications are becoming more prevalent. They help to reduce the onboarding costs for new customers as well as the financial impact of managing Cloud services by automating these previously manual tasks. With the widespread use of such systems, the adoption of a common standard for describing Cloud applications will provide a crucial advantage by enabling reusable and portable applications. TOSCA, a newly published standard by OASIS with broad industry participation provides this opportunity. Besides the technical requirements of running and managing applications in the cloud, non-functional requirements, like cost, security, and environmental issues, are of special importance when moving towards the automated provisioning and management of Cloud applications. In this paper we demonstrate how non-functional requirements are defined in TOSCA using policies. We propose a mechanism for automatic processing of these formal policy definitions in a TOSCA runtime environment that we have developed based on the proposed architecture of the TOSCA primer. In order to evaluate our approach, we present prototypical implementations of security policies for encrypting databases and for limiting the geographical location of the Cloud servers. We demonstrate how our runtime environment is ensuring these policies and show how they affect the deployment of the application.

Active worms pose major security threats to the Internet. This is due to the ability of a ctive worms to propagate in an automated fashion as they continuously compromise computers on the Internet. Active w orms evolve during their propagation, and thus, pose great challenges to defend against them. In this paper, we investigate a new class of active worms, referred to as Camouflaging Worm (C -Worm in short). The C-Worm is different from traditional worms because of its ability to intelligently manipulate its scan traffic volume over time. Thereby, the C-Worm camouflages its propagation from existing worm detection systems based on analyzing the propagation traffic generated by worms. We analyze characteristics of the C -Worm and conduct a comprehensive comparison between its traffic and non worm traffic (background traffic). We observe t hat these two types of traffic are barely distinguishable in the time domain. However, their distinction is clear in the fre quency domain, due to t he recurring manipulative nature of the C -Worm. Motivated by our observations, we design a novel spectrum-based scheme to detect the C-Worm. Our scheme uses the Power Spectral Density (PSD) distribution of the scan traffic volume and its corresponding Spectral Flatness Measure (SFM) to distinguish the C -Worm traffic from background traffic. Using a comprehensive set of detection metrics and real -world traces as background traffic, we conduct extensive performance evaluations on our proposed spectrum-based detection scheme. The performance data clearly demonstrates that our scheme can effectively detect the C -Worm propagation. Furthermore, we show the generality of our spectrum-based scheme in effectively detecting not only the C-Worm, but traditional worms as well.

Automated ballistics imaging and analysis systems, such as the integrated ballistic identification system (IBIS), have advanced gun law enforcement operations by allowing images of gun crime evidence to be rapidly compared to a large inventory of evidence collected from other crime scenes. After firearm examiners confirm candidate matches, detectives can use the information generated by the links among gun crimes to help solve their cases. Links between recovered cartridge casings represent the vast majority of ballistic matches made through IBIS. Unfortunately, the two-dimensional grayscale digital photography used by the original IBIS equipment was often not refined enough to suggest potential matches between often highly damaged bullets from separate crime scenes. Through the acquisition of three-dimensional measurements, the BulletTrax-3-D image acquisition technology was specifically designed to improve the ability of law enforcement agencies to make bullet matches through automated ballistic imaging and analysis. This study examines the impact of 3-D imaging technology on the productivity of the Boston Police Department's Ballistics Unit in making bullet matches. When directly compared with 2-D imaging technology, we find that the 3-D imaging technology acquired larger amounts of crime bullet evidence and was associated with a nearly fivefold increase in the cold bullet matches by the Ballistics Unit. Interviews with Boston Police detectives confirmed the considerable investigative value of the cold bullet matches.

Spam has become a major issue in computer security because it is a channel for threats such as computer viruses, worms and phishing. Many solutions feature machine-learning algorithms trained using statistical representations of the terms that usually appear in the e-mails. Still, these methods require a training step with labelled data. Dealing with the situation where the availability of labelled training instances is limited slows down the progress of filtering systems and offers advantages to spammers. Currently, many approaches direct their efforts into Semi-Supervised Learning (SSL). SSL is a halfway method between supervised and unsupervised learning, which, in addition to unlabelled data, receives some supervision information such as the association of the targets with some of the examples. Collective Classification for Text Classification poses as an interesting method for optimising the classification of partially-labelled data. In this way, we propose here, for the first time, Collective Classification algorithms for spam filtering to overcome the amount of unclassified e-mails that are sent every day.

