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Abhinav, P Y, Bhat, Avakash, Joseph, Christina Terese, Chandrasekaran, K.  2020.  Concurrency Analysis of Go and Java. 2020 5th International Conference on Computing, Communication and Security (ICCCS). :1—6.
There has been tremendous progress in the past few decades towards developing applications that receive data and send data concurrently. In such a day and age, there is a requirement for a language that can perform optimally in such environments. Currently, the two most popular languages in that respect are Go and Java. In this paper, we look to analyze the concurrency features of Go and Java through a complete programming language performance analysis, looking at their compile time, run time, binary sizes and the language's unique concurrency features. This is done by experimenting with the two languages using the matrix multiplication and PageRank algorithms. To the extent of our knowledge, this is the first work which used PageRank algorithm to analyse concurrency. Considering the results of this paper, application developers and researchers can hypothesize on an appropriate language to use for their concurrent programming activity.Results of this paper show that Go performs better for fewer number of computation but is soon taken over by Java as the number of computations drastically increase. This trend is shown to be the opposite when thread creation and management is considered where Java performs better with fewer computation but Go does better later on. Regarding concurrency features both Java with its Executor Service library and Go had their own advantages that made them better for specific applications.
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.

Abidin, Aysajan, Argones Rúa, Enrique, Peeters, Roel.  2017.  Uncoupling Biometrics from Templates for Secure and Privacy-Preserving Authentication. Proceedings of the 22Nd ACM on Symposium on Access Control Models and Technologies. :21–29.

Biometrics are widely used for authentication in several domains, services and applications. However, only very few systems succeed in effectively combining highly secure user authentication with an adequate privacy protection of the biometric templates, due to the difficulty associated with jointly providing good authentication performance, unlinkability and irreversibility to biometric templates. This thwarts the use of biometrics in remote authentication scenarios, despite the advantages that this kind of architectures provides. We propose a user-specific approach for decoupling the biometrics from their binary representation before using biometric protection schemes based on fuzzy extractors. This allows for more reliable, flexible, irreversible and unlinkable protected biometric templates. With the proposed biometrics decoupling procedures, biometric metadata, that does not allow to recover the original biometric template, is generated. However, different biometric metadata that are generated starting from the same biometric template remain statistically linkable, therefore we propose to additionally protect these using a second authentication factor (e.g., knowledge or possession based). We demonstrate the potential of this approach within a two-factor authentication protocol for remote biometric authentication in mobile scenarios.

Abie, Habtamu.  2019.  Cognitive Cybersecurity for CPS-IoT Enabled Healthcare Ecosystems. 2019 13th International Symposium on Medical Information and Communication Technology (ISMICT). :1–6.

Cyber Physical Systems (CPS)-Internet of Things (IoT) enabled healthcare services and infrastructures improve human life, but are vulnerable to a variety of emerging cyber-attacks. Cybersecurity specialists are finding it hard to keep pace of the increasingly sophisticated attack methods. There is a critical need for innovative cognitive cybersecurity for CPS-IoT enabled healthcare ecosystem. This paper presents a cognitive cybersecurity framework for simulating the human cognitive behaviour to anticipate and respond to new and emerging cybersecurity and privacy threats to CPS-IoT and critical infrastructure systems. It includes the conceptualisation and description of a layered architecture which combines Artificial Intelligence, cognitive methods and innovative security mechanisms.

Abir, Md. Towsif, Rahman, Lamiya, Miftah, Samit Shahnawaz, Sarker, Sudipta, Al Imran, Md. Ibrahim, Shafiqul Islam, Md..  2019.  Image Encryption and Decryption using Enigma Algorithm. 2019 IEEE International Conference on Electrical, Computer and Communication Technologies (ICECCT). :1—5.

