Visible to the public Biblio

Found 4058 results

Filters: Keyword is Resiliency  [Clear All Filters]
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z   [Show ALL]
A
A. Rawat, A. K. Singh, J. Jithin, N. Jeyanthi, R. Thandeeswaran.  2016.  RSJ Approach for User Authentication. Proceeding AICTC '16 Proceedings of the International Conference on Advances in Information Communication Technology & Computing Article No. 101 .

Some of the common works like, upload and retrieval of data, buying and selling things, earning and donating or transaction of money etc., are the most common works performed in daily life through internet. For every user who is accessing the internet regularly, their highest priority is to make sure that there data is secured. Users are willing to pay huge amount of money to the service provider for maintaining the security. But the intention of malicious users is to access and misuse others data. For that they are using zombie bots. Always Bots are not the only malicious, legitimate authorized user can also impersonate to access the data illegally. This makes the job tougher to discriminate between the bots and boots. For providing security form that threats, here we are proposing a novel RSJ Approach by User Authentication. RSJ approach is a secure way for providing the security to the user form both bots and malicious users.

Aafer, Yousra, Tao, Guanhong, Huang, Jianjun, Zhang, Xiangyu, Li, Ninghui.  2018.  Precise Android API Protection Mapping Derivation and Reasoning. Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security. :1151-1164.

The Android research community has long focused on building an Android API permission specification, which can be leveraged by app developers to determine the optimum set of permissions necessary for a correct and safe execution of their app. However, while prominent existing efforts provide a good approximation of the permission specification, they suffer from a few shortcomings. Dynamic approaches cannot generate complete results, although accurate for the particular execution. In contrast, static approaches provide better coverage, but produce imprecise mappings due to their lack of path-sensitivity. In fact, in light of Android's access control complexity, the approximations hardly abstract the actual co-relations between enforced protections. To address this, we propose to precisely derive Android protection specification in a path-sensitive fashion, using a novel graph abstraction technique. We further showcase how we can apply the generated maps to tackle security issues through logical satisfiability reasoning. Our constructed maps for 4 Android Open Source Project (AOSP) images highlight the significance of our approach, as \textasciitilde41% of APIs' protections cannot be correctly modeled without our technique.

Abaid, Z., Kaafar, M. A., Jha, S..  2017.  Early Detection of In-the-Wild Botnet Attacks by Exploiting Network Communication Uniformity: An Empirical Study. 2017 IFIP Networking Conference (IFIP Networking) and Workshops. :1–9.

Distributed attacks originating from botnet-infected machines (bots) such as large-scale malware propagation campaigns orchestrated via spam emails can quickly affect other network infrastructures. As these attacks are made successful only by the fact that hundreds of infected machines engage in them collectively, their damage can be avoided if machines infected with a common botnet can be detected early rather than after an attack is launched. Prior studies have suggested that outgoing bot attacks are often preceded by other ``tell-tale'' malicious behaviour, such as communication with botnet controllers (C&C servers) that command botnets to carry out attacks. We postulate that observing similar behaviour occuring in a synchronised manner across multiple machines is an early indicator of a widespread infection of a single botnet, leading potentially to a large-scale, distributed attack. Intuitively, if we can detect such synchronised behaviour early enough on a few machines in the network, we can quickly contain the threat before an attack does any serious damage. In this work we present a measurement-driven analysis to validate this intuition. We empirically analyse the various stages of malicious behaviour that are observed in real botnet traffic, and carry out the first systematic study of the network behaviour that typically precedes outgoing bot attacks and is synchronised across multiple infected machines. We then implement as a proof-of-concept a set of analysers that monitor synchronisation in botnet communication to generate early infection and attack alerts. We show that with this approach, we can quickly detect nearly 80% of real-world spamming and port scanning attacks, and even demonstrate a novel capability of preventing these attacks altogether by predicting them before they are launched.

Abate, Alessandro.  2017.  Formal Verification of Complex Systems: Model-Based and Data-Driven Methods. Proceedings of the 15th ACM-IEEE International Conference on Formal Methods and Models for System Design. :91–93.

