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I. Ilhan, A. C. Gurbuz, O. Arikan.  2015.  "Sparsity based robust Stretch Processing". 2015 IEEE International Conference on Digital Signal Processing (DSP). :95-99.

Strecth Processing (SP) is a radar signal processing technique that provides high-range resolution with processing large bandwidth signals with lower rate Analog to Digital Converter(ADC)s. The range resolution of the large bandwidth signal is obtained through looking into a limited range window and low rate ADC samples. The target space in the observed range window is sparse and Compressive sensing(CS) is an important tool to further decrease the number of measurements and sparsely reconstruct the target space for sparse scenes with a known basis which is the Fourier basis in the general application of SP. Although classical CS techniques might be directly applied to SP, due to off-grid targets reconstruction performance degrades. In this paper, applicability of compressive sensing framework and its sparse signal recovery techniques to stretch processing is studied considering off-grid cases. For sparsity based robust SP, Perturbed Parameter Orthogonal Matching Pursuit(PPOMP) algorithm is proposed. PPOMP is an iterative technique that estimates off-grid target parameters through a gradient descent. To compute the error between actual and reconstructed parameters, Earth Movers Distance(EMD) is used. Performance of proposed algorithm are compared with classical CS and SP techniques.

I. Mukherjee, R. Ganguly.  2015.  "Privacy preserving of two sixteen-segmented image using visual cryptography". 2015 IEEE International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN). :417-422.

With the advancement of technology, the world has not only become a better place to live in but have also lost the privacy and security of shared data. Information in any form is never safe from the hands of unauthorized accessing individuals. Here, in our paper we propose an approach by which we can preserve data using visual cryptography. In this paper, two sixteen segment displayed text is broken into two shares that does not reveal any information about the original images. By this process we have obtained satisfactory results in statistical and structural testes.

Iakovakis, Dimitrios, Hadjileontiadis, Leontios.  2016.  Standing Hypotension Prediction Based on Smartwatch Heart Rate Variability Data: A Novel Approach. Proceedings of the 18th International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct. :1109–1112.

The number of wearable and smart devices which are connecting every day in the Internet of Things (IoT) is continuously growing. We have a great opportunity though to improve the quality of life (QoL) standards by adding medical value to these devices. Especially, by exploiting IoT technology, we have the potential to create useful tools which utilize the sensors to provide biometric data. This novel study aims to use a smartwatch, independent from other hardware, to predict the Blood Pressure (BP) drop caused by postural changes. In cases that the drop is due to orthostatic hypotension (OH) can cause dizziness or even faint factors, which increase the risk of fall in the elderly but, as well as, in younger groups of people. A mathematical prediction model is proposed here which can reduce the risk of fall due to OH by sensing heart rate variability (data and drops in systolic BP after standing in a healthy group of 10 subjects. The experimental results justify the efficiency of the model, as it can perform correct prediction in 86.7% of the cases, and are encouraging enough for extending the proposed approach to pathological cases, such as patients with Parkinson's disease, involving large scale experiments.

Ibarra, Jaime, Javed Butt, Usman, Do, Anh, Jahankhani, Hamid, Jamal, Arshad.  2019.  Ransomware Impact to SCADA Systems and its Scope to Critical Infrastructure. 2019 IEEE 12th International Conference on Global Security, Safety and Sustainability (ICGS3). :1–12.
SCADA systems are being constantly migrated to modern information and communication technologies (ICT) -based systems named cyber-physical systems. Unfortunately, this allows attackers to execute exploitation techniques into these architectures. In addition, ransomware insertion is nowadays the most popular attacking vector because it denies the availability of critical files and systems until attackers receive the demanded ransom. In this paper, it is analysed the risk impact of ransomware insertion into SCADA systems and it is suggested countermeasures addressed to the protection of SCADA systems and its components to reduce the impact of ransomware insertion.
Ibdah, D., Kanani, M., Lachtar, N., Allan, N., Al-Duwairi, B..  2017.  On the security of SDN-enabled smartgrid systems. 2017 International Conference on Electrical and Computing Technologies and Applications (ICECTA). :1–5.

Software Defined Networks (SDNs) is a new networking paradigm that has gained a lot of attention in recent years especially in implementing data center networks and in providing efficient security solutions. The popularity of SDN and its attractive security features suggest that it can be used in the context of smart grid systems to address many of the vulnerabilities and security problems facing such critical infrastructure systems. This paper studies the impact of different cyber attacks that can target smart grid communication network which is implemented as a software defined network on the operation of the smart grid system in general. In particular, we perform different attack scenarios including DDoS attacks, location highjacking and link overloading against SDN networks of different controller types that include POX, Floodlight and RYU. Our experiments were carried out using the mininet simulator. The experiments show that SDN-enabled smartgrid systems are vulnerable to different types of attacks.

