jehanweerasuriya/uni-ai-dataset huggingface dataset:
Enabling security in cloud storage SLAs with CloudProof
Authors: Raluca Ada Popa, Jacob R. Lorch, Dávid Molnár, Helen J. Wang, Zhuang Li
Published in:  (2011-06-15)

Several cloud storage systems exist today, but none of them provide security guarantees in their Service Level Agreements (SLAs). This lack of security support has been a major hurdle for the adoption of cloud services, especially for enterprises and cautious consumers. To fix this issue, we present CloudProof, a secure storage system specifically designed for the cloud. In CloudProof, customers can not only detect violations of integrity, write-serializability, and freshness, they can also prove the occurrence of these violations to a third party. This proof-based system is critical to enabling security guarantees in SLAs, wherein clients pay for a desired level of security and are assured they will receive a certain compensation in the event of cloud misbehavior. Furthermore, since CloudProof aims to scale to the size of large enterprises, we delegate as much work as possible to the cloud and use cryptographic tools to allow customers to detect and prove cloud misbehavior. Our evaluation of CloudProof indicates that its security mechanisms have a reasonable cost: they incur a latency overhead of only ∼15 % on reads and writes, and reduce throughput by around 10%. We also achieve highly scalable access control, with membership management (addition and removal of members ’ permissions) for a large proprietary software with more than 5000 developers taking only a few seconds per month. 1
Cyber Security Threats Detection in Internet of Things Using Deep Learning Approach
Authors: Farhan Ullah, Hamad Naeem, Sohail Jabbar, Shehzad Khalid, Muhammad Ahsan Latif, Fadi Al‐Turjman, Leonardo Mostarda
Published in: IEEE Access (2019-01-01)

The IoT (Internet of Things) connect systems, applications, data storage, and services that may be a new gateway for cyber-attacks as they continuously offer services in the organization. Currently, software piracy and malware attacks are high risks to compromise the security of IoT. These threats may steal important information that causes economic and reputational damages. In this paper, we have proposed a combined deep learning approach to detect the pirated software and malware-infected files across the IoT network. The TensorFlow deep neural network is proposed to identify pirated software using source code plagiarism. The tokenization and weighting feature methods are used to filter the noisy data and further, to zoom the importance of each token in terms of source code plagiarism. Then, the deep learning approach is used to detect source code plagiarism. The dataset is collected from Google Code Jam (GCJ) to investigate software piracy. Apart from this, the deep convolutional neural network is used to detect malicious infections in IoT network through color image visualization. The malware samples are obtained from Maling dataset for experimentation. The experimental results indicate that the classification performance of the proposed solution to measure the cybersecurity threats in IoT are better than the state of the art methods.
Securing the Internet of Things in the Age of Machine Learning and Software-Defined Networking
Authors: Francesco Restuccia, Salvatore D’Oro, Tommaso Melodia
Published in: IEEE Internet of Things Journal (2018-06-11)

The Internet of Things (IoT) realizes a vision where billions of interconnected devices are deployed just about everywhere, from inside our bodies to the most remote areas of the globe. As the IoT will soon pervade every aspect of our lives and will be accessible from anywhere, addressing critical IoT security threats is now more important than ever. Traditional approaches where security is applied as an afterthought and as a “patch” against known attacks are insufficient. Indeed, next-generation IoT challenges will require a new secure-by-design vision, where threats are addressed proactively and IoT devices learn to dynamically adapt to different threats. To this end, machine learning (ML) and software-defined networking (SDN) will be key to provide both reconfigurability and intelligence to the IoT devices. In this paper, we first provide a taxonomy and survey the state of the art in IoT security research, and offer a roadmap of concrete research challenges related to the application of ML and SDN to address existing and next-generation IoT security threats.
A technical review of wireless security for the internet of things: Software defined radio perspective
Authors: José de Jesús Rugeles Uribe, Edward Guillén, Leonardo S. Cardoso
Published in: Journal of King Saud University - Computer and Information Sciences (2021-04-24)