Two known shortcomings of standard techniques in formal verification are the limited capability to provide system-level assertions, and the scalability to large, complex models, such as those needed in Cyber-Physical Systems (CPS) applications. Leveraging data, which nowadays is becoming ever more accessible, has the potential to mitigate such limitations. However, this leads to a lack of formal proofs that are needed for modern safety-critical systems. This contribution presents a research initiative that addresses these shortcomings by bringing model-based techniques and data-driven methods together, which can help pushing the envelope of existing algorithms and tools in formal verification and thus expanding their applicability to complex engineering systems, such as CPS. In the first part of the contribution, we discuss a new, formal, measurement-driven and model-based automated technique, for the quantitative verification of physical systems with partly unknown dynamics. We formulate this setup as a data-driven Bayesian inference problem, formally embedded within a quantitative, model-based verification procedure. We argue that the approach can be applied to complex physical systems that are key for CPS applications, dealing with spatially continuous variables, evolving under complex dynamics, driven by external inputs, and accessed under noisy measurements. In the second part of the contribution, we concentrate on systems represented by models that evolve under probabilistic and heterogeneous (continuous/discrete - that is "hybrid" - as well as nonlinear) dynamics. Such stochastic hybrid models (also known as SHS) are a natural mathematical framework for CPS. With focus on model-based verification procedures, we provide algorithms for quantitative model checking of temporal specifications on SHS with formal guarantees. This is attained via the development of formal abstraction techniques that are based on quantitative approximations. Theory is complemented by algorithms, all packaged in software tools that are available to users, and which are applied here in the domain of Smart Energy.

Abbas, Waseem, Perelman, Lina Sela, Amin, Saurabh, Koutsoukos, Xenofon.  2017.  Resilient Sensor Placement for Fault Localization in Water Distribution Networks. Proceedings of the 8th International Conference on Cyber-Physical Systems. :165–174.

In this paper, we study the sensor placement problem in urban water networks that maximizes the localization of pipe failures given that some sensors give incorrect outputs. False output of a sensor might be the result of degradation in sensor's hardware, software fault, or might be due to a cyber attack on the sensor. Incorrect outputs from such sensors can have any possible values which could lead to an inaccurate localization of a failure event. We formulate the optimal sensor placement problem with erroneous sensors as a set multicover problem, which is NP-hard, and then discuss a polynomial time heuristic to obtain efficient solutions. In this direction, we first examine the physical model of the disturbance propagating in the network as a result of a failure event, and outline the multi-level sensing model that captures several event features. Second, using a combinatorial approach, we solve the problem of sensor placement that maximizes the localization of pipe failures by selecting m sensors out of which at most e give incorrect outputs. We propose various localization performance metrics, and numerically evaluate our approach on a benchmark and a real water distribution network. Finally, using computational experiments, we study relationships between design parameters such as the total number of sensors, the number of sensors with errors, and extracted signal features.

AbdAllah, E. G., Zulkernine, M., Hassanein, H. S..  2018.  A Security Framework for ICN Traffic Management. 2018 IEEE 16th Intl Conf on Dependable, Autonomic and Secure Computing, 16th Intl Conf on Pervasive Intelligence and Computing, 4th Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress(DASC/PiCom/DataCom/CyberSciTech). :78-85.

Information Centric Networking (ICN) changed the communication model from host-based to content-based to cope with the high volume of traffic due to the rapidly increasing number of users, data objects, devices, and applications. ICN communication model requires new security solutions that will be integrated with ICN architectures. In this paper, we present a security framework to manage ICN traffic by detecting, preventing, and responding to ICN attacks. The framework consists of three components: availability, access control, and privacy. The availability component ensures that contents are available for legitimate users. The access control component allows only legitimate users to get restrictedaccess contents. The privacy component prevents attackers from knowing content popularities or user requests. We also show our specific solutions as examples of the framework components.

