Analysis of cloud computing attacks and countermeasures

Jabir, Raja; Khanji, Salam; Ahmad, Liza; Alfandi, Omar; Said, Huwida

doi:10.1109/icact.2016.7423296

Cited by 17 publications

(6 citation statements)

References 5 publications

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“…Therefore, the privacy of data transactions should be protected. This is a problem in centralized storage systems, which are really common in finance or industry, since such an infrastructure can suffer attacks or internal leaks [101], [102]. To prevent such issues, blockchain decentralizes storage.…”

Section: F Information Securitymentioning

confidence: 99%

A Review on Blockchain Technologies for an Advanced and Cyber-Resilient Automotive Industry

Fraga‐Lamas¹,

2019

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In the last century, the automotive industry has arguably transformed society, being one of the most complex, sophisticated, and technologically advanced industries, with innovations ranging from the hybrid, electric, and self-driving smart cars to the development of IoT-connected cars. Due to its complexity, it requires the involvement of many Industry 4.0 technologies, like robotics, advanced manufacturing systems, cyber-physical systems, or augmented reality. One of the latest technologies that can benefit the automotive industry is blockchain, which can enhance its data security, privacy, anonymity, traceability, accountability, integrity, robustness, transparency, trustworthiness, and authentication, as well as provide long-term sustainability and a higher operational efficiency to the whole industry. This review analyzes the great potential of applying blockchain technologies to the automotive industry emphasizing its cybersecurity features. Thus, the applicability of blockchain is evaluated after examining the state-of-the-art and devising the main stakeholders' current challenges. Furthermore, the article describes the most relevant use cases, since the broad adoption of blockchain unlocks a wide area of short-and medium-term promising automotive applications that can create new business models and even disrupt the car-sharing economy as we know it. Finally, after strengths, weaknesses, opportunities, and threats analysis, some recommendations are enumerated with the aim of guiding researchers and companies in future cyber-resilient automotive industry developments.

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Section: F Information Securitymentioning

confidence: 99%

A Review on Blockchain Technologies for an Advanced and Cyber-Resilient Automotive Industry

Fraga‐Lamas¹,

2019

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“…Commonly, FL architecture comprises a server or a cluster of servers living in the cloud. A cloud-based or a physical server can be a target for cloud computing and hacking attacks [36], [37] or Distributed Denial of service (DDos) attacks [38]. Furthermore, a compromised server can inspect all gradient updates sent to the server in any training rounds and tamper with the aggregation process.…”

Section: ) Compromised Servermentioning

confidence: 99%

Vulnerabilities in Federated Learning

2021

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With more regulations tackling the protection of users' privacy-sensitive data in recent years, access to such data has become increasingly restricted. A new decentralized training paradigm, known as Federated Learning (FL), enables multiple clients located at different geographical locations to learn a machine learning model collaboratively without sharing their data. While FL has recently emerged as a promising solution to preserve users' privacy, this new paradigm's potential security implications may hinder its widespread adoption. The existing FL protocols exhibit new unique vulnerabilities that adversaries can exploit to compromise the trained model. FL is often preferred in learning environments where security and privacy are the key concerns. Therefore, it is crucial to raise awareness of the consequences resulting from the new threats to FL systems. To date, the security of traditional machine learning systems has been widely examined. However, many open challenges and complex questions are still surrounding FL security. In this paper, we bridge the gap in FL literature by providing a comprehensive survey of the unique security vulnerabilities exposed by the FL ecosystem. We highlight the vulnerabilities sources, key attacks on FL, defenses, as well as their unique challenges, and discuss promising future research directions towards more robust FL.INDEX TERMS Attacks, defenses, Federated Learning, security threats, vulnerabilities.

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“…This is due to the fact that most of the data that is produced from IoT devices, like wearables and smart home devices, are very sensitive and private to their owners. With regard to the data that is produced and stored in IoT applications, it has been observed over the years that the system architectures and solutions have been built around centralized communications and [112,113]. If centralized systems cannot be trusted, then blockchains offer a decentralized system or approach that incorporates many nodes, that means no down times, and if one node is comprised, the others can keep the system running efficiently (iii) Availability.…”

Section: Current Challenges Faced In Biot Applicationsmentioning

confidence: 99%

On Blockchain and IoT Integration Platforms: Current Implementation Challenges and Future Perspectives

Nartey

Tchao

Gadze

et al. 2021

Wireless Communications and Mobile Computing

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Digitization and automation have engulfed every scope and sphere of life. Internet of Things (IoT) has been the main enabler of the revolution. There still exist challenges in IoT that need to be addressed such as the limited address space for the increasing number of devices when using IPv4 and IPv6 as well as key security issues such as vulnerable access control mechanisms. Blockchain is a distributed ledger technology that has immense benefits such as enhanced security and traceability. Thus, blockchain can serve as a good foundation for applications based on transaction and interactions. IoT implementations and applications are by definition distributed. This means blockchain can help to solve most of the security vulnerabilities and traceability concerns of IoTs by using blockchain as a ledger that can keep track of how devices interact, in which state they are and how they transact with other IoT devices. IoT applications have been mainly implemented with technologies such as cloud and fog computing, and AI to help address some of its key challenges. The key implementation challenges and technical choices to consider in making a successful blockchain IoT (BIoT) project are clearly outlined in this paper. The security and privacy aspect of BIoT applications are also analyzed, and several relevant solutions to improve the scalability and throughput of such applications are proposed. The paper also reviews integration schemes and monitoring frameworks for BIoT applications. A hybrid blockchain IoT integration architecture that makes use of containerization is proposed.

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Analysis of cloud computing attacks and countermeasures

Cited by 17 publications

References 5 publications

A Review on Blockchain Technologies for an Advanced and Cyber-Resilient Automotive Industry

A Review on Blockchain Technologies for an Advanced and Cyber-Resilient Automotive Industry

Vulnerabilities in Federated Learning

On Blockchain and IoT Integration Platforms: Current Implementation Challenges and Future Perspectives

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