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Journal Article
Almajed, Hisham N., Almogren, Ahmad S..  2019.  SE-Enc: A Secure and Efficient Encoding Scheme Using Elliptic Curve Cryptography. IEEE Access. 7:175865–175878.
Many applications use asymmetric cryptography to secure communications between two parties. One of the main issues with asymmetric cryptography is the need for vast amounts of computation and storage. While this may be true, elliptic curve cryptography (ECC) is an approach to asymmetric cryptography used widely in low computation devices due to its effectiveness in generating small keys with a strong encryption mechanism. The ECC decreases power consumption and increases device performance, thereby making it suitable for a wide range of devices, ranging from sensors to the Internet of things (IoT) devices. It is necessary for the ECC to have a strong implementation to ensure secure communications, especially when encoding a message to an elliptic curve. It is equally important for the ECC to secure the mapping of the message to the curve used in the encryption. This work objective is to propose a trusted and proofed scheme that offers authenticated encryption (AE) for both encoding and mapping a message to the curve. In addition, this paper provides analytical results related to the security requirements of the proposed scheme against several encryption techniques. Additionally, a comparison is undertaken between the SE-Enc and other state-of-the-art encryption schemes to evaluate the performance of each scheme.
Oqaily, Momen, Jarraya, Yosr, Mohammady, Meisam, Majumdar, Suryadipta, Pourzandi, Makan, Wang, Lingyu, Debbabi, Mourad.  2019.  SegGuard: Segmentation-based Anonymization of Network Data in Clouds for Privacy-Preserving Security Auditing. IEEE Transactions on Dependable and Secure Computing. :1–1.
Security auditing allows cloud tenants to verify the compliance of cloud infrastructure with respect to desirable security properties, e.g., whether a tenant's virtual network is properly isolated from other tenants' networks. However, the input to such an auditing task, such as the detailed topology of the underlying cloud infrastructure, typically contains sensitive information which a cloud provider may be reluctant to hand over to a third party auditor. Additionally, auditing results intended for one tenant may inadvertently reveal private information about other tenants, e.g., another tenant's VM is reachable due to a misconfiguration. How to anonymize both the input data and the auditing results in order to prevent such information leakage is a novel challenge that has received little attention. Directly applying most of the existing anonymization techniques to such a context would either lead to insufficient protection or render the data unsuitable for auditing. In this paper, we propose SegGuard, a novel anonymization approach that prevents cross-tenant information leakage through per-tenant encryption, and prevents information leakage to auditors through hiding real input segments among fake ones; in addition, applying property-preserving encryption in an innovative way enables SegGuard to preserve the data utility for auditing while mitigating semantic attacks. We implement SegGuard based on OpenStack, and evaluate its effectiveness and overhead using both synthetic and real data. Our experimental results demonstrate that SegGuard can reduce the information leakage to a negligible level (e.g., less than 1% for an adversary with 50% pre-knowledge) with a practical response time (e.g., 62 seconds to anonymize a cloud infrastructure with 25,000 virtual machines).
Kebin Liu, Qiang Ma, Wei Gong, Xin Miao, Yunhao Liu.  2014.  Self-Diagnosis for Detecting System Failures in Large-Scale Wireless Sensor Networks. Wireless Communications, IEEE Transactions on. 13:5535-5545.

Existing approaches to diagnosing sensor networks are generally sink based, which rely on actively pulling state information from sensor nodes so as to conduct centralized analysis. First, sink-based tools incur huge communication overhead to the traffic-sensitive sensor networks. Second, due to the unreliable wireless communications, sink often obtains incomplete and suspicious information, leading to inaccurate judgments. Even worse, it is always more difficult to obtain state information from problematic or critical regions. To address the given issues, we present a novel self-diagnosis approach, which encourages each single sensor to join the fault decision process. We design a series of fault detectors through which multiple nodes can cooperate with each other in a diagnosis task. Fault detectors encode the diagnosis process to state transitions. Each sensor can participate in the diagnosis by transiting the detector's current state to a new state based on local evidences and then passing the detector to other nodes. Having sufficient evidences, the fault detector achieves the Accept state and outputs a final diagnosis report. We examine the performance of our self-diagnosis tool called TinyD2 on a 100-node indoor testbed and conduct field studies in the GreenOrbs system, which is an operational sensor network with 330 nodes outdoor.
 