Abdelbari, Hassan, Shafi, Kamran.  2017.  A Genetic Programming Ensemble Method for Learning Dynamical System Models. Proceedings of the 8th International Conference on Computer Modeling and Simulation. :47–51.
Modelling complex dynamical systems plays a crucial role to understand several phenomena in different domains such as physics, engineering, biology and social sciences. In this paper, a genetic programming ensemble method is proposed to learn complex dynamical systems' underlying mathematical models, represented as differential equations, from systems' time series observations. The proposed method relies on decomposing the modelling space based on given variable dependencies. An ensemble of learners is then applied in this decomposed space and their output is combined to generate the final model. Two examples of complex dynamical systems are used to test the performance of the proposed methodology where the standard genetic programming method has struggled to find matching model equations. The empirical results show the effectiveness of the proposed methodology in learning closely matching structure of almost all system equations.
Abdellatif, Karim M., Chotin-Avot, Roselyne, Mehrez, Habib.  2016.  AEGIS-Based Efficient Solution for Secure Reconfiguration of FPGAs. Proceedings of the Third Workshop on Cryptography and Security in Computing Systems. :37–40.

The reconfiguration of FPGAs includes downloading the bit-stream file which contains the new design on the FPGA. The option to reconfigure FPGAs dynamically opens up the threat of stealing the Intellectual Property (IP) of the design. Since the configuration is usually stored in external memory, this can be easily tapped and read out by an eaves-dropper. This work presents a low cost solution in order to secure the reconfiguration of FPGAs. The proposed solution is based on an efficient-compact hardware implementation for AEGIS which is considered one of the candidates to the competition of CAESAR. The proposed architecture depends on using 1/4 AES-round for reducing the consumed area. We evaluated the presented design using 90 and 65 nm technologies. Our comparison to existing AES-based schemes reveals that the proposed design is better in terms of the hardware performance (Thr./mm2).

Abdellatif, Lasbahani, Chhiba, Mostafa, Mjihil, Oussama.  2017.  Deals with Integrating of Security Specifications During Software Design Phase Using MDA Approach. Proceedings of the Second International Conference on Internet of Things, Data and Cloud Computing. :196:1–196:7.
There are many recent propositions treating Model Driven Architecture (MDA) approaches to perform and automate code generation from design models. To the best of our knowledge and research, most of these propositions have been only focused on functional aspect by allowing code generation without considering this the non-functional aspect at the same time so that to generate secure object-oriented software basing on MDA approach. In this context, we are adding further details to integrate the security policies required in the form of secure models. The systems specification models will be enhanced with security requirements at different abstraction levels through a set of transformation models. Improving functional models with security constraints allow us to incorporate the security needs and automating generating secure applications with their security infrastructure using MDA approach. After carrying out a modification on MDA processes and UML meta-model to cover a better representation of security policies of an organization by updating different existing software engineering process to take into account nonfunctional aspect along with their functional aspect. This work presents a new methodology based on MDA approach and existing security technologies for allowing the integration of the proposed security requirements, which are obtained from security experts, during the system design. Within this context, we have focused on the essential elements of security, such as data encryption, Message Integrity, and Access Control in order to express the importance of merging both the functional and non-functional aspects altogether. We have chosen these properties to practically illustrate how to generate secure applications including their security policies. Then the source code will be obtained automatically from Platform Specific Models (PSM) by applying a set of model transformations and using a code generator designed for this mission. In addition, we can inject also other security-related properties, such as Availability, Traceability, non-repudiation, and Scalability issues during the whole development process by following the same methodology. these properties will be treated in the future work.
Abdelraheem, Mohamed Ahmed, Gehrmann, Christian, Lindström, Malin, Nordahl, Christian.  2016.  Executing Boolean Queries on an Encrypted Bitmap Index. Proceedings of the 2016 ACM on Cloud Computing Security Workshop. :11–22.

We propose a simple and efficient searchable symmetric encryption scheme based on a Bitmap index that evaluates Boolean queries. Our scheme provides a practical solution in settings where communications and computations are very constrained as it offers a suitable trade-off between privacy and performance.