The increase of cyberattacks by using the Internet of Things devices has exposed multiple vulnerabilities not only on devices but also on IoT infrastructures. Now, small devices can affect different networks and their services. This paper presents a review of the vulnerabilities on wireless technologies that gives connectivity to IoT, and the experiences using Software Defined Radio SDR for implementing wireless attacks to IoT technologies are assessed. A systematic literature review was conducted. The types of vulnerabilities and attacks that can affect the wireless technologies that stand the IoT ecosystem and SDR platforms were compared, and recent methods to overcome these attacks were identified. On the IoT reference model, the perception layer was identified as the most vulnerable. Most attacks at this level occur due to hardware limitations, physical device exposure, and heterogeneity of technologies. Future cybersecurity systems based on SDR technologies have notable advantages due to their flexibility and adaptability to new communication technologies and their potential to develop advanced tools. However, the IoT’s cybersecurity challenges are so complex that merging SDR hardware with cognitive and intelligent techniques is highly advisable. Some of these techniques could include deep learning to adapt mitigation systems to rapid technological changes.
Online Neighborhood Watch: The Impact of Social Network Advice on Software Security Decisions
Authors: Bruna Freitas, Ashraf Matrawy, Robert Biddle
Published in: Canadian Journal of Electrical and Computer Engineering (2016-01-01)

Malicious software (malware) is one significant threat to Internet security. Malware is designed to harm a computer or network, and can be installed on one's machine without their consent. Attacks are often done by deceiving people into downloading malicious software that is posing as useful software. We speculated that if people had advice from a trusted source, they would be inclined to use the advice, reducing their chances of putting their computers at security risk. We designed and developed a system, Online Neighborhood Watch (ONWatch), to provide social network advice to users considering downloading software, sometimes offering alternatives when software was not trustworthy. We ran an empirical study to compare the advice coming from a trusted person to the advice coming from other more general social networks. We compared five different sources of advice in total. We did not find much evidence that the advice had a different effect based on the advisor, but the study confirmed our hypothesis that presenting alternative software will improve security.
The application of software and safety engineering techniques to security protocol development
Authors: Nathalie Louise Foster
Published in:  (2003-01-01)

Security protocols are series of steps designed to achieve a particular aim, whilst also providing security functions. However, despite extensive research, protocols are still being designed which are susceptible to common flaws and attacks. Much of the research in this area has focused on protocol verification and, to a lesser extent, protocol design. Many comparisons have been made between software and safety and security engineering. This thesis builds on these comparisons in order to identify an approach to protocol development which reduces the likelihood of the occurrence of common flaws and attacks. This thesis proposes a process model for protocol development and justifies why such a model should be used to structure protocol development. One area that has often been overlooked in protocol research is that of the requirements of the security protocol. In this thesis, this area is investigated and, as a result, two techniques for the analysis and elicitation of security protocol requirements have been developed. The first technique is the Vulnerability Identification and Analysis (VIA) method. This is based on the HAZOP technique, which is successfully used in safety engineering, as well as a wide variety of other industries. The VIA method provides a structured approach to the deviation analysis of security protocol requirements, as well as the elicitation of further requirements. The second technique, Requirements Analysis and Elicitation (RAE) trees, extends the tree based analysis techniques which have been developed for the security field and draws on ideas from the safety analysis technique Fault Tree Analysis. The RAE trees are used to determine the causes of, and identify requirements to address, protocol vulnerabilities. Acknowledgements 16 Declaration 1...
Fuzzing for Software Security Testing and Quality Assurance, Second Edition
Authors: Ari Takanen, Jared D. DeMott, Charles L. Miller, Atte Kettunen
Published in:  (2018-01-01)