The use of mobile phones has increased in our lives because they offer nearly the same functionality as a personal computer. Besides, the number of applications available for Android-based mobile devices has increased. Google offers programmers the opportunity to upload and sell applications in the Android Market, but malware writers upload their malicious code there. In light of this background, we present here Manifest Analysis for Malware detection in Android (MAMA), a new method that extracts several features from the Android Manifest of the applications to build machine-learning classifiers and detect malware.

The complexity of modern security systems requires comprehensive (holistic) research methods that not only reduce complexity but also maintain high diagnostic power. The author addresses the problem area of security system structures, which can be classified as the scientific discipline of security engineering. A pre-research theory strategy and a deformation method and abstraction technique were applied, based on the existing meaning of specific primary concepts and axioms of action system theory. It was assumed that every security system, which is an example of an action system, is composed of layers. Based on his conclusions, the author distinguished the human, organisational and technical layers. The main research problem is of a praxeological nature and is expressed in the following question: what types of security system configurations can be distinguished on the basis of action system theory? The result is a description of four basic types of security system architecture: unification, coordination, replication, and diversification.

This study was based on data analysis of academic histories of civil engineering students at FACET-UNT. Our main objective was to determine the academic performance variables that have a significant impact on the dropout of the career. To do this, we implemented a correlation model using LightGBM . We use this model to identify the key variables that influence the probability of student dropout. In addition, we use game theory to interpret the results obtained. Specifically, we use the SHAP library

The security of information technology, specifically web applications, has become an area of concern today. Computer cybercrime is now a significant problem that affects more than just businesses and organizations. Higher education institutions also began to experience computer threats that revealed their information assets. Universities, polytechnics, colleges of education, research centers, and other postsecondary institutions are probably the most vulnerable because they house sensitive data on their faculty, staff, and students, as well as academic records of scientific and technological advancements and research. The first step in an information system security strategy is risk analysis management It helps in assessing the risk of information assets to know their security level or status, and assist in define a security control measures and implementation of technical plan to avoid threats that exploit some vulnerability that could cause severe damage to an asset or infrastructure of institutions higher education (IHEs). This article presents some recommendations to perform a risk analysis management in IHEs to accessed threats and vulnerability that helps to lower the risk of their information assets. This article presents existing educational threat and vulnerability on their web applications. Ensuring security is a goal of every organization regardless of its size or purpose and also proposed a risk management model. With the information technology, an organization may be considered secure when it ensures the confidentiality, integrity, and availability of information and IT assets. Confidentiality may be broken due to theft of sensitive information such as trade secrets, clients' personal information.

This paper presents a study for modernization of the water supply system in Kriva Palanka, Macedonia. As main water sources the system uses the springs of Kalin Kamen and the alternative sources are Stanеchka reka and four wells in the basin of Kriva reka. The population growth due to the migration from rural areas into high zones of the city caused water supply problems. The proposed solution for modernization of the system contributes to regular and continuous supply of quality drinking water. Furthermore we propose implementation of SCADA system for monitoring and control of the parameters in water distribution system.

Recent disasters have not only pointed out to humanity how small we are compared to nature, but also showed us that terrorism has become a factor that we cannot ignore. We are being forced to handle crisis situations in the most efficient way we can. Especially the first hours after a disaster can be of vital interest to the victims and an efficient and well thought approach can greatly reduce the number of victims. After the event of a crisis, rescue workers therefore have to be able to do their work in a dynamic and dangerous environment, with all means available. In these situations it has turned out that on a local and global level, the communication between rescue workers is sometimes a problem. Recently more interest has been going out to assisting rescue workers in their work by offering them solutions to problems or extra tools and services to simplify their tasks while improving the results. The approach described in this thesis work aims at facilitating the communication for the rescue workers and offering them services if needed. This communication is provided by an ad-hoc network of mobile devices, PDAs, that offer services to rescue workers, while at the same time providing an infrastructure for processing of data from the rescue workers. The communication primarily takes place via a blackboard structure, that is distributed over the nodes in the network. Besides offering communication to the actual rescue workers that have the task of helping victims and reporting about the situation, another challenge is to collect all the knowledge that is available, to get to an overview of the situation. For this purpose, we propose introducing a structure in the topology of the network that is most applicable to a crisis situation. Our approach consists of introducing mobile crisis centers, with around them rings of nodes that take care of the processing of the data that comes in from the outer ring, that consists of the sensor nodes. These sensor nodes can be rescue workers with PDAs, but also sensors on robots or fixed sensors (e.g. chemical gas sensors). This approach is inspired by current procedures of crisis teams. The approach aims at providing services in the network, by dynamically assigning tasks to nodes in the network. Besides the place in the network, the (distributed) decision where a tasks is to be executed, is based on performance measures of the nodes. These are integrated in one value, that is used as a decision criteria. Besides assigning tasks to the best node at hand, the system offers more functionalities with respect to fault tolerance, in the form of replication and monitoring of other nodes.