Szott, S..  2014.  Selfish insider attacks in IEEE 802.11s wireless mesh networks. Communications Magazine, IEEE. 52:227-233.

The IEEE 802.11s amendment for wireless mesh networks does not provide incentives for stations to cooperate and is particularly vulnerable to selfish insider attacks in which a legitimate network participant hopes to increase its QoS at the expense of others. In this tutorial we describe various attacks that can be executed against 802.11s networks and also analyze existing attacks and identify new ones. We also discuss possible countermeasures and detection methods and attempt to quantify the threat of the attacks to determine which of the 802.11s vulnerabilities need to be secured with the highest priority.

Macedonio, Damiano, Merro, Massimo.  2014.  A Semantic Analysis of Key Management Protocols for Wireless Sensor Networks. Sci. Comput. Program.. 81:53–78.

Gorrieri and Martinelli’s timed Generalized Non-Deducibility on Compositions () schema is a well-known general framework for the formal verification of security protocols in a concurrent scenario. We generalise the  schema to verify wireless network security protocols. Our generalisation relies on a simple timed broadcasting process calculus whose operational semantics is given in terms of a labelled transition system which is used to derive a standard simulation theory. We apply our  framework to perform a security analysis of three well-known key management protocols for wireless sensor networks: , LEAP+ and LiSP.

Creech, G., Jiankun Hu.  2014.  A Semantic Approach to Host-Based Intrusion Detection Systems Using Contiguousand Discontiguous System Call Patterns. Computers, IEEE Transactions on. 63:807-819.

Host-based anomaly intrusion detection system design is very challenging due to the notoriously high false alarm rate. This paper introduces a new host-based anomaly intrusion detection methodology using discontiguous system call patterns, in an attempt to increase detection rates whilst reducing false alarm rates. The key concept is to apply a semantic structure to kernel level system calls in order to reflect intrinsic activities hidden in high-level programming languages, which can help understand program anomaly behaviour. Excellent results were demonstrated using a variety of decision engines, evaluating the KDD98 and UNM data sets, and a new, modern data set. The ADFA Linux data set was created as part of this research using a modern operating system and contemporary hacking methods, and is now publicly available. Furthermore, the new semantic method possesses an inherent resilience to mimicry attacks, and demonstrated a high level of portability between different operating system versions.

Creech, G., Jiankun Hu.  2014.  A Semantic Approach to Host-Based Intrusion Detection Systems Using Contiguousand Discontiguous System Call Patterns. Computers, IEEE Transactions on. 63:807-819.

Host-based anomaly intrusion detection system design is very challenging due to the notoriously high false alarm rate. This paper introduces a new host-based anomaly intrusion detection methodology using discontiguous system call patterns, in an attempt to increase detection rates whilst reducing false alarm rates. The key concept is to apply a semantic structure to kernel level system calls in order to reflect intrinsic activities hidden in high-level programming languages, which can help understand program anomaly behaviour. Excellent results were demonstrated using a variety of decision engines, evaluating the KDD98 and UNM data sets, and a new, modern data set. The ADFA Linux data set was created as part of this research using a modern operating system and contemporary hacking methods, and is now publicly available. Furthermore, the new semantic method possesses an inherent resilience to mimicry attacks, and demonstrated a high level of portability between different operating system versions.

Lina Sela Perelman, Waseem Abbas, Xenofon D. Koutsoukos, Saurabh Amin.  2015.  Sensor placement for fault location identification in water networks: A minimum test cover approach. CoRR. abs/1507.07134

This paper focuses on the optimal sensor placement problem for the identification of pipe failure locations in large-scale urban water systems. The problem involves selecting the minimum number of sensors such that every pipe failure can be uniquely localized. This problem can be viewed as a minimum test cover (MTC) problem, which is NP-hard. We consider two approaches to obtain approximate solutions to this problem. In the first approach, we transform the MTC problem to a minimum set cover (MSC) problem and use the greedy algorithm that exploits the submodularity property of the MSC problem to compute the solution to the MTC problem. In the second approach, we develop a new \textit{augmented greedy} algorithm for solving the MTC problem. This approach does not require the transformation of the MTC to MSC. Our augmented greedy algorithm provides in a significant computational improvement while guaranteeing the same approximation ratio as the first approach. We propose several metrics to evaluate the performance of the sensor placement designs. Finally, we present detailed computational experiments for a number of real water distribution networks.