The main objective of this paper is to present a more secured and computationally efficient procedure of encrypting and decrypting images using the enigma algorithm in comparison to the existing methods. Available literature on image encryptions and descriptions are not highly secured in every case.To achieve more secured image processing for highly advanced technologies, a proposed algorithm can be the process used in enigma machine for image encryption and decryption. Enigma machine is piece of spook hardware that was used frequently during the World War II by the Germans. This paper describes the detailed algorithm along with proper demonstration of several essential components present in an enigma machine that is required for image security. Each pixel in a colorful picture can be represented by RGB (Red, Green, Blue) value. The range of RGB values is 0 to 255 that states the red, green and blue intensity of a particular picture.These RGB values are accessed one by one and changed into another by various steps and hence it is not possible to track the original RGB value. In order to retrieve the original image, the receiver needs to know the setting of the enigma. To compare the decrypted image with the original one,these two images are subtracted and their results are also discussed in this paper.

Abishek Gupta, University of Illinois at Urbana-Champaign, Galina Schwartz, University of California, Berkeley, Cedric Langbort, University of Illinois at Urbana-Champaign, S. Shankar Sastry, University of California, Berkeley, Tamer Başar, University of Illinois at Urbana-Champaign.  2014.  A Three-stage Colonel Blotto Game with Applications to Cyberphysical Security. American Control Conference .

We consider a three-step three-player complete information Colonel Blotto game in this paper, in which the first two players fight against a common adversary. Each player is endowed with a certain amount of resources at the beginning of the game, and the number of battlefields on which a player and the adversary fights is specified. The first two players are allowed to form a coalition if it improves their payoffs. In the first stage, the first two players may add battlefields and incur costs. In the second stage, the first two players may transfer resources among each other. The adversary observes this transfer, and decides on the allocation of its resources to the two battles with the players. At the third step, the adversary and the other two players fight on the updated number of battlefields and receive payoffs. We characterize the subgame-perfect Nash equilibrium (SPNE) of the game in various parameter regions. In particular, we show that there are certain parameter regions in which if the players act according to the SPNE strategies, then (i) one of the first two players add battlefields and transfer resources to the other player (a coalition is formed), (ii) there is no addition of battlefields and no transfer of resources (no coalition is formed). We discuss the implications of the results on resource allocation for securing cyberphysical systems.

Abishek Gupta, University of Illinois at Urbana-Champaign, Tamer Başar, University of Illinois at Urbana-Champaign, Galina Schwartz, University of California, Berkeley.  2014.  A Three-Stage Colonel Blotto Game: When to Provide More Information to an Adversary. 5th International Conference on Decision and Game Theory for Security (GameSec 2014).

In this paper, we formulate a three-player three-stage Colonel Blotto game, in which two players fight against a common adversary. We assume that the game is one of complete information, that is, the players have complete and consistent information on the underlying model of the game; further, each player observes the actions taken by all players up to the previous stage.  The setting  under  consideration is similar  to the one considered in our recent  work [1], but with a different  information structure  during  the  second  stage  of the  game;  this  leads  to  a  significantly different  solution.

In the first stage, players can add additional battlefields. In the second stage, the players (except the adversary) are allowed to transfer resources among  each  other  if it  improves their  expected payoffs, and simultaneously, the adversary decides  on the amount  of resource it allocates  to the battle with each player subject to its resource constraint. At the third stage, the players and the adversary fight against each other with updated resource levels and battlefields. We compute the subgame-perfect Nash equilibrium for this game. Further, we show that when playing according to the equilibrium, there are parameter regions  in which (i) there  is a net  positive transfer, (ii)  there  is absolutely no transfer, (iii) the  adversary fights  with  only  one player, and  (iv)  adding  battlefields is beneficial to a player. In doing so, we also exhibit a counter-intuitive property of Nash equilibrium in games: extra information to a player in the game does not necessarily lead to a better performance for that player.  The result finds application in resource allocation problems for securing cyber-physical systems.

Ablaev, Farid, Andrianov, Sergey, Soloviev, Aleksey.  2019.  Quantum Electronic Generator of Random Numbers for Information Security in Automatic Control Systems. 2019 International Russian Automation Conference (RusAutoCon). :1–5.