This newly revised and expanded second edition of the popular Artech House title, Fuzzing for Software Security Testing and Quality Assurance, provides practical and professional guidance on how and why to integrate fuzzing into the software development lifecycle. This edition introduces fuzzing as a process, goes through commercial tools, and explains what the customer requirements are for fuzzing. The advancement of evolutionary fuzzing tools, including American Fuzzy Lop (AFL) and the emerging full fuzz test automation systems are explored in this edition. Traditional software programmers and testers will learn how to make fuzzing a standard practice that integrates seamlessly with all development activities. It surveys all popular commercial fuzzing tools and explains how to select the right one for software development projects. This book is a powerful new tool to build secure, high-quality software taking a weapon from the malicious hacker’s arsenal. This practical resource helps engineers find and patch flaws in software before harmful viruses, worms, and Trojans can use these vulnerabilities to rampage systems. The book shows how to make fuzzing a standard practice that integrates seamlessly with all development activities.
Security Enhanced (SE) Android: Bringing Flexible MAC to Android.
Authors: Stephen Smalley, Robert Craig
Published in:  (2013-01-01)

The Android software stack for mobile devices defines and enforces its own security model for apps through its application-layer permissions model. However, at its foundation, Android relies upon the Linux kernel to protect the system from malicious or flawed apps and to isolate apps from one another. At present, Android leverages Linux discretionary access control (DAC) to enforce these guarantees, despite the known shortcomings of DAC. In this paper, we motivate and describe our work to bring flexible mandatory access control (MAC) to Android by enabling the effective use of Security Enhanced Linux (SELinux) for kernel-level MAC and by developing a set of middleware MAC extensions to the Android permissions model. We then demonstrate the benefits of our security enhancements for Android through a detailed analysis of how they mitigate a number of previously published exploits and vulnerabilities for Android. Finally, we evaluate the overheads imposed by our security enhancements. 1.
The Roadmap to 6G Security and Privacy
Authors: Pawani Porambage, Gürkan Gür, Diana Pamela Moya Osorio, Madhusanka Liyanage, Andrei Gurtov, Mika Ylianttila
Published in: IEEE Open Journal of the Communications Society (2021-01-01)

Although the fifth generation (5G) wireless networks are yet to be fully investigated, the visionaries of the 6th generation (6G) echo systems have already come into the discussion. Therefore, in order to consolidate and solidify the security and privacy in 6G networks, we survey how security may impact the envisioned 6G wireless systems, possible challenges with different 6G technologies, and the potential solutions. We provide our vision on 6G security and security key performance indicators (KPIs) with the tentative threat landscape based on the foreseen 6G network architecture. Moreover, we discuss the security and privacy challenges that may encounter with the available 6G requirements and potential 6G applications. We also give the reader some insights into the standardization efforts and research-level projects relevant to 6G security. In particular, we discuss the security considerations with 6G enabling technologies such as distributed ledger technology (DLT), physical layer security, distributed AI/ML, visible light communication (VLC), THz, and quantum computing. All in all, this work intends to provide enlightening guidance for the subsequent research of 6G security and privacy at this initial phase of vision towards reality.
Communication security for smart grid distribution networks
Authors: Elias Bou‐Harb, Claude Fachkha, Makan Pourzandi, Mourad Debbabi, Chadi Assi
Published in: IEEE Communications Magazine (2013-01-01)

The operation and control of the next generation electrical grids will depend on a complex network of computers, software, and communication technologies. Being compromised by a malicious adversary would cause significant damage, including extended power outages and destruction of electrical equipment. Moreover, the implementation of the smart grid will include the deployment of many new enabling technologies such as advanced sensors and metering, and the integration of distributed generation resources. Such technologies and various others will require the addition and utilization of multiple communication mechanisms and infrastructures that may suffer from serious cyber vulnerabilities. These need to be addressed in order to increase the security and thus the greatest adoption and success of the smart grid. In this article, we focus on the communication security aspect, which deals with the distribution component of the smart grid. Consequently, we target the network security of the advanced metering infrastructure coupled with the data communication toward the transmission infrastructure. We discuss the security and feasibility aspects of possible communication mechanisms that could be adopted on that subpart of the grid. By accomplishing this, the correlated vulnerabilities in these systems could be remediated, and associated risks may be mitigated for the purpose of enhancing the cyber security of the future electric grid.
NOTATIONS FOR FACILITATING SOFTWARE SECURITY DESIGN
Authors: Muhammad Nadeem, Adul Hussain Shah Bukhari
Published in: Journal of Applied and Emerging Sciences (2011-01-01)