Zhang, M., Chen, Y., Huang, J..  2020.  SE-PPFM: A Searchable Encryption Scheme Supporting Privacy-Preserving Fuzzy Multikeyword in Cloud Systems. IEEE Systems Journal. :1–9.
Cloud computing provides an appearing application for compelling vision in managing big-data files and responding queries over a distributed cloud platform. To overcome privacy revealing risks, sensitive documents and private data are usually stored in the clouds in a cipher-based manner. However, it is inefficient to search the data in traditional encryption systems. Searchable encryption is a useful cryptographic primitive to enable users to retrieve data in ciphertexts. However, the traditional searchable encryptions provide lower search efficiency and cannot carry out fuzzy multikeyword queries. To solve this issue, in this article, we propose a searchable encryption that supports privacy-preserving fuzzy multikeyword search (SE-PPFM) in cloud systems, which is built by asymmetric scalar-product-preserving encryptions and Hadamard product operations. In order to realize the functionality of efficient fuzzy searches, we employ Word2vec as the primitive of machine learning to obtain a fuzzy correlation score between encrypted data and queries predicates. We analyze and evaluate the performance in terms of token of multikeyword, retrieval and match time, file retrieval time and matching accuracy, etc. The experimental results show that our scheme can achieve a higher efficiency in fuzzy multikeyword ciphertext search and provide a higher accuracy in retrieving and matching procedure.
Xiaoyong Li, Huadong Ma, Feng Zhou, Xiaolin Gui.  2015.  Service Operator-Aware Trust Scheme for Resource Matchmaking across Multiple Clouds. Parallel and Distributed Systems, IEEE Transactions on. 26:1419-1429.

This paper proposes a service operator-aware trust scheme (SOTS) for resource matchmaking across multiple clouds. Through analyzing the built-in relationship between the users, the broker, and the service resources, this paper proposes a middleware framework of trust management that can effectively reduces user burden and improve system dependability. Based on multidimensional resource service operators, we model the problem of trust evaluation as a process of multi-attribute decision-making, and develop an adaptive trust evaluation approach based on information entropy theory. This adaptive approach can overcome the limitations of traditional trust schemes, whereby the trusted operators are weighted manually or subjectively. As a result, using SOTS, the broker can efficiently and accurately prepare the most trusted resources in advance, and thus provide more dependable resources to users. Our experiments yield interesting and meaningful observations that can facilitate the effective utilization of SOTS in a large-scale multi-cloud environment.

Driss, Maha, Aljehani, Amani, Boulila, Wadii, Ghandorh, Hamza, Al-Sarem, Mohammed.  2020.  Servicing Your Requirements: An FCA and RCA-Driven Approach for Semantic Web Services Composition. IEEE Access. 8:59326—59339.
The evolution of Service-Oriented Computing (SOC) provides more efficient software development methods for building and engineering new value-added service-based applications. SOC is a computing paradigm that relies on Web services as fundamental elements. Research and technical advancements in Web services composition have been considered as an effective opportunity to develop new service-based applications satisfying complex requirements rapidly and efficiently. In this paper, we present a novel approach enhancing the composition of semantic Web services. The novelty of our approach, as compared to others reported in the literature, rests on: i) mapping user's/organization's requirements with Business Process Modeling Notation (BPMN) and semantic descriptions using ontologies, ii) considering functional requirements and also different types of non-functional requirements, such as quality of service (QoS), quality of experience (QoE), and quality of business (QoBiz), iii) using Formal Concept Analysis (FCA) technique to select the optimal set of Web services, iv) considering composability levels between sequential Web services using Relational Concept Analysis (RCA) technique to decrease the required adaptation efforts, and finally, v) validating the obtained service-based applications by performing an analytical technique, which is the monitoring. The approach experimented on an extended version of the OWLS-TC dataset, which includes more than 10830 Web services descriptions from various domains. The obtained results demonstrate that our approach allows to successfully and effectively compose Web services satisfying different types of user's functional and non-functional requirements.
Montague, E., Jie Xu, Chiou, E..  2014.  Shared Experiences of Technology and Trust: An Experimental Study of Physiological Compliance Between Active and Passive Users in Technology-Mediated Collaborative Encounters. Human-Machine Systems, IEEE Transactions on. 44:614-624.