The problems of random numbers application to the information security of data, communication lines, computer units and automated driving systems are considered. The possibilities for making up quantum generators of random numbers and existing solutions for acquiring of sufficiently random sequences are analyzed. The authors found out the method for the creation of quantum generators on the basis of semiconductor electronic components. The electron-quantum generator based on electrons tunneling is experimentally demonstrated. It is shown that it is able to create random sequences of high security level and satisfying known NIST statistical tests (P-Value\textbackslashtextgreater0.9). The generator created can be used for formation of both closed and open cryptographic keys in computer systems and other platforms and has great potential for realization of random walks and probabilistic computing on the basis of neural nets and other IT problems.

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.

Aborisade, O., Anwar, M..  2018.  Classification for Authorship of Tweets by Comparing Logistic Regression and Naive Bayes Classifiers. 2018 IEEE International Conference on Information Reuse and Integration (IRI). :269–276.

At a time when all it takes to open a Twitter account is a mobile phone, the act of authenticating information encountered on social media becomes very complex, especially when we lack measures to verify digital identities in the first place. Because the platform supports anonymity, fake news generated by dubious sources have been observed to travel much faster and farther than real news. Hence, we need valid measures to identify authors of misinformation to avert these consequences. Researchers propose different authorship attribution techniques to approach this kind of problem. However, because tweets are made up of only 280 characters, finding a suitable authorship attribution technique is a challenge. This research aims to classify authors of tweets by comparing machine learning methods like logistic regression and naive Bayes. The processes of this application are fetching of tweets, pre-processing, feature extraction, and developing a machine learning model for classification. This paper illustrates the text classification for authorship process using machine learning techniques. In total, there were 46,895 tweets used as both training and testing data, and unique features specific to Twitter were extracted. Several steps were done in the pre-processing phase, including removal of short texts, removal of stop-words and punctuations, tokenizing and stemming of texts as well. This approach transforms the pre-processed data into a set of feature vector in Python. Logistic regression and naive Bayes algorithms were applied to the set of feature vectors for the training and testing of the classifier. The logistic regression based classifier gave the highest accuracy of 91.1% compared to the naive Bayes classifier with 89.8%.

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.

Abraham, A., Kumar, M. B. Santosh.  2020.  A study on using private-permissioned blockchain for securely sharing farmers data. 2020 Advanced Computing and Communication Technologies for High Performance Applications (ACCTHPA). :103—106.
In agriculture, farmers are the most important entity. For supporting farmers in increasing productivity and efficiency, the government offers subsidies, loans, insurances, and so on. This paper explores the usage of Blockchain technology for securing farmer's data in the Indian scenario. The farmer needs to register through the multiple official registration systems for availing different schemes and information provided by the country. The personnel and crop-based details of each farmer are collected at the time of registration. The filing also helps in providing better services to farmers like connecting farmers and traders to ensure a fair price for quality crops, advice to farmers of agricultural practices and location. In this paper, a blockchain-based farmer's data securing system is proposed to provide data provenance and transparency of the information entered in the system. While registering, the data is collected, and it is verified. A single verified record of farmers accessed by various government agriculture departments were designed using the Hyperledger fabric framework.
Abraham, Jacob A..  2019.  Resiliency Demands on Next Generation Critical Embedded Systems. 2019 IEEE 25th International Symposium on On-Line Testing and Robust System Design (IOLTS). :135–138.

Emerging intelligent systems have stringent constraints including cost and power consumption. When they are used in critical applications, resiliency becomes another key requirement. Much research into techniques for fault tolerance and dependability has been successfully applied to highly critical systems, such as those used in space, where cost is not an overriding constraint. Further, most resiliency techniques were focused on dealing with failures in the hardware and bugs in the software. The next generation of systems used in critical applications will also have to be tolerant to test escapes after manufacturing, soft errors and transients in the electronics, hardware bugs, hardware and software Trojans and viruses, as well as intrusions and other security attacks during operation. This paper will assess the impact of these threats on the results produced by a critical system, and proposed solutions to each of them. It is argued that run-time checks at the application-level are necessary to deal with errors in the results.