The conventional software designing tools do not address the software security design, the security considerations are taken care of independently and there is no de facto unified mechanism to design software’s functional requirements along with the security requirements, it allows the applications more vulnerable to the security threats, this is especially true clientserver / web based systems. In this research designing notations are being proposed that can be integrated with the existing designing tools to address software security design. The notations have less abstraction order to design security requirements more clearly and effectively. Security is not a feature that can be added to software or bolted on after other software features are codified, nor can it be patched in after attacks have occurred the field. Instead, security must be built from the very beginning (requirements specification) and included every subsequent System Development Life Cycle phase.
Basic concepts and taxonomy of dependable and secure computing
Authors: A. Avižienis, J.-C. Laprie, Brian Randell, Carl E. Landwehr
Published in: IEEE Transactions on Dependable and Secure Computing (2004-01-01)

This paper gives the main definitions relating to dependability, a generic concept including a special case of such attributes as reliability, availability, safety, integrity, maintainability, etc. Security brings in concerns for confidentiality, in addition to availability and integrity. Basic definitions are given first. They are then commented upon, and supplemented by additional definitions, which address the threats to dependability and security (faults, errors, failures), their attributes, and the means for their achievement (fault prevention, fault tolerance, fault removal, fault forecasting). The aim is to explicate a set of general concepts, of relevance across a wide range of situations and, therefore, helping communication and cooperation among a number of scientific and technical communities, including ones that are concentrating on particular types of system, of system failures, or of causes of system failures.
The (In)Security of Virtualization in Software Defined Networks
Authors: Talal Alharbi, Marius Portmann
Published in: IEEE Access (2019-01-01)

Software Defined Networking (SDN) is a new networking paradigm with the promise to increase simplicity and efficiency in network management through the separation of control functions from the forwarding functions. In SDN, the control functions are softwarized and logically placed in a centralized entity, i.e. the SDN controller. Network virtualization is one of the key features enabled and facilitated by the SDN, and it allows multiple virtual networks and the SDN controllers to share the same physical network infrastructure. This paper discusses the security of virtualization in the SDN, and it highlights and demonstrates critical vulnerabilities of key network hypervisors used in the SDN. In particular, the paper demonstrates how the isolation of different virtual networks can be broken, and enabling different types of attacks. Finally, the paper discusses the potential impact of these vulnerabilities and points to mitigation approaches.
DEPENDABILITY ATTRIBUTES FOR INCREASED SECURITY IN COMPONENT-BASED SOFTWARE DEVELOPMENT
Authors: Hasan Kahtan
Published in: Journal of Computer Science (2014-07-01)

Existing software applications become increasingly distributed as their continuity and lifetimes are lengthened; consequently, the users' dependence on these applications is increased. The security of these applications has become a primary concern in their design, construction and evolution. Thus, these applications give rise to major concerns on the capability of the current development approach to develop secure systems. Component-Based Software Development (CBSD) is a software engineering approach. CBSD has been successfully applied in many domains. However, the CBSD capability to develop secure software applications is lacking to date. This study is an extension of the previous study on the challenges of the security features in CBSD models. Therefore, this study proposes a solution to the lack of security in CBSD models by highlighting the attributes that must be embedded into the CBSD process. A thorough analysis of existing studies is conducted to investigate the related software security attributes. The outcome analysis is beneficial for industries, such as software development companies, as well as for academic institutions. The analysis also serves as a baseline reference for companies that develop component-based software.
Edge-IIoTset: A New Comprehensive Realistic Cyber Security Dataset of IoT and IIoT Applications for Centralized and Federated Learning
Authors: Mohamed Amine Ferrag, Othmane Friha, Djallel Hamouda, Λέανδρος Μαγλαράς, Helge Janicke
Published in: IEEE Access (2022-01-01)