The aim of this study is to examine the utility of physiological compliance (PC) to understand shared experience in a multiuser technological environment involving active and passive users. Common ground is critical for effective collaboration and important for multiuser technological systems that include passive users since this kind of user typically does not have control over the technology being used. An experiment was conducted with 48 participants who worked in two-person groups in a multitask environment under varied task and technology conditions. Indicators of PC were measured from participants' cardiovascular and electrodermal activities. The relationship between these PC indicators and collaboration outcomes, such as performance and subjective perception of the system, was explored. Results indicate that PC is related to group performance after controlling for task/technology conditions. PC is also correlated with shared perceptions of trust in technology among group members. PC is a useful tool for monitoring group processes and, thus, can be valuable for the design of collaborative systems. This study has implications for understanding effective collaboration.

Luo, Chao, Fei, Yunsi, Kaeli, David.  2019.  Side-Channel Timing Attack of RSA on a GPU. ACM Transactions on Architecture and Code Optimization (TACO). 16:32:1-32:18.
To increase computation throughput, general purpose Graphics Processing Units (GPUs) have been leveraged to accelerate computationally intensive workloads. GPUs have been used as cryptographic engines, improving encryption/decryption throughput and leveraging the GPU's Single Instruction Multiple Thread (SIMT) model. RSA is a widely used public-key cipher and has been ported onto GPUs for signing and decrypting large files. Although performance has been significantly improved, the security of RSA on GPUs is vulnerable to side-channel timing attacks and is an exposure overlooked in previous studies. GPUs tend to be naturally resilient to side-channel attacks, given that they execute a large number of concurrent threads, performing many RSA operations on different data in parallel. Given the degree of parallel execution on a GPU, there will be a significant amount of noise introduced into the timing channel given the thousands of concurrent threads executing concurrently. In this work, we build a timing model to capture the parallel characteristics of an RSA public-key cipher implemented on a GPU. We consider optimizations that include using Montgomery multiplication and sliding-window exponentiation to implement cryptographic operations. Our timing model considers the challenges of parallel execution, complications that do not occur in single-threaded computing platforms. Based on our timing model, we launch successful timing attacks on RSA running on a GPU, extracting the private key of RSA. We also present an effective error detection and correction mechanism. Our results demonstrate that GPU acceleration of RSA is vulnerable to side-channel timing attacks. We propose several countermeasures to defend against this class of attacks.
Béraud-Sudreau, Q., Begueret, J.-B., Mazouffre, O., Pignol, M., Baguena, L., Neveu, C., Deval, Y., Taris, T..  2014.  SiGe Clock and Data Recovery System Based on Injection-Locked Oscillator for 100 Gbit/s Serial Data Link. Solid-State Circuits, IEEE Journal of. 49:1895-1904.

Clock and data recovery (CDR) systems are the first logic blocks in serial data receivers and the latter's performance depends on the CDR. In this paper, a 100 Gbit/s CDR designed in 130 nm BiCMOS SiGe is presented. The CDR uses an injection locked oscillator (ILO) which delivers the 100 GHz clock. The inherent phase shift between the recovered clock and the incoming data is compensated by a feedback loop which performs phase and frequency tracking. Furthermore, a windowed phase comparator has been used, first to lower the classical number of gates, in order to prevent any delay skews between the different phase detector blocks, then to decrease the phase comparator operating frequency, and furthermore to extend the ability to track zero bit patterns The measurements results demonstrate a 100 GHz clock signal extracted from 50 Gb/s input data, with a phase noise as low as 98 dBc/Hz at 100 kHz offset from the carrier frequency. The rms jitter of the 25 GHz recovered data is only 1.2 ps. The power consumption is 1.4 W under 2.3 V power supply.
 