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.
Abratkiewicz, K., Gromek, D., Samczynski, P..  2019.  Chirp Rate Estimation and micro-Doppler Signatures for Pedestrian Security Radar Systems. 2019 Signal Processing Symposium (SPSympo). :212—215.

A new approach to micro-Doppler signal analysis is presented in this article. Novel chirp rate estimators in the time-frequency domain were used for this purpose, which provided the chirp rate of micro-Doppler signatures, allowing the classification of objects in the urban environment. As an example verifying the method, a signal from a high-resolution radar with a linear frequency modulated continuous wave (FMCW) recording an echo reflected from a pedestrian was used to validate the proposed algorithms for chirp rate estimation. The obtained results are plotted on saturated accelerograms, giving an additional parameter dedicated for target classification in security systems utilizing radar sensors for target detection.

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''.

Abuella, Hisham, Ekin, Sabit.  2019.  A New Paradigm for Non-contact Vitals Monitoring using Visible Light Sensing. 2019 16th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON). :1–2.
Typical techniques for tracking vital signs require body contact and most of these techniques are intrusive in nature. Body-contact methods might irritate the patient's skin and he/she might feel uncomfortable while sensors are touching his/her body. In this study, we present a new wireless (non-contact) method for monitoring human vital signs (breathing and heartbeat). We have demonstrated for the first time1 that vitals signs can be measured wirelessly through visible light signal reflected from a human subject, also referred to as visible light sensing (VLS). In this method, the breathing and heartbeat rates are measured without any body-contact device, using only a simple photodetector and a light source (e.g., LED). The light signal reflected from human subject is modulated by the physical motions during breathing and heartbeats. Signal processing tools such as filtering and Fourier transform are used to convert these small variations in the received light signal power to vitals data.We implemented the VLS-based non-contact vital signs monitoring system by using an off-the-shelf light source, a photodetector and a signal acquisition and processing unit. We observed more than 94% of accuracy as compared to a contact-based FDA (The Food and Drug Administration) approved devices. Additional evaluations are planned to assess the performance of the developed vitals monitoring system, e.g., different subjects, environments, etc. Non-contact vitals monitoring system can be used in various areas and scenarios such as medical facilities, residential homes, security and human-computer-interaction (HCI) applications.
Abur, Maria M., Junaidu, Sahalu B., Obiniyi, Afolayan A., Abdullahi, Saleh E..  2019.  Privacy Token Technique for Protecting User’s Attributes in a Federated Identity Management System for the Cloud Environment. 2019 2nd International Conference of the IEEE Nigeria Computer Chapter (NigeriaComputConf). :1–10.
Once an individual employs the use of the Internet for accessing information; carrying out transactions and sharing of data on the Cloud, they are connected to diverse computers on the network. As such, security of such transmitted data is most threatened and then potentially creating privacy risks of users on the federated identity management system in the Cloud. Usually, User's attributes or Personal Identifiable Information (PII) are needed to access Services on the Cloud from different Service Providers (SPs). Sometime these SPs may by themselves violate user's privacy by the reuse of user's attributes offered them for the release of services to the users without their consent and then carrying out activities that may appear malicious and then causing damage to the users. Similarly, it should be noted that sensitive user's attributes (e.g. first name, email, address and the likes) are received in their original form by needed SPs in plaintext. As a result of these problems, user's privacy is being violated. Since these SPs may reuse them or connive with other SPs to expose a user's identity in the cloud environment. This research is motivated to provide a protective and novel approach that shall no longer release original user's attributes to SPs but pseudonyms that shall prevent the SPs from violating user's privacy through connivance to expose the user's identity or other means. The paper introduces a conceptual framework for the proposed user's attributes privacy protection in a federated identity management system for the cloud. On the proposed system, the use of pseudonymous technique also called Privacy Token (PT) is employed. The pseudonymous technique ensures users' original attributes values are not sent directly to the SP but auto generated pseudo attributes values. The PT is composed of: Pseudo Attribute values, Timestamp and SPİD. These composition of the PT makes it difficult for the User's PII to be revealed and further preventing the SPs from being able to keep them or reuse them in the future without the user's consent for any purpose. Another important feature of the PT is its ability to forestall collusion among several collaborating service providers. This is due to the fact that each SP receives pseudo values that have no direct link to the identity of the user. The prototype was implemented with Java programming language and its performance tested on CloudAnalyst simulation.
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.
Abusitta, Adel, Bellaiche, Martine, Dagenais, Michel.  2018.  A trust-based game theoretical model for cooperative intrusion detection in multi-cloud environments. 2018 21st Conference on Innovation in Clouds, Internet and Networks and Workshops (ICIN). :1—8.