In this paper we describe a disaster management system. It is assumed that each individual in the field is equipped with a PDA (Personal Digital Assistant) and that can communicate with other PDAs in the vicinity. Together the PDAs form an ad-hoc network. Users can enter their own observations to the PDA, like the position of victims, or a description of the current situation at particular location (e.g. smoke, emergency exits, traffic congestion). This information is entered in a special iconic language. Reversibly, the PDAs inform the users on the overall current situation of the crisis. In order to come to a shared view of the world, the knowledge that is present in the network has to be shared and fused. The proposed way to communicate is via a shared blackboard. This approach facilitates communication in a time and place independent way.

The use of general descriptive names, registered names, trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use.

I would also like to present gratitude to Mrs. Shruti Jaiswal (Research Scholar, Delhi Technological University) for providing me continuous support and guidance during this project. I would also like to thank every DTU faculty member and the staff members who were directly or indirectly there to provide me valuable knowledge, guidance and support. I would like to thank "Samsung" for providing me this option of higher studies and research opportunity simultaneously with the job. I am also thankful to my friends and colleagues who have supported me in the time of need. I am really grateful to my family members for their unconditional love, support and understanding during this project.

Technology is the integration of technical skills, methods, processes and knowledge which are applied in streamlining the business operations with respect to products and services which are embedded in the business with computers, devices, machines and factories. Technological innovations influences business efficiency, productivity,costs, relationship with clients, retention of market share, customer satisfaction and growth. It has greater impact on the economy in various sectors of business.The paper has attempted to interpret the impact of technology in recreating the banking operations with respect to decision making, marketing, business growth, building robust customer support system, customer relationship management, resource allocation, offering unique banking products with exorbitant facilities.

Smart phones are very effective tools for increasing the productivity of business users. With their increasing computational power and storage capacity, smartphones allow end users to perform several tasks and be always updated while on the move. In Existing system, the location-based policy systems (LPS) are not accurate enough to differentiate between nearby locations without extra hardware or location devices. In most cases, such systems assume the context as given without providing or evaluating context detection methods of mobile devices. In order to overcome this issue, context-based access control (CBAC) mechanismhave been proposed. By means of CBAC, many privileges can be dynamically granted or revoked to applications based on the specific context of the user. The CBAC framework utilizes context sensing and machine learning to automatically classify contexts according to their security and privacy-related properties. It provides protection against device misuse using a dynam...

The advancement of artificial intelligence and the perception of
international migration as a security issue by governments have led to
the exploration of next-generation technologies in border security.
Advanced technologies are being implemented at the nations’ borders
for the development of intelligent security barriers. Due to the evolution
in border management policy, the responsibility for border security is
now being delegated to civilian officials instead of the military. The
deployment of the Mobile Surveillance System, the formation of the Risk
Analysis Network, and the application of technologies such as robotic
dogs, airships, and unmanned aerial vehicles have facilitated the
efficient monitoring of the territory behind the border, the border itself,
and areas beyond it. The deployment of sophisticated border
technologies enhances the identification, prevention, and deterrence of
unlawful crossings while improving border surveillance efficacy. The
existing literature indicates that this circumstance enhances both border effectiveness of new border security technology implemented by nations
in safeguarding human and border security. The SWOT technique is
utilized to assess the strengths and weaknesses of new-generation
border applications while also examining the possible threats they may
present to human security and the opportunities they may offer for
enhancing human security. This study aims to conduct a comprehensive
analysis of next-generation applications concerning human and border
security.