Iber, J., Rauter, T., Krisper, M., Kreiner, C..  2017.  An Integrated Approach for Resilience in Industrial Control Systems. 2017 47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W). :67–74.
New generations of industrial control systems offer higher performance, they are distributed, and it is very likely that they are internet connected in one way or another. These trends raise new challenges in the contexts of reliability and security. We propose a novel approach that tackles the complexity of industrial control systems at design time and run time. At design time our target is to ease the configuration and verification of controller configurations through model-driven engineering techniques together with the contract-based design paradigm. At run time the information from design time is reused in order to support a modular and distributed self-adaptive software system that aims to increase reliability and security. The industrial setting of the presented approach are control devices for hydropower plant units.
Ibrahim, Ahmad, Sadeghi, Ahmad-Reza, Tsudik, Gene, Zeitouni, Shaza.  2016.  DARPA: Device Attestation Resilient to Physical Attacks. Proceedings of the 9th ACM Conference on Security & Privacy in Wireless and Mobile Networks. :171–182.

As embedded devices (under the guise of "smart-whatever") rapidly proliferate into many domains, they become attractive targets for malware. Protecting them from software and physical attacks becomes both important and challenging. Remote attestation is a basic tool for mitigating such attacks. It allows a trusted party (verifier) to remotely assess software integrity of a remote, untrusted, and possibly compromised, embedded device (prover). Prior remote attestation methods focus on software (malware) attacks in a one-verifier/one-prover setting. Physical attacks on provers are generally ruled out as being either unrealistic or impossible to mitigate. In this paper, we argue that physical attacks must be considered, particularly, in the context of many provers, e.g., a network, of devices. As- suming that physical attacks require capture and subsequent temporary disablement of the victim device(s), we propose DARPA, a light-weight protocol that takes advantage of absence detection to identify suspected devices. DARPA is resilient against a very strong adversary and imposes minimal additional hardware requirements. We justify and identify DARPA's design goals and evaluate its security and costs.

Ibrahim, Naseem.  2014.  Trustworthy Context-dependent Services. Proceedings of the 2014 Symposium and Bootcamp on the Science of Security. :20:1–20:2.

With the wide popularity of Cloud Computing, Service-oriented Computing is becoming the de-facto approach for the development of distributed systems. This has introduced the issue of trustworthiness with respect to the services being provided. Service Requesters are provided with a wide range of services that they can select from. Usually the service requester compare between these services according to their cost and quality. One essential part of the quality of a service is the trustworthiness properties of such services. Traditional service models focuses on service functionalities and cost when defining services. This paper introduces a new service model that extends traditional service models to support trustworthiness properties.

Ibrahim, Rosziati, Omotunde, Habeeb.  2017.  A Hybrid Threat Model for Software Security Requirement Specification - IEEE Conference Publication.

Security is often treated as secondary or a non- functional feature of software which influences the approach of vendors and developers when describing their products often in terms of what it can do (Use Cases) or offer customers. However, tides are beginning to change as more experienced customers are beginning to demand for more secure and reliable software giving priority to confidentiality, integrity and privacy while using these applications. This paper presents the MOTH (Modeling Threats with Hybrid Techniques) framework designed to help organizations secure their software assets from attackers in order to prevent any instance of SQL Injection Attacks (SQLIAs). By focusing on the attack vectors and vulnerabilities exploited by the attackers and brainstorming over possible attacks, developers and security experts can better strategize and specify security requirements required to create secure software impervious to SQLIAs. A live web application was considered in this research work as a case study and results obtained from the hybrid models extensively exposes the vulnerabilities deep within the application and proposed resolution plans for blocking those security holes exploited by SQLIAs.
 