Cloud systems are becoming more complex and vulnerable to attacks. Cyber attacks are also becoming more sophisticated and harder to detect. Therefore, it is increasingly difficult for a single cloud-based intrusion detection system (IDS) to detect all attacks, because of limited and incomplete knowledge about attacks. The recent researches in cyber-security have shown that a co-operation among IDSs can bring higher detection accuracy in such complex computer systems. Through collaboration, a cloud-based IDS can consult other IDSs about suspicious intrusions and increase the decision accuracy. The problem of existing cooperative IDS approaches is that they overlook having untrusted (malicious or not) IDSs that may negatively effect the decision about suspicious intrusions in the cloud. Moreover, they rely on a centralized architecture in which a central agent regulates the cooperation, which contradicts the distributed nature of the cloud. In this paper, we propose a framework that enables IDSs to distributively form trustworthy IDSs communities. We devise a novel decentralized algorithm, based on coalitional game theory, that allows a set of cloud-based IDSs to cooperatively set up their coalition in such a way to make their individual detection accuracy increase, even in the presence of untrusted IDSs.

Abusnaina, A., Khormali, A., Alasmary, H., Park, J., Anwar, A., Mohaisen, A..  2019.  Adversarial Learning Attacks on Graph-based IoT Malware Detection Systems. 2019 IEEE 39th International Conference on Distributed Computing Systems (ICDCS). :1296—1305.

IoT malware detection using control flow graph (CFG)-based features and deep learning networks are widely explored. The main goal of this study is to investigate the robustness of such models against adversarial learning. We designed two approaches to craft adversarial IoT software: off-the-shelf methods and Graph Embedding and Augmentation (GEA) method. In the off-the-shelf adversarial learning attack methods, we examine eight different adversarial learning methods to force the model to misclassification. The GEA approach aims to preserve the functionality and practicality of the generated adversarial sample through a careful embedding of a benign sample to a malicious one. Intensive experiments are conducted to evaluate the performance of the proposed method, showing that off-the-shelf adversarial attack methods are able to achieve a misclassification rate of 100%. In addition, we observed that the GEA approach is able to misclassify all IoT malware samples as benign. The findings of this work highlight the essential need for more robust detection tools against adversarial learning, including features that are not easy to manipulate, unlike CFG-based features. The implications of the study are quite broad, since the approach challenged in this work is widely used for other applications using graphs.

Abusukhon, A., AlZu’bi, S..  2020.  New Direction of Cryptography: A Review on Text-to-Image Encryption Algorithms Based on RGB Color Value. 2020 Seventh International Conference on Software Defined Systems (SDS). :235–239.
Data encryption techniques are important for answering the question: How secure is the Internet for sending sensitive data. Keeping data secure while they are sent through the global network is a difficult task. This is because many hackers are fishing these data in order to get some benefits. The researchers have developed various types of encryption algorithms to protect data from attackers. These algorithms are mainly classified into two categories namely symmetric and asymmetric encryption algorithms. This survey sheds light on the recent work carried out on encrypting a text into an image based on the RGB color value and held a comparison between them based on various factors evolved from the literature.