Abdelwahed, N., Letaifa, A. Ben, Asmi, S. El.  2018.  Content Based Algorithm Aiming to Improve the WEB\_QoE Over SDN Networks. 2018 32nd International Conference on Advanced Information Networking and Applications Workshops (WAINA). :153–158.
Since the 1990s, the concept of QoE has been increasingly present and many scientists take it into account within different fields of application. Taking for example the case of video streaming, the QoE has been well studied in this case while for the web the study of its QoE is relatively neglected. The Quality of Experience (QoE) is the set of objective and subjective characteristics that satisfy retain or give confidence to a user through the life cycle of a service. There are researches that take the different measurement metrics of QoE as a subject, others attack new ways to improve this QoE in order to satisfy the customer and gain his loyalty. In this paper, we focus on the web QoE that is declined by researches despite its great importance given the complexity of new web pages and their utility that is increasingly critical. The wealth of new web pages in images, videos, audios etc. and their growing significance prompt us to write this paper, in which we discuss a new method that aims to improve the web QoE in a software-defined network (SDN). Our proposed method consists in automating and making more flexible the management of the QoE improvement of the web pages and this by writing an algorithm that, depending on the case, chooses the necessary treatment to improve the web QoE of the page concerned and using both web prefetching and caching to accelerate the data transfer when the user asks for it. The first part of the paper discusses the advantages and disadvantages of existing works. In the second part we propose an automatic algorithm that treats each case with the appropriate solution that guarantees its best performance. The last part is devoted to the evaluation of the performance.
Abdeslam, W. Oulad, Tabii, Y., El Kadiri, K. E..  2017.  Adaptive Appearance Model in Particle Filter Based Visual Tracking. Proceedings of the 2Nd International Conference on Big Data, Cloud and Applications. :85:1–85:5.

Visual Tracking methods based on particle filter framework uses frequently the state space information of the target object to calculate the observation model, However this often gives a poor estimate if unexpected motions happen, or under conditions of cluttered backgrounds illumination changes, because the model explores the state space without any additional information of current state. In order to avoid the tracking failure, we address in this paper, Particle filter based visual tracking, in which the target appearance model is represented through an adaptive conjunction of color histogram, and space based appearance combining with velocity parameters, then the appearance models is estimated using particles whose weights, are incrementally updated for dynamic adaptation of the cue parametrization.

Abdi, Fardin, Tabish, Rohan, Rungger, Matthias, Zamani, Majid, Caccamo, Marco.  2017.  Application and System-level Software Fault Tolerance Through Full System Restarts. Proceedings of the 8th International Conference on Cyber-Physical Systems. :197–206.

Due to the growing performance requirements, embedded systems are increasingly more complex. Meanwhile, they are also expected to be reliable. Guaranteeing reliability on complex systems is very challenging. Consequently, there is a substantial need for designs that enable the use of unverified components such as real-time operating system (RTOS) without requiring their correctness to guarantee safety. In this work, we propose a novel approach to design a controller that enables the system to restart and remain safe during and after the restart. Complementing this controller with a switching logic allows the system to use complex, unverified controller to drive the system as long as it does not jeopardize safety. Such a design also tolerates faults that occur in the underlying software layers such as RTOS and middleware and recovers from them through system-level restarts that reinitialize the software (middleware, RTOS, and applications) from a read-only storage. Our approach is implementable using one commercial off-the-shelf (COTS) processing unit. To demonstrate the efficacy of our solution, we fully implement a controller for a 3 degree of freedom (3DOF) helicopter. We test the system by injecting various types of faults into the applications and RTOS and verify that the system remains safe.

Abdollahpouri, Himan, Burke, Robin, Mobasher, Bamshad.  2017.  Recommender Systems As Multistakeholder Environments. Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization. :347–348.