In several application scenarios, like the case of structural monitoring, it is important to model and represent the Wireless Sensor Networks (WSN) to be deployed. To model the components and properties of entire WSN types of collaboration in WSNs, we have created the Collaborative Wireless Sensor Networks (CWSN) model. This model also models the different types of collaboration that occur in a WSN. Our main goal is to provide a theoretical mathematical foundation that can model and analyze WSNs. Our approach is based on graph theory and propositional logic. The main contribution of this paper is applying the CWSN model to describe and represent a WSN. The use of the CWSN model brings several advantages, such as enabling the graphical representation of the state of the network and of several important properties: 1) the network topology; 2) the transmission between nodes considering a multi-hop communication; 3) the transmission hierarchy; 4) the evolution of the networks through a ...

A total of 3 orifice plates were observed -10-, 9-and 5-hole. With each orifice plate, 4 pressure profiles were compared -10, 7, 4 and 1 bar for each Pressure and Velocity Profiles were compared. Shnerr-Sauer Model was used in the ANSYS Fluent for CFD. An extensive comparison has been made between every model with respect to Pressure and Velocity Profiles, Bubble Radius and Cavitation Number. This has been an acute study over cavitation in a multi-hole orifice plate for which the preceding data has been observed and validated.

Less Economically Developed Countries (LEDCs) struggle to meet the demand for affordable housing in their growing cities. There are several reasons for this, but a major constraint is the high cost of construction materials. In LEDCs, material costs can constitute 60 to 80 percent of the total cost of residential construction. Nonetheless, their construction mimics the materially inefficient practices of the More Economically Developed Countries (MEDCs), which were developed to reduce labor over material costs. As a result, prismatic beams and flat slabs are often used despite their structural inefficiency. The mounting use of steel-reinforced concrete structures in LEDC cities also raises concern for the environmental costs of construction; construction accounts for 20-30 percent of LEDC carbon emissions. This research addresses these challenges with a flexible and accessible methodology for the design and analysis of materially efficient concrete elements that may reduce the econo...

The protocol for Quantitative Field Observations (QFOs) discussed here, termed the Baker-Rodrigo Observation Method Protocol (BROMP) 1.0, were initially developed by Ryan Baker and Ma. Mercedes T. Rodrigo . This method is used to record observations of student behavior and/or affect in field settings. Typically, these observations are then synchronized to log-file data compiled by the educational software that students are using at the time of the observations (although they have not been synchronized in all research using these methods). EDM researchers can then use data mining algorithms to determine what patterns in the software interactions correlate with the observational categories noted in the field. In this way, we can build detectors for the educational software that predict when students are in need of intervention because they are bored, frustrated, confused, off-task, etc. The first publication to use these QFO protocols was Baker, Corbett, Koedinger, & Wagner ( ), which looked at student behavior (e.g., was the student on-task working alone, on-task but participating in conversation, off-task, or gaming the system). The coding schemes for affect (initially developed by Graesser and his colleagues, cf. D 'Mello, Graesser, & Picard, 2007) were incorporated later (first in the best description of this work is found in Baker, D 'Mello, Rodrigo, and Graesser, 2010). In this method, behavior and affect are coded separately, because they are at least partially orthogonal (e.g., a student could be gaming the system and bored, or gaming the system and frustrated). Any behavior or affect not fitting in the scheme is noted as being outside the scheme (for instance, we do not typically include "surprise" or "delight" in our coding scheme, but they are occasionally seen, particularly in software environments with a more game-like design). The observers base their judgment of a student's state or behavior on the student's work context, actions, utterances, facial expressions, body language, and interactions with teachers or fellow students, in line with descriptive research on how humans generally identify affect, using multiple cues in concert for maximum accuracy rather than attempting to select individual cues. In our experience, attempting to focus on specific cues substantially reduces inter-rater reliability, as compared to more holistic judgment of behavior and affect. Previous research has produced a number of successful models based on these observations. In terms of behavior, these methods have been used to develop and validate models that can infer gaming the system (Baker, Corbett, & Koedinger, 2004; and off-task behavior (Baker, 2007). In terms of affect, these methods have been used to develop and validate models that can infer confusion, boredom, frustration, and engaged concentration (Baker et al., 2012, San Pedro et al., under review). These methods have also been used to study affect and the contexts and fashions in which affect emerges and changes over time (cf.

