Biblio

The increased interconnectivity and complexity of supervisory control and data acquisition (SCADA) systems in power system networks has exposed the systems to a multitude of potential vulnerabilities. In this paper, we present a novel approach for a next-generation SCADA-specific intrusion detection system (IDS). The proposed system analyzes multiple attributes in order to provide a comprehensive solution that is able to mitigate varied cyber-attack threats. The multiattribute IDS comprises a heterogeneous white list and behavior-based concept in order to make SCADA cybersystems more secure. This paper also proposes a multilayer cyber-security framework based on IDS for protecting SCADA cybersecurity in smart grids without compromising the availability of normal data. In addition, this paper presents a SCADA-specific cybersecurity testbed to investigate simulated attacks, which has been used in this paper to validate the proposed approach.

The addition of synchrophasors such as phasor measurement units (PMUs) to the existing power grid will enhance real-time monitoring and analysis of the grid. The PMU collects bus voltage, line current, and frequency measurements and uses the communication network to send the measurements to the respective substation(s)/control center(s). Since this approach relies on network infrastructure, possible cyber security vulnerabilities have to be addressed to ensure that is stable, secure, and reliable. In this paper, security vulnerabilities associated with a synchrophasor network in a benchmark IEEE 68 bus (New England/New York) power system model are examined. Currently known feasible attacks are demonstrated. Recommended testing and verification methods are also presented.

Nowadays is increasingly used process bus for communication of equipments in substations. In addition to signaling various statuses of device using GOOSE messages it is possible to transmit measured values, which can be used for diagnostic of system or other advanced functions. Transmission of such values via Ethernet is well defined in protocol IEC 61850-9-2. Paper introduces a tool designed for verification of sampled values generated by various devices using this protocol.
 

Non-intrusive load monitoring (NILM) extracts information about how energy is being used in a building from electricity measurements collected at a single location. Obtaining measurements at only one location is attractive because it is inexpensive and convenient, but it can result in large amounts of data from high frequency electrical measurements. Different ways to compress or selectively measure this data are therefore required for practical implementations of NILM. We explore the use of random filtering and random demodulation, techniques that are closely related to compressed sensing, to offer a computationally simple way of compressing the electrical data. We show how these techniques can allow one to reduce the sampling rate of the electricity measurements, while requiring only one sampling channel and allowing accurate NILM performance. Our tests are performed using real measurements of electrical signals from a public data set, thus demonstrating their effectiveness on real appliances and allowing for reproducibility and comparison with other data management strategies for NILM.

The precise measurement of temperature is very important to the security and stability of the operation for a superconducting magnet. A slight fluctuation in the operating temperature may cause a superconducting magnet unstable. This paper presents a low-temperature measurement system based on C8051 Micro Controller Unit and Platinum resistance thermometer. In the process of data acquisition, a modified weighted average algorithm is applied to the digital filter program of the micro controller unit. The noise can be effectively reduced and can measure temperature of three different location points simultaneously, and there is no the interference among the three channels. The designed system could measure the temperature from 400 K to 4.0 K with a resolution of 1 mK. This system will be applied in a conduction cooling Nb3Al superconducting magnet. In order to certify the feasibility of the system, tests are performed in a small NbTi non-insulation superconducting magnet model. The results show that the measurement system is reliable and the measured temperature is accurate.

Intrusion detection has been an active field of research for more than 35 years. Numerous systems had been built based on the two fundamental detection principles, knowledge-based and behavior-based detection. Anyway, having a look at day-to-day news about data breaches and successful attacks, detection effectiveness is still limited. Even more, heavy-weight intrusion detection systems cannot be installed in every endangered environment. For example, Industrial Control Systems are typically utilized for decades, charging off huge investments of companies. Thus, some of these systems have been in operation for years, but were designed afore without security in mind. Even worse, as systems often have connections to other networks and even the Internet nowadays, an adequate protection is mandatory, but integrating intrusion detection can be extremely difficult - or even impossible to date. We propose a new lightweight current-based IDS which is using a difficult to manipulate measurement base and verifiable ground truth. Focus of our system is providing intrusion detection for ICS and SCADA on a low-priced base, easy to integrate. Dr. WATTson, a prototype implemented based on our concept provides high detection and low false alarm rates.