Recommender systems are typically evaluated on their ability to provide items that satisfy the needs and interests of the end user. However, in many real world applications, users are not the only stakeholders involved. There may be a variety of individuals or organizations that benefit in different ways from the delivery of recommendations. In this paper, we re-define the recommender system as a multistakeholder environment in which different stakeholders are served by delivering recommendations, and we suggest a utility-based approach to evaluating recommendations in such an environment that is capable of distinguishing among the distributions of utility delivered to different stakeholders.

Abdulqadder, I. H., Zou, D., Aziz, I. T., Yuan, B..  2017.  Modeling software defined security using multi-level security mechanism for SDN environment. 2017 IEEE 17th International Conference on Communication Technology (ICCT). :1342–1346.

Software Defined Networking (SDN) support several administrators for quicker access of resources due to its manageability, cost-effectiveness and adaptability. Even though SDN is beneficial it also exists with security based challenges due to many vulnerable threats. Participation of such threats increases their impact and risk level. In this paper a multi-level security mechanism is proposed over SDN architecture design. In each level the flow packet is analyzed using different metric and finally it reaches a secure controller for processing. Benign flow packets are differentiated from non-benign flow by means of the packet features. Initially routers verify user, secondly policies are verified by using dual-fuzzy logic design and thirdly controllers are authenticated using signature based authentication before assigning flow packets. This work aims to enhance entire security of developed SDN environment. SDN architecture is implemented in OMNeT++ simulation tool that supports OpenFlow switches and controllers. Finally experimental results show better performances in following performance metrics as throughput, time consumption and jitter.

Abera, Tigist, Asokan, N., Davi, Lucas, Ekberg, Jan-Erik, Nyman, Thomas, Paverd, Andrew, Sadeghi, Ahmad-Reza, Tsudik, Gene.  2016.  C-FLAT: Control-Flow Attestation for Embedded Systems Software. Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security. :743–754.

Remote attestation is a crucial security service particularly relevant to increasingly popular IoT (and other embedded) devices. It allows a trusted party (verifier) to learn the state of a remote, and potentially malware-infected, device (prover). Most existing approaches are static in nature and only check whether benign software is initially loaded on the prover. However, they are vulnerable to runtime attacks that hijack the application's control or data flow, e.g., via return-oriented programming or data-oriented exploits. As a concrete step towards more comprehensive runtime remote attestation, we present the design and implementation of Control-FLow ATtestation (C-FLAT) that enables remote attestation of an application's control-flow path, without requiring the source code. We describe a full prototype implementation of C-FLAT on Raspberry Pi using its ARM TrustZone hardware security extensions. We evaluate C-FLAT's performance using a real-world embedded (cyber-physical) application, and demonstrate its efficacy against control-flow hijacking attacks.

Abi-Antoun, Marwan, Khalaj, Ebrahim, Vanciu, Radu, Moghimi, Ahmad.  2016.  Abstract Runtime Structure for Reasoning About Security: Poster. Proceedings of the Symposium and Bootcamp on the Science of Security. :1–3.

We propose an interactive approach where analysts reason about the security of a system using an abstraction of its runtime structure, as opposed to looking at the code. They interactively refine a hierarchical object graph, set security properties on abstract objects or edges, query the graph, and investigate the results by studying highlighted objects or edges or tracing to the code. Behind the scenes, an inference analysis and an extraction analysis maintain the soundness of the graph with respect to the code.

Abo-alian, Alshaimaa, Badr, Nagwa L., Tolba, M. F..  2016.  Authentication As a Service for Cloud Computing. Proceedings of the International Conference on Internet of Things and Cloud Computing. :10:1–10:7.

Traditional authentication techniques such as static passwords are vulnerable to replay and guessing attacks. Recently, many studies have been conducted on keystroke dynamics as a promising behavioral biometrics for strengthening user authentication, however, current keystroke based solutions suffer from a numerous number of features with an insufficient number of samples which lead to a high verification error rate and high verification time. In this paper, a keystroke dynamics based authentication system is proposed for cloud environments that supports fixed and free text samples. The proposed system utilizes the ReliefF dimensionality reduction method, as a preprocessing step, to minimize the feature space dimensionality. The proposed system applies clustering to users' profile templates to reduce the verification time. The proposed system is applied to two different benchmark datasets. Experimental results prove the effectiveness and efficiency of the proposed system.