While Information and Communication Technology (ICT) trends are moving towards the Internet of Things (IoT), mobile applications are becoming more and more popular. Mostly due to their pervasiveness and the level of interaction with the users, along with the great number of advantages, the mobile applications bring up a great number of privacy related issues as well. These platforms can gather our very sensitive private data by only granting them a list of permissions during the installation process. Additionally, most of the users can find it difficult, or even useless, to analyze system permissions. Thus, their guess of app's safety mostly relies on the features like rating and popularity, rather than in understanding context of listed permissions. In this paper we investigate the relationship between the features collected from Android Market API 23 (such as Popularity, Total Number of Permissions, Number of Dangerous Permissions, Rating and Package Size) to app's privacy violation. To show the influence of each feature we use linear regression and R squared statistics. The conducted research can contribute to the classification of mobile applications with regards to the threat on user's privacy.

Nowadays, telemedicine is an emerging healthcare service where the healthcare professionals can diagnose, evaluate, and treat a patient using telecommunication technology. To diagnose and evaluate a patient, the healthcare professionals need to access the electronic medical record (EMR) of the patient, which might contain huge multimedia big data including X-rays, ultrasounds, CT scans, and MRI reports. For efficient access and supporting mobility for both the healthcare professionals as well as the patients, the EMR needs to be kept in big data storage in the healthcare cloud. In spite of the popularity of the healthcare cloud, it faces different security issues; for instance, data theft attacks are considered to be one of the most serious security breaches of healthcare data in the cloud. In this paper, the main focus has been given to secure healthcare private data in the cloud using a fog computing facility. To this end, a tri-party one-round authenticated key agreement protocol has been proposed based on the bilinear pairing cryptography that can generate a session key among the participants and communicate among them securely. Finally, the private healthcare data are accessed and stored securely by implementing a decoy technique.

Attacks on computer networks are increasingly common, often leading to severe economical and reputational damage to organisations. Subsequently, Intrusion Response Systems are recently an active area of research which seek to automatically respond to alerts generated by Intrusion Detection Systems. Current Intrusion Response Systems often seek to find optimal responses based on a general and balanced policy such as the cost and benefit to the network overall. However, organisations are encouraged to prepare Incident Response Policies, which outline prioritisations and performance measures for their response. These policies are highly individualised to the organisation, often influenced by the type of data present within the network. Building on this it is possible for several subsections of a network to have differing Incident Response Policies, for example in a Cyber-Physical network, a Control Area Network may have a much stricter policy in order to preserve a physical process. In this work we utilise a Deep Reinforcement Learning approach to allow the customisation of Reward Functions which in turn facilitates the creation of Response Profiles to align with differing Incident Response Policies. Evaluation of the Profiles is performed in a Cyber-Physical System testbed consisting of Web and Business local area networks configured using Mininet and integrated with a Tennessee Eastman Process plant running in Matlab. Experimentation demonstrates the ability of a Reinforcement Learning Agent to converge on near-optimal response to multi-stage attack scenarios in accordance with their Response Profile.

Cyber threats in Supervisory Control and Data Acquisition (SCADA) systems have the potential to render physical damage and jeopardize power system operation, safety and stability. SCADA systems were originally designed with little consideration of escalating cyber threats and hence the problem of how to develop robust intrusion detection technologies to tailor the requirements of SCADA is an emerging topic and a big challenge. This paper proposes a stateful Intrusion Detection System (IDS) using a Deep Packet Inspection (DPI) method to improve the cyber-security of SCADA systems using the IEC 60870-5-104 protocol which is tailored for basic telecontrol communications. The proposed stateful protocol analysis approach is presented that is designed specifically for the IEC 60870-5-104 protocol. Finally, the novel intrusion detection approach are implemented and validated.

With the development and deployment of IEC 61850 based smart substations, cybersecurity vulnerabilities of supervisory control and data acquisition (SCADA) systems are increasingly emerging. In response to the emergence of cybersecurity vulnerabilities in smart substations, a test-bed is indispensable to enable cybersecurity experimentation. In this paper, a comprehensive and realistic cyber-physical test-bed has been built to investigate potential cybersecurity vulnerabilities and the impact of cyber-attacks on IEC 61850 based smart substations. This test-bed is close to a real production type environment, and has the ability to carry out end-to-end testing of cyber-attacks and physical consequences. A fuzz testing approach is proposed for detecting IEC 61850 based intelligent electronic devices (IEDs) and validated in the proposed test-bed.