The 6L0WPAN adaptation layer is widely used in many Internet of Things (IoT) and vehicular networking applications. The current IoT framework [1], which introduced 6LoWPAN to the TCP/IP model, does not specif the implementation for managing its received-fragments buffer. This paper looks into the effect of current implementations of buffer management strategies at 6LoWPAN's response in case of fragmentation-based, buffer reservation Denial of Service (DoS) attacks. The Packet Drop Rate (PDR) is used to analyze how successful the attacker is for each management technique. Our investigation uses different defence strategies, which include our implementation of the Split Buffer mechanism [2] and a modified version of this mechanism that we devise in this paper as well. In particular, we introduce dynamic calculation for the average time between consecutive fragments and the use of a list of previously dropped packets tags. NS3 is used to simulate all the implementations. Our results show that using a ``slotted'' buffer would enhance 6LoWPAN's response against these attacks. The simulations also provide an in-depth look at using scoring systems to manage buffer cleanups.

Communication networks can be the targets of organized and distributed attacks such as flooding-type DDOS attack in which malicious users aim to cripple a network server or a network domain. For the attack to have a major effect on the network, malicious users must act in a coordinated and time correlated manner. For instance, the members of the flooding attack increase their message transmission rates rapidly but also synchronously. Even though detection and prevention of the flooding attacks are well studied at network and transport layers, the emergence and wide deployment of new systems such as VoIP (Voice over IP) have turned flooding attacks at the session layer into a new defense challenge. In this study a structured sparsity based group anomaly detection system is proposed that not only can detect synchronized attacks, but also identify the malicious groups from normal users by jointly estimating their members, structure, starting and end points. Although we mainly focus on security on SIP (Session Initiation Protocol) servers/proxies which are widely used for signaling in VoIP systems, the proposed scheme can be easily adapted for any type of communication network system at any layer.

A method for the multiple faults diagnosis in linear analog circuits is presented in this paper. The proposed approach is based upon the concept named by the indirect compensation theorem. This theorem is reducing the procedure of fault diagnosis in the analog circuit to the symbolic analysis process. An extension of the indirect compensation theorem for the linear subcircuit is proposed. The indirect compensation provides equivalent replacement of the n-ports subcircuit by n norators and n fixators of voltages and currents. The proposed multiple faults diagnosis techniques can be used for evaluation of any kind of terminal characteristics of the two-port network. For calculation of the circuit determinant expressions, the Generalized Parameter Extraction Method is implemented. The main advantage of the analysis method is that it is cancellation free. It requires neither matrix nor ordinary graph description of the circuit. The process of symbolic circuit analysis is automated by the freeware computer program Cirsym which can be used online. The experimental results are presented to show the efficiency and reliability of the proposed technique.

Research has observed context factors like occasion and time as influential factors for predicting whether or not to share a location with online friends. In other domains like social networks, personality was also found to play an important role. Furthermore, users are seeking a fine-grained disclosement policy that also allows them to display an obfuscated location, like the center of the current city, to some of their friends. In this paper, we observe which context factors and personality measures can be used to predict the correct privacy level out of seven privacy levels, which include obfuscation levels like center of the street or current city. Our results show that a prediction is possible with a precision 20% better than a constant value. We will give design indications to determine which context factors should be recorded, and how much the precision can be increased if personality and privacy measures are recorded using either a questionnaire or automated text analysis.

Research has observed context factors like occasion and time as influential factors for predicting whether or not to share a location with online friends. In other domains like social networks, personality was also found to play an important role. Furthermore, users are seeking a fine-grained disclosement policy that also allows them to display an obfuscated location, like the center of the current city, to some of their friends. In this paper, we observe which context factors and personality measures can be used to predict the correct privacy level out of seven privacy levels, which include obfuscation levels like center of the street or current city. Our results show that a prediction is possible with a precision 20% better than a constant value. We will give design indications to determine which context factors should be recorded, and how much the precision can be increased if personality and privacy measures are recorded using either a questionnaire or automated text analysis.