Abou-Zahra, Shadi, Brewer, Judy, Cooper, Michael.  2018.  Artificial Intelligence (AI) for Web Accessibility: Is Conformance Evaluation a Way Forward? Proceedings of the Internet of Accessible Things. :20:1–20:4.

The term "artificial intelligence" is a buzzword today and is heavily used to market products, services, research, conferences, and more. It is scientifically disputed which types of products and services do actually qualify as "artificial intelligence" versus simply advanced computer technologies mimicking aspects of natural intelligence. Yet it is undisputed that, despite often inflationary use of the term, there are mainstream products and services today that for decades were only thought to be science fiction. They range from industrial automation, to self-driving cars, robotics, and consumer electronics for smart homes, workspaces, education, and many more contexts. Several technological advances enable what is commonly referred to as "artificial intelligence". It includes connected computers and the Internet of Things (IoT), open and big data, low cost computing and storage, and many more. Yet regardless of the definition of the term artificial intelligence, technological advancements in this area provide immense potential, especially for people with disabilities. In this paper we explore some of these potential in the context of web accessibility. We review some existing products and services, and their support for web accessibility. We propose accessibility conformance evaluation as one potential way forward, to accelerate the uptake of artificial intelligence, to improve web accessibility.

Abrath, Bert, Coppens, Bart, Volckaert, Stijn, Wijnant, Joris, De Sutter, Bjorn.  2016.  Tightly-coupled Self-debugging Software Protection. Proceedings of the 6th Workshop on Software Security, Protection, and Reverse Engineering. :7:1–7:10.
Existing anti-debugging protections are relatively weak. In existing self-debugger approaches, a custom debugger is attached to the main application, of which the control flow is obfuscated by redirecting it through the debugger. The coupling between the debugger and the main application is then quite loose, and not that hard to break by an attacker. In the tightly-coupled self-debugging technique proposed in this paper, full code fragments are migrated from the application to the debugger, making it harder for the attacker to reverse-engineer the program and to deconstruct it into the original unprotected program to attach a debugger or to collect traces. We evaluate a prototype implementation on three complex, real-world Android use cases and present the results of tests conducted by professional penetration testers.
Abtioglu, E., Yeniçeri, R., Gövem, B., Göncü, E., Yalçin, M. E., Saldamli, G..  2017.  Partially Reconfigurable IP Protection System with Ring Oscillator Based Physically Unclonable Functions. 2017 New Generation of CAS (NGCAS). :65–68.
The size of counterfeiting activities is increasing day by day. These activities are encountered especially in electronics market. In this paper, a countermeasure against counterfeiting on intellectual properties (IP) on Field-Programmable Gate Arrays (FPGA) is proposed. FPGA vendors provide bitstream ciphering as an IP security solution such as battery-backed or non-volatile FPGAs. However, these solutions are secure as long as they can keep decryption key away from third parties. Key storage and key transfer over unsecure channels expose risks for these solutions. In this work, physical unclonable functions (PUFs) have been used for key generation. Generating a key from a circuit in the device solves key transfer problem. Proposed system goes through different phases when it operates. Therefore, partial reconfiguration feature of FPGAs is essential for feasibility of proposed system.
AbuAli, N. A., Taha, A. E. M..  2017.  A dynamic scalable scheme for managing mixed crowds. 2017 IEEE International Conference on Communications (ICC). :1–5.
Crowd management in urban settings has mostly relied on either classical, non-automated mechanisms or spontaneous notifications/alerts through social networks. Such management techniques are heavily marred by lack of comprehensive control, especially in terms of averting risks in a manner that ensures crowd safety and enables prompt emergency response. In this paper, we propose a Markov Decision Process Scheme MDP to realize a smart infrastructure that is directly aimed at crowd management. A key emphasis of the scheme is a robust and reliable scalability that provides sufficient flexibility to manage a mixed crowd (i.e., pedestrian, cyclers, manned vehicles and unmanned vehicles). The infrastructure also spans various population settings (e.g., roads, buildings, game arenas, etc.). To realize a reliable and scalable crowd management scheme, the classical MDP is decomposed into Local MDPs with smaller action-state spaces. Preliminarily results show that the MDP decomposition can reduce the system global cost and facilitate fast convergence to local near-optimal solution for each L-MDP.
Abubaker, N., Dervishi, L., Ayday, E..  2017.  Privacy-preserving fog computing paradigm. 2017 IEEE Conference on Communications and Network Security (CNS). :502–509.