Critical infrastructures and industrial control systems are complex Cyber-Physical Systems (CPS). To ensure reliable operations of such systems, comprehensive threat modeling during system design and validation is of paramount significance. Previous works in literature mostly focus on safety, risks and hazards in CPS but lack effective threat modeling necessary to eliminate cyber vulnerabilities. Further, impact of cyber attacks on physical processes is not fully understood. This paper presents a comprehensive threat modeling framework for CPS using STRIDE, a systematic approach for ensuring system security at the component level. This paper first devises a feasible and effective methodology for applying STRIDE and then demonstrates it against a real synchrophasor-based synchronous islanding testbed in the laboratory. It investigates (i) what threat types could emerge in each system component based on the security properties lacking, and (ii) how a vulnerability in a system component risks the entire system security. The paper identifies that STRIDE is a light-weight and effective threat modeling methodology for CPS that simplifies the task for security analysts to identify vulnerabilities and plan appropriate component level security measures at the system design stage.

Many critical industrial control systems integrate a mixture of state-of-the-art and legacy equipment. Legacy installations lack advanced, and often even basic security features, risking entire system security. Existing research primarily focuses on the development of secure protocols for emerging devices or protocol translation proxies for legacy equipment. However, a robust security framework not only needs encryption but also mechanisms to prevent reconnaissance and unauthorized access to industrial devices. This paper proposes a novel Edge Security Gateway (ESG) that provides both, communication and endpoint security. The ESG is based on double ratchet algorithm and encrypts every message with a different key. It manages the ongoing renewal of short-lived session keys and provides localized firewall protection to individual devices. The ESG is easily customizable for a wide range of industrial application. As a use case, this paper presents the design and validation for synchrophasor technology in smart grid. The ESG effectiveness is practically validated in detecting reconnaissance, manipulation, replay, and command injection attacks due to its perfect forward and backward secrecy properties.

Currently deployed legacy industrial systems were not designed with the future industry 4.0 vision in mind and lack advanced, and often even basic, security features. Further, the presence of legacy systems not only introduces security and data privacy challenges but is also a barrier for the adoption of emerging cloud technologies. This paper proposes an approach for seamless and secure migration of legacy industrial control systems to the cloud. It investigates whether the cloud can meet the real-time requirements for control operations without compromising system safety. The proposed approach is designed to cause no or minimal interruption to industrial processes during cloud migration and offers a generic framework to be applied for different industrial sectors. As a use case, this paper presents the design and validation for synchrophasor technology in smart grid using the Amazon AWS cloud. Experiments on a real laboratory-based cyber-physical tested concluded that proposed cloud migration approach is promising for time-critical systems such as synchrophasor technology.

Cyber-attacks against Smart Grids have been found in the real world. Malware such as Havex and BlackEnergy have been found targeting industrial control systems (ICS) and researchers have shown that cyber-attacks can exploit vulnerabilities in widely used Smart Grid communication standards. This paper addresses a deep investigation of attacks against the manufacturing message specification of IEC 61850, which is expected to become one of the most widely used communication services in Smart Grids. We investigate how an attacker can build a custom tool to execute man-in-the-middle attacks, manipulate data, and affect the physical system. Attack capabilities are demonstrated based on NESCOR scenarios to make it possible to thoroughly test these scenarios in a real system. The goal is to help understand the potential for such attacks, and to aid the development and testing of cyber security solutions. An attack use-case is presented that focuses on the standard for power utility automation, IEC 61850 in the context of inverter-based distributed energy resource devices; especially photovoltaics (PV) generators.