Measurers are critical to a remote attestation (RA) system to verify the integrity of a remote untrusted host. Run-time measurers in a dynamic RA system sample the dynamic program state of the host to form evidence in order to establish trust by a remote system (appraiser). However, existing run-time measurers are tightly integrated with specific software. Such measurers need to be generated anew for each software, which is a manual process that is both challenging and tedious. In this paper we present a novel approach to decouple application-specific measurement policies from the measurers tasked with performing the actual run-time measurement. We describe MSRR (MeaSeReR), a novel general-purpose measurement framework that is agnostic of the target application. We show how measurement policies written per application can use MSRR, eliminating much time and effort spent on reproducing core measurement functionality. We describe MSRR's robust querying language, which allows the appraiser to accurately specify the what, when, and how to measure. We evaluate MSRR's overhead and demonstrate its functionality.

We propose POWERALERT, an efficient external integrity checker for untrusted hosts. Current attestation systems suffer from shortcomings, including requiring a complete checksum of the code segment, from being static, use of timing information sourced from the untrusted machine, or using imprecise timing information such as network round-trip time. We address those shortcomings by (1) using power measurements from the host to ensure that the checking code is executed and (2) checking a subset of the kernel space over an extended period. We compare the power measurement against a learned power model of the execution of the machine and validate that the execution was not tampered. Finally, POWERALERT randomizes the integrity checking program to prevent the attacker from adapting. We model the interaction between POWERALERT and an attacker as a time-continuous game. The Nash equilibrium strategy of the game shows that POWERALERT has two optimal strategy choices: (1) aggressive checking that forces the attacker into hiding, or (2) slow checking that minimizes cost. We implement a prototype of POWERALERT using Raspberry Pi and evaluate the performance of the integrity checking program generation.

Compressed sensing (CS) integrates sampling and compression into a single step to reduce the processed data amount. However, the CS reconstruction generally suffers from high complexity. To solve this problem, compressive signal processing (CSP) is recently proposed to implement some signal processing tasks directly in the compressive domain without reconstruction. Among various CSP techniques, compressive detection achieves the signal detection based on the CS measurements. This paper investigates the compressive detection problem of random signals when the measurements are corrupted. Different from the current studies that only consider the dense noise, our study considers both the dense noise and sparse error. The theoretical performance is derived, and simulations are provided to verify the derived theoretical results.

Securing Cyber-Physical Systems (CPS) against cyber-attacks is challenging due to the wide range of possible attacks - from stealthy ones that seek to manipulate/drop/delay control and measurement signals to malware that infects host machines that control the physical process. This has prompted the research community to address this problem through developing targeted methods that protect and check the run-time operation of the CPS. Since protecting signals and checking for errors result in performance penalties, they must be performed within the delay bounds dictated by the control loop. Due to the large number of potential checks that can be performed, coupled with various degrees of their effectiveness to detect a wide range of attacks, strategic assignment of these checks in the control loop is a critical endeavor. To that end, this paper presents a coherent runtime framework - which we coin BLOC - for orchestrating the CPS with check blocks to secure them against cyber attacks. BLOC capitalizes on game theoretical techniques to enable the defender to find an optimal randomized use of check blocks to secure the CPS while respecting the control-loop constraints. We develop a Stackelberg game model for stateless blocks and a Markov game model for stateful ones and derive optimal policies that minimize the worst-case damage from rational adversaries. We validate our models through extensive simulations as well as a real implementation for a HVAC system.

The paper is devoted to analysis of condition of executing devices and sensors of Industrial Control Systems information security. The work contains structures of industrial control systems divided into groups depending on system's layer. The article contains the analysis of analog interfaces work and work features of data transmission protocols in industrial control system field layer. Questions about relevance of industrial control systems information security, both from the point of view of the information security occurring incidents, and from the point of view of regulators' reaction in the form of normative legal acts, are described. During the analysis of the information security systems of industrial control systems a possibility of leakage through technical channels of information leakage at the field layer was found. Potential vectors of the attacks on devices of field layer and data transmission network of an industrial control system are outlined in the article. The relevance analysis of the threats connected with the attacks at the field layer of an industrial control system is carried out, feature of this layer and attractiveness of this kind of attacks is observed.