Zhenqi Huang, University of Illinois at Urbana-Champaign, Chuchu Fan, University of Illinois at Urbana-Champaign, Alexandru Mereacre, University of Oxford, Sayan Mitra, University of Illinois at Urbana-Champaign, Marta Kwiatkowska, University of Oxford.  2015.  Simulation-based Verification of Cardiac Pacemakers with Guaranteed Coverage. Special Issue of IEEE Design and Test. 32(5)

Design and testing of pacemaker is challenging because of the need to capture the interaction between the physical processes (e.g. voltage signal in cardiac tissue) and the embedded software (e.g. a pacemaker). At the same time, there is a growing need for design and certification methodologies that can provide quality assurance for the embedded software. We describe recent progress in simulation-based techniques that are capable of ensuring guaranteed coverage. Our methods employ discrep- ancy functions, which impose bounds on system dynamics, and proceed through iteratively constructing over-approximations of the reachable set of states. We are able to prove time bounded safety or produce counterexamples. We illustrate the techniques by analyzing a family of pacemaker designs against time duration requirements and synthesize safe parameter ranges. We conclude by outlining the potential uses of this technology to improve the safety of medical device designs.

Silei Xu, Runhui Li, Lee, P.P.C., Yunfeng Zhu, Liping Xiang, Yinlong Xu, Lui, J.C.S..  2014.  Single Disk Failure Recovery for X-Code-Based Parallel Storage Systems. Computers, IEEE Transactions on. 63:995-1007.

In modern parallel storage systems (e.g., cloud storage and data centers), it is important to provide data availability guarantees against disk (or storage node) failures via redundancy coding schemes. One coding scheme is X-code, which is double-fault tolerant while achieving the optimal update complexity. When a disk/node fails, recovery must be carried out to reduce the possibility of data unavailability. We propose an X-code-based optimal recovery scheme called minimum-disk-read-recovery (MDRR), which minimizes the number of disk reads for single-disk failure recovery. We make several contributions. First, we show that MDRR provides optimal single-disk failure recovery and reduces about 25 percent of disk reads compared to the conventional recovery approach. Second, we prove that any optimal recovery scheme for X-code cannot balance disk reads among different disks within a single stripe in general cases. Third, we propose an efficient logical encoding scheme that issues balanced disk read in a group of stripes for any recovery algorithm (including the MDRR scheme). Finally, we implement our proposed recovery schemes and conduct extensive testbed experiments in a networked storage system prototype. Experiments indicate that MDRR reduces around 20 percent of recovery time of the conventional approach, showing that our theoretical findings are applicable in practice.

Gorur, P., Amrutur, B..  2014.  Skip Decision and Reference Frame Selection for Low-Complexity H.264/AVC Surveillance Video Coding. Circuits and Systems for Video Technology, IEEE Transactions on. 24:1156-1169.

H.264/advanced video coding surveillance video encoders use the Skip mode specified by the standard to reduce bandwidth. They also use multiple frames as reference for motion-compensated prediction. In this paper, we propose two techniques to reduce the bandwidth and computational cost of static camera surveillance video encoders without affecting detection and recognition performance. A spatial sampler is proposed to sample pixels that are segmented using a Gaussian mixture model. Modified weight updates are derived for the parameters of the mixture model to reduce floating point computations. A storage pattern of the parameters in memory is also modified to improve cache performance. Skip selection is performed using the segmentation results of the sampled pixels. The second contribution is a low computational cost algorithm to choose the reference frames. The proposed reference frame selection algorithm reduces the cost of coding uncovered background regions. We also study the number of reference frames required to achieve good coding efficiency. Distortion over foreground pixels is measured to quantify the performance of the proposed techniques. Experimental results show bit rate savings of up to 94.5% over methods proposed in literature on video surveillance data sets. The proposed techniques also provide up to 74.5% reduction in compression complexity without increasing the distortion over the foreground regions in the video sequence.

Chen, L.M., Hsiao, S.-W., Chen, M.C., Liao, W..  2014.  Slow-Paced Persistent Network Attacks Analysis and Detection Using Spectrum Analysis. Systems Journal, IEEE. PP:1-12.