Ibrokhimov, Sanjar, Hui, Kueh Lee, Abdulhakim Al-Absi, Ahmed, lee, hoon jae, Sain, Mangal.  2019.  Multi-Factor Authentication in Cyber Physical System: A State of Art Survey. 2019 21st International Conference on Advanced Communication Technology (ICACT). :279–284.
Digital Multifactor authentication is one of the best ways to make secure authentication. It covers many different areas of a Cyber-connected world, including online payments, communications, access right management, etc. Most of the time, Multifactor authentication is little complex as it require extra step from users. With two-factor authentication, along with the user-ID and password, user also needs to enter a special code which they normally receive by short message service or some special code which they got in advance. This paper will discuss the evolution from single authentication to Multi-Factor Authentication (MFA) starting from Single-Factor Authentication (SFA) and through Two-Factor Authentication (2FA). In addition, this paper presents five high-level categories of features of user authentication in the gadget-free world including security, privacy, and usability aspects. These are adapted and extended from earlier research on web authentication methods. In conclusion, this paper gives future research directions and open problems that stem from our observations.
Idayanti, N., Dedi, Nanang, T. K., Sudrajat, Septiani, A., Mulyadi, D., Irasari, P..  2016.  The implementation of hybrid bonded permanent magnet on permanent magnet generator for renewable energy power plants. 2016 International Seminar on Intelligent Technology and Its Applications (ISITIA). :557–560.

{This paper describes application of permanent magnet on permanent magnet generator (PMG) for renewable energy power plants. Permanent magnet used are bonded hybrid magnet that was a mixture of barium ferrite magnetic powders 50 wt % and NdFeB magnetic powders 50 wt % with 15 wt % of adhesive polymer as a binder. Preparation of bonded hybrid magnets by hot press method at a pressure of 2 tons and temperature of 200°C for 15 minutes. The magnetic properties obtained were remanence induction (Br) =1.54 kG, coercivity (Hc) = 1.290 kOe, product energy maximum (BHmax) = 0.28 MGOe, surface remanence induction (Br) = 1200 gauss

Idriss, H., Idriss, T., Bayoumi, M..  2017.  A highly reliable dual-arbiter PUF for lightweight authentication protocols. 2017 IEEE International Conference on RFID Technology Application (RFID-TA). :248–253.

PUFs are an emerging security primitive that offers a lightweight security alternative to highly constrained devices like RFIDs. PUFs used in authentication protocols however suffer from unreliable outputs. This hinders their scaling, which is necessary for increased security, and makes them also problematic to use with cryptographic functions. We introduce a new Dual Arbiter PUF design that reveals additional information concerning the stability of the outputs. We then employ a novel filtering scheme that discards unreliable outputs with a minimum number of evaluations, greatly reducing the BER of the PUF.

Idrus, S. Z. Syed, Cherrier, E., Rosenberger, C., Mondal, S., Bours, P..  2015.  Keystroke dynamics performance enhancement with soft biometrics. IEEE International Conference on Identity, Security and Behavior Analysis (ISBA 2015). :1–7.

It is accepted that the way a person types on a keyboard contains timing patterns, which can be used to classify him/her, is known as keystroke dynamics. Keystroke dynamics is a behavioural biometric modality, whose performances, however, are worse than morphological modalities such as fingerprint, iris recognition or face recognition. To cope with this, we propose to combine keystroke dynamics with soft biometrics. Soft biometrics refers to biometric characteristics that are not sufficient to authenticate a user (e.g. height, gender, skin/eye/hair colour). Concerning keystroke dynamics, three soft categories are considered: gender, age and handedness. We present different methods to combine the results of a classical keystroke dynamics system with such soft criteria. By applying simple sum and multiply rules, our experiments suggest that the combination approach performs better than the classification approach with best result of 5.41% of equal error rate. The efficiency of our approaches is illustrated on a public database.

Iffländer, Lukas, Walter, Jürgen, Eismann, Simon, Kounev, Samuel.  2018.  The Vision of Self-Aware Reordering of Security Network Function Chains. Companion of the 2018 ACM/SPEC International Conference on Performance Engineering. :1-4.

Services provided online are subject to various types of attacks. Security appliances can be chained to protect a system against multiple types of network attacks. The sequence of appliances has a significant impact on the efficiency of the whole chain. While the operation of security appliance chains is currently based on a static order, traffic-aware reordering of security appliances may significantly improve efficiency and accuracy. In this paper, we present the vision of a self-aware system to automatically reorder security appliances according to incoming traffic. To achieve this, we propose to apply a model-based learning, reasoning, and acting (LRA-M) loop. To this end, we describe a corresponding system architecture and explain its building blocks.

Ifinedo, Princely.  2017.  Effects of Organization Insiders' Self-Control and Relevant Knowledge on Participation in Information Systems Security Deviant Behavior: [Best Paper Nominee]. Proceedings of the 2017 ACM SIGMIS Conference on Computers and People Research. :79–86.