The application of line current differential relays (LCDRs) to protect transmission lines has recently proliferated. However, the reliance of LCDRs on digital communication channels has raised growing cyber-security concerns. This paper investigates the impacts of false data injection attacks (FDIAs) on the performance of LCDRs. It also develops coordinated attacks that involve multiple components, including LCDRs, and can cause false line tripping. Additionally, this paper proposes a technique for detecting FDIAs against LCDRs and differentiating them from actual faults in two-terminal lines. In this method, when an LCDR detects a fault, instead of immediately tripping the line, it calculates and measures the superimposed voltage at its local terminal, using the proposed positive-sequence (PS) and negative-sequence (NS) submodules. To calculate this voltage, the LCDR models the protected line in detail and replaces the rest of the system with a Thevenin equivalent that produces accurate responses at the line terminals. Afterwards, remote current measurement is utilized by the PS and NS submodules to compute each sequence's superimposed voltage. A difference between the calculated and the measured superimposed voltages in any sequence reveals that the remote current measurements are not authentic. Thus, the LCDR's trip command is blocked. The effectiveness of the proposed method is corroborated using simulation results for the IEEE 39-bus test system. The performance of the proposed method is also tested using an OPAL real-time simulator.

The exponential usage of messaging services for communication raises many questions in privacy fields. Privacy issues in such services strongly depend on the graph-theoretical properties of users' interactions representing the real friendships between users. One of the most important issues of privacy is that users may disclose information of other users beyond the scope of the interaction, without realizing that such information could be aggregated to reveal sensitive information. Determining vulnerable interactions from non-vulnerable ones is difficult due to the lack of awareness mechanisms. To address this problem, we analyze the topological relationships with the level of trust between users to notify each of them about their vulnerable social interactions. Particularly, we analyze the impact of trusting vulnerable friends in infecting other users' privacy concerns by modeling a new vulnerability contagion process. Simulation results show that over-trusting vulnerable users speeds the vulnerability diffusion process through the network. Furthermore, vulnerable users with high reputation level lead to a high convergence level of infection, this means that the vulnerability contagion process infects the biggest number of users when vulnerable users get a high level of trust from their interlocutors. This work contributes to the development of privacy awareness framework that can alert users of the potential private information leakages in their communications.

Microservice architectures adoption is growing expeditiously in market size and adoption, including in business-critical systems. This is due to agility in development and deployment further increased by containers and their characteristics. Ensuring security is still a major concern due to challenges faced such as resource separation and isolation, as improper access to one service might compromise complete systems. This doctoral work intends to advance the security of microservice systems through research and improvement of methodologies for detection, tolerance and mitigation of security intrusions, while overcoming challenges related to multi-tenancy, heterogeneity, dynamicity of systems and environments. Our preliminary research shows that host-based IDSes are applicable in container environments. This will be extended to dynamic scenarios, serving as a steppingstone to research intrusion tolerance techniques suited to these environments. These methodologies will be demonstrated in realistic microservice systems: complex, dynamic, scalable and elastic.

The threats from side-channel attacks to modern processors has become a serious problem, especially under the enhancement of the microarchitecture characteristics with multicore and resource sharing. Therefore, the research and measurement of the vulnerability of the side-channel attack of the system is of great significance for computer designers. Most of the current evaluation methods proposed by researchers are only for typical cache side-channel attacks. In this paper, we propose a method to measure systems' vulnerability to side-channel attacks caused by port contention called pcSVF. We collected the traces of the victim and attacker and computed the correlation coefficient between them, thus we can measure the vulnerability of the system against side-channel attack. Then we analyzed the effectiveness of the method through the results under different system defense schemes.

The current evaluation of API recommendation systems mainly focuses on correctness, which is calculated through matching results with ground-truth APIs. However, this measurement may be affected if there exist more than one APIs in a result. In practice, some APIs are used to implement basic functionalities (e.g., print and log generation). These APIs can be invoked everywhere, and they may contribute less than functionally related APIs to the given requirements in recommendation. To study the impacts of correct-but-useless APIs, we use utility to measure them. Our study is conducted on more than 5,000 matched results generated by two specification-based API recommendation techniques. The results show that the matched APIs are heavily overlapped, 10% APIs compose more than 80% matched results. The selected 10% APIs are all correct, but few of them are used to implement the required functionality. We further propose a heuristic approach to measure the utility and conduct an online evaluation with 15 developers. Their reports confirm that the matched results with higher utility score usually have more efforts on programming than the lower ones.