A slow-paced persistent attack, such as slow worm or bot, can bewilder the detection system by slowing down their attack. Detecting such attacks based on traditional anomaly detection techniques may yield high false alarm rates. In this paper, we frame our problem as detecting slow-paced persistent attacks from a time series obtained from network trace. We focus on time series spectrum analysis to identify peculiar spectral patterns that may represent the occurrence of a persistent activity in the time domain. We propose a method to adaptively detect slow-paced persistent attacks in a time series and evaluate the proposed method by conducting experiments using both synthesized traffic and real-world traffic. The results show that the proposed method is capable of detecting slow-paced persistent attacks even in a noisy environment mixed with legitimate traffic.

Hosseinipour, A., Hojabri, H..  2020.  Small-Signal Stability Analysis and Active Damping Control of DC Microgrids Integrated With Distributed Electric Springs. IEEE Transactions on Smart Grid. 11:3737–3747.
Series DC electric springs (DCESs) are a state-of-the-art demand-side management (DSM) technology with the capability to reduce energy storage requirements of DC microgrids by manipulating the power of non-critical loads (NCLs). As the stability of DC microgrids is highly prone to dynamic interactions between the system active and passive components, this study intends to conduct a comprehensive small-signal stability analysis of a community DC microgrid integrated with distributed DCESs considering the effect of destabilizing constant power loads (CPLs). For this purpose, after deriving the small-signal model of a DCES-integrated microgrid, the sensitivity of the system dominant frequency modes to variations of various physical and control parameters is evaluated by means of eigenvalue analysis. Next, an active damping control method based on virtual RC parallel impedance is proposed for series DCESs to compensate for their slow dynamic response and to provide a dynamic stabilization function within the microgrid. Furthermore, impedance-based stability analysis is utilized to study the DC microgrid expandability in terms of integration with multiple DCESs. Finally, several case studies are presented to verify analytical findings of the paper and to evaluate the dynamic performance of the DC microgrid.
Bin Hu, Gharavi, H..  2014.  Smart Grid Mesh Network Security Using Dynamic Key Distribution With Merkle Tree 4-Way Handshaking. Smart Grid, IEEE Transactions on. 5:550-558.

Distributed mesh sensor networks provide cost-effective communications for deployment in various smart grid domains, such as home area networks (HAN), neighborhood area networks (NAN), and substation/plant-generation local area networks. This paper introduces a dynamically updating key distribution strategy to enhance mesh network security against cyber attack. The scheme has been applied to two security protocols known as simultaneous authentication of equals (SAE) and efficient mesh security association (EMSA). Since both protocols utilize 4-way handshaking, we propose a Merkle-tree based handshaking scheme, which is capable of improving the resiliency of the network in a situation where an intruder carries a denial of service attack. Finally, by developing a denial of service attack model, we can then evaluate the security of the proposed schemes against cyber attack, as well as network performance in terms of delay and overhead.

Pearce, Hammond, Pinisetty, Srinivas, Roop, Partha S., Kuo, Matthew M. Y., Ukil, Abhisek.  2020.  Smart I/O Modules for Mitigating Cyber-Physical Attacks on Industrial Control Systems. IEEE Transactions on Industrial Informatics. 16:4659—4669.

Cyber-physical systems (CPSs) are implemented in many industrial and embedded control applications. Where these systems are safety-critical, correct and safe behavior is of paramount importance. Malicious attacks on such CPSs can have far-reaching repercussions. For instance, if elements of a power grid behave erratically, physical damage and loss of life could occur. Currently, there is a trend toward increased complexity and connectivity of CPS. However, as this occurs, the potential attack vectors for these systems grow in number, increasing the risk that a given controller might become compromised. In this article, we examine how the dangers of compromised controllers can be mitigated. We propose a novel application of runtime enforcement that can secure the safety of real-world physical systems. Here, we synthesize enforcers to a new hardware architecture within programmable logic controller I/O modules to act as an effective line of defence between the cyber and the physical domains. Our enforcers prevent the physical damage that a compromised control system might be able to perform. To demonstrate the efficacy of our approach, we present several benchmarks, and show that the overhead for each system is extremely minimal.

Zonouz, S., Davis, C.M., Davis, K.R., Berthier, R., Bobba, R.B., Sanders, W.H..  2014.  SOCCA: A Security-Oriented Cyber-Physical Contingency Analysis in Power Infrastructures. Smart Grid, IEEE Transactions on. 5:3-13.