Disastrous consequences tend to befall organizations whose employees participate in information systems security deviant behavior (ISSDB) (e.g., connecting computers to the Internet through an insecure wireless network and opening emails from unverified senders). Although organizations recognize that ISSDB poses a serious problem, understanding what motivates its occurrence continues to be a key concern. While studies on information technology (IT) misuse abounds, research specifically focusing on the drivers of ISSDB remains scant in the literature. Using self-control theory, augmented with knowledge of relevant factors, this study examined the effects of employees' self-control, knowledge of computers/IT, and information systems (IS) security threats and risks on participation in ISSDB. A research model, including the aforementioned factors, was proposed and tested using the partial least squares technique. Data was collected from a survey of Canadian professionals. The results show that low self-control and lower levels of knowledge of computers/IT are related to employees' involvement in ISSDB. The data did not provide a meaningful relationship between employees' knowledge of IS security threats/risks and desire to participate in ISSDB.

Iftikhar, Jawad, Hussain, Sajid, Mansoor, Khwaja, Ali, Zeeshan, Chaudhry, Shehzad Ashraf.  2019.  Symmetric-Key Multi-Factor Biometric Authentication Scheme. 2019 2nd International Conference on Communication, Computing and Digital systems (C-CODE). :288–292.
Authentication is achieved by using different techniques, like using smart-card, identity password and biometric techniques. Some of the proposed schemes use a single factor for authentication while others combine multiple ways to provide multi-factor authentication for better security. lately, a new scheme for multi-factor authentication was presented by Cao and Ge and claimed that their scheme is highly secure and can withstand against all known attacks. In this paper, it is revealed that their scheme is still vulnerable and have some loopholes in term of reflection attack. Therefore, an improved scheme is proposed to overcome the security weaknesses of Cao and Ge's scheme. The proposed scheme resists security attacks and secure. Formal testing is carried out under a broadly-accepted simulated tool ProVerif which demonstrates that the proposed scheme is well secure.
Igarashi, Takeo, Shono, Naoyuki, Kin, Taichi, Saito, Toki.  2016.  Interactive Volume Segmentation with Threshold Field Painting. Proceedings of the 29th Annual Symposium on User Interface Software and Technology. :403–413.

An interactive method for segmentation and isosurface extraction of medical volume data is proposed. In conventional methods, users decompose a volume into multiple regions iteratively, segment each region using a threshold, and then manually clean the segmentation result by removing clutter in each region. However, this is tedious and requires many mouse operations from different camera views. We propose an alternative approach whereby the user simply applies painting operations to the volume using tools commonly seen in painting systems, such as flood fill and brushes. This significantly reduces the number of mouse and camera control operations. Our technical contribution is in the introduction of the threshold field, which assigns spatially-varying threshold values to individual voxels. This generalizes discrete decomposition of a volume into regions and segmentation using a constant threshold in each region, thereby offering a much more flexible and efficient workflow. This paper describes the details of the user interaction and its implementation. Furthermore, the results of a user study are discussed. The results indicate that the proposed method can be a few times faster than a conventional method.

Ignacio X. Dominguez, Prairie Rose Goodwin,, David L. Roberts,, Robert St. Amant.  2016.  Human Subtlety Proofs: Using Computer Games to Model Cognitive Processes for Cybersecurity. International Journal of Human-Computer Interaction, special issue on Cognitive Foundations for Human-Computer Interaction.

This article describes an emerging direction in the intersection between human–computer interaction and cognitive science: the use of cognitive models to give insight into the challenges of cybersecurity (cyber-SA). The article gives a brief overview of work in different areas of cyber-SA where cognitive modeling research plays a role, with regard to direct interaction between end users and computer systems and with regard to the needs of security analysts working behind the scenes. The problem of distinguishing between human users and automated agents (bots) interacting with computer systems is introduced, as well as ongoing efforts toward building Human Subtlety Proofs (HSPs), persistent and unobtrusive windows into human cognition with direct application to cyber-SA. Two computer games are described, proxies to illustrate different ways in which cognitive modeling can potentially contribute to the development of HSPs and similar cyber-SA applications.

 

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Ignacio X. Dominguez, Jayant Dhawan, Robert St. Amant, David L. Roberts.  2016.  JIVUI: JavaScript Interface for Visualization of User Interaction. Proceedings of the International Conference on Cognitive Modeling (ICCM). :125–130.