As an extension of cloud computing, fog computing is proving itself more and more potentially useful nowadays. Fog computing is introduced to overcome the shortcomings of cloud computing paradigm in handling the massive amount of traffic caused by the enormous number of Internet of Things devices being increasingly connected to the Internet on daily basis. Despite its advantages, fog architecture introduces new security and privacy threats that need to be studied and solved as soon as possible. In this work, we explore two privacy issues posed by the fog computing architecture and we define privacy challenges according to them. The first challenge is related to the fog's design purposes of reducing the latency and improving the bandwidth, where the existing privacy-preserving methods violate these design purposed. The other challenge is related to the proximity of fog nodes to the end-users or IoT devices. We discuss the importance of addressing these challenges by putting them in the context of real-life scenarios. Finally, we propose a privacy-preserving fog computing paradigm that solves these challenges and we assess the security and efficiency of our solution.

Abuein, Q., Shatnawi, A., Al-Sheyab, H..  2017.  Trusted Recomendation System Based on Level of Trust(TRS\_LoT). 2017 International Conference on Engineering and Technology (ICET). :1–5.

There are vast amounts of information in our world. Accessing the most accurate information in a speedy way is becoming more difficult and complicated. A lot of relevant information gets ignored which leads to much duplication of work and effort. The focuses tend to provide rapid and intelligent retrieval systems. Information retrieval (IR) is the process of searching for information that is related to some topics of interest. Due to the massive search results, the user will normally have difficulty in identifying the relevant ones. To alleviate this problem, a recommendation system is used. A recommendation system is a sort of filtering information system, which predicts the relevance of retrieved information to the user's needs according to some criteria. Hence, it can provide the user with the results that best fit their needs. The services provided through the web normally provide massive information about any requested item or service. An efficient recommendation system is required to classify this information result. A recommendation system can be further improved if augmented with a level of trust information. That is, recommendations are ranked according to their level of trust. In our research, we produced a recommendation system combined with an efficient level of trust system to guarantee that the posts, comments and feedbacks from users are trusted. We customized the concept of LoT (Level of Trust) [1] since it can cover medical, shopping and learning through social media. The proposed system TRS\_LoT provides trusted recommendations to the users with a high percentage of accuracy. Whereas a 300 post with more than 5000 comments from ``Amazon'' was selected to be used as a dataset, the experiment has been conducted by using same dataset based on ``post rating''.

Abura'ed, Nour, Khan, Faisal Shah, Bhaskar, Harish.  2017.  Advances in the Quantum Theoretical Approach to Image Processing Applications. ACM Comput. Surv.. 49:75:1–75:49.
In this article, a detailed survey of the quantum approach to image processing is presented. Recently, it has been established that existing quantum algorithms are applicable to image processing tasks allowing quantum informational models of classical image processing. However, efforts continue in identifying the diversity of its applicability in various image processing domains. Here, in addition to reviewing some of the critical image processing applications that quantum mechanics have targeted, such as denoising, edge detection, image storage, retrieval, and compression, this study will also highlight the complexities in transitioning from the classical to the quantum domain. This article shall establish theoretical fundamentals, analyze performance and evaluation, draw key statistical evidence to support claims, and provide recommendations based on published literature mostly during the period from 2010 to 2015.