The emergence of Industrial Cyber-Physical Systems (ICPS) in today's business world is still steadily progressing to new dimensions. Although they bring many new advantages to business processes and enable automation and a wider range of service capability, they also propose a variety of new challenges. One major challenge, which is introduced by such System-of-Systems (SoS), lies in the security aspect. As security may not have had that significant role in traditional embedded system engineering, a generic way to measure the level of security within an ICPS would provide a significant benefit for system engineers and involved stakeholders. Even though many security metrics and frameworks exist, most of them insufficiently consider an SoS context and the challenges of such environments. Therefore, we aim to define a security metric for ICPS, which measures the level of security during the system design, tests, and integration as well as at runtime. For this, we try to focus on a semantic point of view, which on one hand has not been considered in security metric definitions yet, and on the other hand allows us to handle the complexity of SoS architectures. Furthermore, our approach allows combining the critical characteristics of an ICPS, like uncertainty, required reliability, multi-criticality and safety aspects.

Numerous measurement researches have been performed to discover the IPv4 network security issues by leveraging the fast Internet-wide scanning techniques. However, IPv6 brings the 128-bit address space and renders brute-force network scanning impractical. Although significant efforts have been dedicated to enumerating active IPv6 hosts, limited by technique efficiency and probing accuracy, large-scale empirical measurement studies under the increasing IPv6 networks are infeasible now. To fill this research gap, by leveraging the extensively adopted IPv6 address allocation strategy, we propose a novel IPv6 network periphery discovery approach. Specifically, XMap, a fast network scanner, is developed to find the periphery, such as a home router. We evaluate it on twelve prominent Internet service providers and harvest 52M active peripheries. Grounded on these found devices, we explore IPv6 network risks of the unintended exposed security services and the flawed traffic routing strategies. First, we demonstrate the unintended exposed security services in IPv6 networks, such as DNS, and HTTP, have become emerging security risks by analyzing 4.7M peripheries. Second, by inspecting the periphery's packet routing strategies, we present the flawed implementations of IPv6 routing protocol affecting 5.8M router devices. Attackers can exploit this common vulnerability to conduct effective routing loop attacks, inducing DoS to the ISP's and home routers with an amplification factor of \textbackslashtextbackslashgt 200. We responsibly disclose those issues to all involved vendors and ASes and discuss mitigation solutions. Our research results indicate that the security community should revisit IPv6 network strategies immediately.

The COVID19 pandemic situation has opened a wide range of opportunities for cyber-criminals, who take advantage of the anxiety generated and the time spent on the Internet, to undertake massive phishing campaigns. Although companies are adopting protective measures, the psychological traits of the victims are still considered from a very generic perspective. In particular, current literature determines that the model proposed in the Big-Five personality traits (i.e., Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism) might play an important role in human behaviour to counter cybercrime. However, results do not provide unanimity regarding the correlation between phishing susceptibility and neuroticism. With the aim to understand this lack of consensus, this article provides a comprehensive literature review of papers extracted from relevant databases (IEEE Xplore, Scopus, ACM Digital Library, and Web of Science). Our results show that there is not a well-established psychological theory explaining the role of neuroticism in the phishing context. We sustain that non-representative samples and the lack of homogeneity amongst the studies might be the culprits behind this lack of consensus on the role of neuroticism on phishing susceptibility.

A new methodology to calculate the hysteresis induced power loss of inductor from the measured waveforms of DC-to-DC converter during the voltage conversion is presented. From this study, we find that the duty cycles (D) of the buck and boost converters used till date for inductance current calculation are not exactly equal to VOUT/VIN and 1-VIN/VOUT as the inductance change induced by the hysteresis effect cannot be neglected. Although the increase in the loading currents of the converter increases the remanence magnetization of inductor at the turn-off time (toff), this remanence magnetization is destroyed by the turbulence induced vortex current at the transistor turn-on transient. So, the core power loss of inductor increases with the loading current of the converter and becomes much larger than other power losses and cannot be neglected for the power efficiency calculation during power stage design.