In this paper we describe the JavaScript Interface for Visu- alization of User Interaction (JIVUI): a modular, Web-based, and customizable visualization tool that shows an animation of the trace of a user interaction with a graphical interface, or of predictions made by cognitive models of user interaction. Any combination of gaze, mouse, and keyboard data can be repro- duced within a user-provided interface. Although customiz- able, the tool includes a series of plug-ins to support common visualization tasks, including a timeline of input device events and perceptual and cognitive operators based on the Model Hu- man Processor and TYPIST. We talk about our use of this tool to support hypothesis generation, assumption validation, and to guide our modeling efforts. 

Ignacio X. Dominguez, Prairie Rose Goodwin, David L. Roberts, Robert St. Amant.  2016.  Human Subtlety Proofs: Using Computer Games to Model Cognitive Processes for Cybersecurity. International Journal of Human–Computer Interaction. :null.

AbstractThis article describes an emerging direction in the intersection between human-computer interaction and cognitive science: the use of cognitive models to give insight into the challenges of cybersecurity. The article gives a brief overview of work in different areas of cybersecurity where cognitive modeling research plays a role, with regard to direct interaction between end users and computer systems and with regard to the needs of security analysts working behind the scenes. The problem of distinguishing between human users and automated agents (bots) interacting with computer systems is introduced, as well as ongoing efforts toward building Human Subtlety Proofs, persistent and unobtrusive windows into human cognition with direct application to cybersecurity. Two computer games are described, proxies to illustrate different ways in which cognitive modeling can potentially contribute to the development of HSPs and similar cybersecurity applications.

Ignacio X. Dominguez, Prairie Rose Goodwin, David L. Roberts, Robert St. Amant.  2016.  Human Subtlety Proofs: Using Computer Games to Model Cognitive Processes for Cybersecurity. International Journal of Human–Computer Interaction.

This article describes an emerging direction in the intersection between human-computer interaction and cognitive science: the use of cognitive models to give insight into the challenges of cybersecurity. The article gives a brief overview of work in different areas of cybersecurity where cognitive modeling research plays a role, with regard to direct interaction between end users and computer systems and with regard to the needs of security analysts working behind the scenes. The problem of distinguishing between human users and automated agents (bots) interacting with computer systems is introduced, as well as ongoing efforts toward building Human Subtlety Proofs, persistent and unobtrusive windows into human cognition with direct application to cybersecurity. Two computer games are described, proxies to illustrate different ways in which cognitive modeling can potentially contribute to the development of HSPs and similar cybersecurity applications.

Ignacio X. Dominguez, Jayant Dhawan, Robert St. Amant, David L. Roberts.  In Press.  Exploring the Effects of Different Text Stimuli on Typing Behavior. International Conference on Cognitive Modeling.

In this work we explore how different cognitive processes af- fected typing patterns through a computer game we call The Typing Game. By manipulating the players’ familiarity with the words in our game through their similarity to dictionary words, and by allowing some players to replay rounds, we found that typing speed improves with familiarity with words, and also with practice, but that these are independent of the number of mistakes that are made when typing. We also found that users who had the opportunity to replay rounds exhibited different typing patterns even before replaying the rounds. 

Ignacio X. Dominguez, Jayant Dhawan, Robert St. Amant, David L. Roberts.  2016.  Exploring the effects of different text stimuli on typing behavior. Proceedings of the International Conference on Cognitive Modeling {(ICCM)}. :175–181.
Ignacio X. Dominguez, Alok Goel, David L. Roberts, Robert St. Amant.  2015.  Detecting Abnormal User Behavior Through Pattern-mining Input Device Analytics. Proceedings of the 2015 Symposium and Bootcamp on the Science of Security (HotSoS-15).
Ijaz, M., Durad, M. H., Ismail, M..  2019.  Static and Dynamic Malware Analysis Using Machine Learning. 2019 16th International Bhurban Conference on Applied Sciences and Technology (IBCAST). :687–691.

Malware detection is an indispensable factor in security of internet oriented machines. The combinations of different features are used for dynamic malware analysis. The different combinations are generated from APIs, Summary Information, DLLs and Registry Keys Changed. Cuckoo sandbox is used for dynamic malware analysis, which is customizable, and provide good accuracy. More than 2300 features are extracted from dynamic analysis of malware and 92 features are extracted statically from binary malware using PEFILE. Static features are extracted from 39000 malicious binaries and 10000 benign files. Dynamically 800 benign files and 2200 malware files are analyzed in Cuckoo Sandbox and 2300 features are extracted. The accuracy of dynamic malware analysis is 94.64% while static analysis accuracy is 99.36%. The dynamic malware analysis is not effective due to tricky and intelligent behaviours of malwares. The dynamic analysis has some limitations due to controlled network behavior and it cannot be analyzed completely due to limited access of network.