The mass integration and deployment of intelligent technologies within critical commercial, industrial and public environments have a significant impact on business operations and society as a whole. Though integration of these critical intelligent technologies pose serious embedded security challenges for technology manufacturers which are required to be systematically approached, in-line with international security regulations. This paper establish security foundation for such intelligent technologies by deriving embedded security requirements to realise the core security functions laid out by international security authorities, and proposing microarchitectural characteristics to establish cyber resilience in embedded systems. To bridge the research gap between embedded and operational security domains, a detailed review of existing embedded security methods, microarchitectures and design practises is presented. The existing embedded security methods have been found ad-hoc, passive and strongly rely on building and maintaining trust. To the best of our knowledge to date, no existing embedded security microarchitecture or defence mechanism provides continuity of data stream or security once trust has broken. This functionality is critical for embedded technologies deployed in critical infrastructure to enhance and maintain security, and to gain evidence of the security breach to effectively evaluate, improve and deploy active response and mitigation strategies. To this end, the paper proposes three microarchitectural characteristics that shall be designed and integrated into embedded architectures to establish, maintain and improve cyber resilience in embedded systems for next-generation critical infrastructure.

With the rise in worth and popularity of cryptocurrencies, a new opportunity for criminal gain is being exploited and with little currently offered in the way of defence. The cost of mining (i.e. earning cryptocurrency through CPU-intensive calculations that underpin the blockchain technology) can be prohibitively expensive, with hardware costs and electrical overheads previously offering a loss compared to the cryptocurrency gained. Off-loading these costs along a distributed network of machines via malware offers an instantly profitable scenario, though standard Anti-virus (AV) products offer some defences against file-based threats. However, newer fileless malicious attacks, occurring through the browser on seemingly legitimate websites, can easily evade detection and surreptitiously engage the victim machine in computationally-expensive cryptomining (cryptojacking). With no current academic literature on the dynamic opcode analysis of cryptomining, to the best of our knowledge, we present the first such experimental study. Indeed, this is the first such work presenting opcode analysis on non-executable files. Our results show that browser-based cryptomining within our dataset can be detected by dynamic opcode analysis, with accuracies of up to 100%. Further to this, our model can distinguish between cryptomining sites, weaponized benign sites, de-weaponized cryptomining sites and real world benign sites. As it is process-based, our technique offers an opportunity to rapidly detect, prevent and mitigate such attacks, a novel contribution which should encourage further future work.

Software-as-a-service (SaaS) is a type of software service delivery model which encompasses a broad range of business opportunities and challenges. Users and service providers are reluctant to integrate their business into SaaS due to its security concerns while at the same time they are attracted by its benefits. This article highlights SaaS utility and applicability in different environments like cloud computing, mobile cloud computing, software defined networking and Internet of things. It then embarks on the analysis of SaaS security challenges spanning across data security, application security and SaaS deployment security. A detailed review of the existing mainstream solutions to tackle the respective security issues mapping into different SaaS security challenges is presented. Finally, possible solutions or techniques which can be applied in tandem are presented for a secure SaaS platform.

In this paper, we propose a malware categorization method that models malware behavior in terms of instructions using PageRank. PageRank computes ranks of web pages based on structural information and can also compute ranks of instructions that represent the structural information of the instructions in malware analysis methods. Our malware categorization method uses the computed ranks as features in machine learning algorithms. In the evaluation, we compare the effectiveness of different PageRank algorithms and also investigate bagging and boosting algorithms to improve the categorization accuracy. • Security and privacy➝Intrusion/anomaly and malware mitigation➝Malware and its mitigation.

Daily cyber-attacks on ships’ IT and OT systems are not a rare occurrence anymore. This has been taken into account in recent years and the IMO has issued directives and circulars with recommendations for increasing the cybersecurity of ship information systems as part of the overall ship security system. The effect of a successful cyber-attack of any kind, on elements of the ship’s IT and OT systems, can have a disastrous impact not only on the ship itself but also on the environment. While modern ships can be designed and all modern methods implemented to reduce and prevent the possibility of cyber-attacks onboard existing ships, it is not possible to achieve this security level and it is necessary to implement various solutions. At the same time, the ships’ crew is declining worldwide and most ships do not have IT officers or trained staff onboard to maintain the ship’s information systems. Because of that, the solutions that need to be put in place to increase the security of sh...