Contingency analysis is a critical activity in the context of the power infrastructure because it provides a guide for resiliency and enables the grid to continue operating even in the case of failure. In this paper, we augment this concept by introducing SOCCA, a cyber-physical security evaluation technique to plan not only for accidental contingencies but also for malicious compromises. SOCCA presents a new unified formalism to model the cyber-physical system including interconnections among cyber and physical components. The cyber-physical contingency ranking technique employed by SOCCA assesses the potential impacts of events. Contingencies are ranked according to their impact as well as attack complexity. The results are valuable in both cyber and physical domains. From a physical perspective, SOCCA scores power system contingencies based on cyber network configuration, whereas from a cyber perspective, control network vulnerabilities are ranked according to the underlying power system topology.
 

Zonouz, S., Davis, C.M., Davis, K.R., Berthier, R., Bobba, R.B., Sanders, W.H..  2014.  SOCCA: A Security-Oriented Cyber-Physical Contingency Analysis in Power Infrastructures. Smart Grid, IEEE Transactions on. 5:3-13.

Contingency analysis is a critical activity in the context of the power infrastructure because it provides a guide for resiliency and enables the grid to continue operating even in the case of failure. In this paper, we augment this concept by introducing SOCCA, a cyber-physical security evaluation technique to plan not only for accidental contingencies but also for malicious compromises. SOCCA presents a new unified formalism to model the cyber-physical system including interconnections among cyber and physical components. The cyber-physical contingency ranking technique employed by SOCCA assesses the potential impacts of events. Contingencies are ranked according to their impact as well as attack complexity. The results are valuable in both cyber and physical domains. From a physical perspective, SOCCA scores power system contingencies based on cyber network configuration, whereas from a cyber perspective, control network vulnerabilities are ranked according to the underlying power system topology.

Ott, David E..  2018.  Software Defined Infrastructure: Rethinking Cybersecurity with a More Capable Toolset. SIGOPS Oper. Syst. Rev.. 52:129-133.

In Software Defined Infrastructure (SDI), virtualization techniques are used to decouple applications and higher-level services from their underlying physical compute, storage, and network resources. The approach offers a set of powerful new capabilities (isolation, encapsulation, portability, interposition), including the formation of a software-based, infrastructure-wide control plane for orchestrated management. In this position paper, we identify opportunities for revisiting ongoing cybersecurity challenges using SDI as a powerful new toolset. Benefits of this approach can be broadly utilized in public, private, and hybrid clouds, data centers, enterprise computing, IoT deployments, and more. The discussion motivates the research challenge underlying VMware's partnership with the National Science Foundation to fund novel and foundational research in this area. Known as the NSF/VMware Partnership on Software Defined Infrastructure as a Foundation for Clean-Slate Computing Security (SDI-CSCS), the jointly funded university research program is set to begin in the fall of 2017.

Keivanloo, Iman, Rilling, Juergen.  2014.  Software Trustworthiness 2.0-A Semantic Web Enabled Global Source Code Analysis Approach. J. Syst. Softw.. 89:33–50.

There has been an ongoing trend toward collaborative software development using open and shared source code published in large software repositories on the Internet. While traditional source code analysis techniques perform well in single project contexts, new types of source code analysis techniques are ermerging, which focus on global source code analysis challenges. In this article, we discuss how the Semantic Web, can become an enabling technology to provide a standardized, formal, and semantic rich representations for modeling and analyzing large global source code corpora. Furthermore, inference services and other services provided by Semantic Web technologies can be used to support a variety of core source code analysis techniques, such as semantic code search, call graph construction, and clone detection. In this paper, we introduce SeCold, the first publicly available online linked data source code dataset for software engineering researchers and practitioners. Along with its dataset, SeCold also provides some Semantic Web enabled core services to support the analysis of Internet-scale source code repositories. We illustrated through several examples how this linked data combined with Semantic Web technologies can be harvested for different source code analysis tasks to support software trustworthiness. For the case studies, we combine both our linked-data set and Semantic Web enabled source code analysis services with knowledge extracted from StackOverflow, a crowdsourcing website. These case studies, we demonstrate that our approach is not only capable of crawling, processing, and scaling to traditional types of structured data (e.g., source code), but also supports emerging non-structured data sources, such as crowdsourced information (e.g., StackOverflow.com) to support a global source code analysis context.