In this paper, we propose a new comprehensive realistic cyber security dataset of IoT and IIoT applications, called Edge-IIoTset, which can be used by machine learning-based intrusion detection systems in two different modes, namely, centralized and federated learning. Specifically, the dataset has been generated using a purpose-built IoT/IIoT testbed with a large representative set of devices, sensors, protocols and cloud/edge configurations. The IoT data are generated from various IoT devices (more than 10 types) such as Low-cost digital sensors for sensing temperature and humidity, Ultrasonic sensor, Water level detection sensor, pH Sensor Meter, Soil Moisture sensor, Heart Rate Sensor, Flame Sensor, etc.). Furthermore, we identify and analyze fourteen attacks related to IoT and IIoT connectivity protocols, which are categorized into five threats, including, DoS/DDoS attacks, Information gathering, Man in the middle attacks, Injection attacks, and Malware attacks. In addition, we extract features obtained from different sources, including alerts, system resources, logs, network traffic, and propose new 61 features with high correlations from 1176 found features. After processing and analyzing the proposed realistic cyber security dataset, we provide a primary exploratory data analysis and evaluate the performance of machine learning approaches (i.e., traditional machine learning as well as deep learning) in both centralized and federated learning modes. The Edge-IIoTset dataset can be publicly accessed fromhttp://ieee-dataport.org/8939.
SSDS: A Smart Software-Defined Security Mechanism for Vehicle-to-Grid Using Transfer Learning
Authors: Shen Wang, Jun Wu, Shanghua Zhang, Kuan Wang
Published in: IEEE Access (2018-01-01)

Nowadays, vehicle-to-grid (V2G) is a very important component for smart cities, which provide a novel energy storage and scheduling approach. However, security threats currently disturb the normal operations of V2G. There are two challenges for the security of V2G. On one hand, existing security schemes for V2G just consider the static security strategy, which cannot deal well with the problem of high dynamics and advanced persistent threat in V2G. On the other hand, existing V2G lacks a unified information modeling approach, which results in the difficulties of security and communications. To address above challenges, this paper proposes a smart software-defined security mechanism, SSDS, for V2G using transfer learning and IEC 61850 standards. First, as next generation networking technology, software-defined networking (SDN) is adopted to establish a dynamic security protection architecture for V2G, which can provide dynamic security strategy configuration capability. Second, IEC 61850 is introduced to model SSDS, including SDN controller and OpenFlow switch. Third, transfer learning-based security strategy constructing scheme is proposed for the security strategy updating dynamically. Simulation results in terms of network performance and security strategy constructing verify the efficiency as well as feasibility of the proposed security mechanism.
A review of cyber security risk assessment methods for SCADA systems
Authors: Yulia Cherdantseva, Pete Burnap, Andrew Blyth, Peter Eden, Kevin Jones, Hugh Soulsby, Kristan Stoddart
Published in: Computers & Security (2015-10-21)

This paper reviews the state of the art in cyber security risk assessment of Supervisory Control and Data Acquisition (SCADA) systems. We select and in-detail examine twenty-four risk assessment methods developed for or applied in the context of a SCADA system. We describe the essence of the methods and then analyse them in terms of aim; application domain; the stages of risk management addressed; key risk management concepts covered; impact measurement; sources of probabilistic data; evaluation and tool support. Based on the analysis, we suggest an intuitive scheme for the categorisation of cyber security risk assessment methods for SCADA systems. We also outline five research challenges facing the domain and point out the approaches that might be taken.