In the last 6-7 years, there is a rapid growth in the development of Smart Grid Network on earth. Smart Grid (SG) is an advancement to the traditional power grid which integrates the power grid with Information and Communication Technology (ICT). SG is a multilayer environment. In this multilayer environment, there are different layers of communications such as Appliance to Home Area Network (HAN), HAN to Building Area Network (BAN) and BAN to Neighbourhood Area Network (NAN). NAN finally connects to Smart Grid Control Center. There are various security challenges at each layer of communication in SG. In this paper, a comprehensive survey of various authentication protocols to address the security threats in SG environment is presented. Study on five different types of authentication protocols such as simple password based, mutual authentication consensus based and password authentication with Juggling is conducted. Simulation study shows that among all protocols, SG-MCPAK and MCEPAK outperforms in terms of number of hashes, passwords, phases, random number and number of packets transferred. Moreover, an improved protocol SG-JMCPAK is suggested, which On Lightweight Authentication for Smart Grid Network

In the late twentieth century, the term "System of Systems" (SoS) became popular to describe a complex system made up of a combination of independent constituent systems. Since then, several studies have been conducted to support and assess SoS management, functionality, and performance. Due to the evolutionary nature of SoS and the non-composability of the security properties of its constituent systems, it is difficult to assess or evaluate SoS security. This paper provides an up-to-date survey on SoS security, aimed at stimulating and guiding further research efforts. This systematic mapping study (SMS) focuses on SoS security, privacy, and trust. Our SMS identified 1828 studies from 6 digital libraries, 87 of which were selected that presented approaches analyzing, evaluating, or improving security. We classified these studies using nine research questions that focused on the nature of the studies, the studied SoS, or the study validation. After examining the selected studies, we identified six gaps and as many future work directions. More precisely, we observed that few studies examine SoS problems and instead propose specific solutions, making it challenging to develop generalizable approaches. Furthermore, the lack of standardization has hindered the reuse of existing approaches, making it difficult for solutions to be generalized to other SoS. In addition, the lack of descriptions of industrial environments in the literature makes it difficult to design realistic validation environments. As a result, the validation of new SoS research remains a challenge in the field.

Within growing pervasive information systems, Systems of Systems (SoS) emerge as a new research frontier. A SoS is formed by a set of constituent systems that live on their own with well-established functionalities and requirements, and, in certain circumstances, they must collaborate to achieve a common mission. In this scenario, security is one crucial property that needs to be considered since the early stages of SoS lifecycle. Unfortunately, SoS security cannot be guaranteed by addressing the security of each constituent system separately. The aim of this paper is to discuss the challenges faced in addressing the security of SoS and to propose some research ideas centered around the notion of a mission to be carried out by the SoS.

The increasing use of the Internet for social purposes enriches the data available online about all of us and promotes the concept of the Digital Persona. Actually, most of us are represented online by more than one identity, what we define here as a Pluridentity . This trend brings increased risks: it is well known that the security of a Digital Persona can be exploited if its data and security are not effectively managed. In this paper, we focus specifically on a new type of digital attack that can be perpetrated by combining pieces of data belonging to one same Pluridentity in order to profile their target. Some victims can be so accurately depicted when looking at their Pluridentity that by using the gathered information attackers can execute very personalized social engineering attacks, or even bypass otherwise safe security mechanisms. We characterize these Pluridentity attacks as a security issue of a virtual System of Systems, whose constituent systems are the individual identities and the humans themselves. We present a strategy to identify vulnerabilities caused by overexposure due to the combination of data from the constituent identities of a Pluridentity. To this end we introduce the Digital Persona Portrayal Metamodel, and the related Digital Pluridentity Persona Portrayal Analysis process that supports the architecting of data from different identities: such model and process can be used to identify the vulnerabilities of a Pluridentity due to its exploitation as a System of Systems. The approach has been validated on the Pluridentities of seventeen candidates selected from a data leak, by retrieving the data of their Digital Personae, and matching them against the security mechanisms of their Pluridentities. After analyzing the results for some of the analyzed subjects we could detect several vulnerabilities.

Research on cyber security related to social engineering has expanded from its purely technological orientation into explaining the role of human behaviour in detecting deception . In the broadest definition, social engineering, in the context of information security, is the manipulation of individuals to perform actions that cause harm or increase the probability of causing future harm. Human personality traits significantly contribute to the probability that an individual is susceptible to manipulation related to social engineering deception attacks and exploits . The outcome of the attacks and objective is the alteration of normal and rational decision making as described in behaviour decision theory . This quantitative and non-experimental study determined what makes an individual based on personality traits predisposed to social engineering treats in the context of susceptibility to deception manipulation and exploitation.