Journal Information
Computers & Security
http://www.journals.elsevier.com/computers-and-security/
Impact Factor:
3.062
Publisher:
ELSEVIER
ISSN:
0167-4048
Viewed:
11910
Tracked:
50

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Call For Papers
Computers & Security is the most respected technical journal in the IT security field. Now in its 29th year, with a new editorial board and new regular features and columns, the journal is essential reading for IT security professionals around the world.

Computers & Security provides you with a unique blend of leading edge research and sound practical management advice. It is aimed at the professional involved with computer security, audit, control and data integrity in all sectors - industry, commerce and academia. Recognized worldwide as THE primary source of reference for applied research and technical expertise it is your first step to fully secure systems.

Subscribe today and see the benefits immediately!

• Our cutting edge research will help you secure and maintain the integrity of your systems
• We accept only the highest quality of papers ensuring that you receive the relevant and practical advice you need
• Our editorial board's collective expertise will save you from paying thousands of pounds to IT consultants
• We don't just highlight the threats, we give you the solutions
Last updated by Dou Sun in 2019-11-24
Special Issues
Special Issue on Privacy in Computing with Big Data and AI
Submission Date: 2019-12-31

The rapid growth of the ICT technologies makes today's society highly digitized and connected, and the advent of even newer technologies such as Internet of Things (IoT) and Cyber-Physical Systems (CPS) further extends the hyper digitization and connectivity from the cyber space into the physical space. In this cyber-physical space, many of us reply on different online and physical services to live our lives and do businesses. This leads to more and more personal data being disclosed to organizations behind such services and other people using such services. Many organizations now have access to data from a large number of people, allowing them to do big data analytics and to offer more targeted (i.e., personalized) services to their customers such as behavioral advertising. This leads to the digital data economy era, and data is incrementally seen as the key to drive future innovations. While the big data landscape benefits many human users through better services, more and more privacy issues also arise such as more frequent and larger-scale data breach incidents. Although many privacy enhancement technologies (PETs) have offered solutions to protect our personal data, many still have practical limitations (e.g., not effective or efficient enough, less user-centric). The big data vs. privacy dilemma calls for more research on privacy computing as a special sub-area of cyber security, which requires involving researchers and practitioners from many other disciplines such as mathematics, electronic engineering, business, law, psychology, economics, sociology. In addition, research on big data based privacy computing also has a lot of overlaps with AI, e.g., on privacy attacks based on AI, privacy leakage from AI models, privacy and ethical issues related to AI, and new paradigms of AI models that are more privacy-aware or privacy-friendly. The aim of this special issue is to create a venue for privacy computing research from different disciplines to meet. Topics of interest include but are not limited to the following: Metrics for privacy computing such as differential privacy Privacy of or by AI (machine learning, data mining and knowledge discovery) e.g. privacy-preserving learning and federated learning Privacy operation and modelling Privacy attacks e.g. AI-based attacks or privacy leakage from AI models Computational taxonomies and ontologies for privacy computing User-centric and personalized privacy computing in the big data context Trade-off between privacy and security, trust, autonomy, reliability, resilience, fault-tolerance Private information collection, storage, aggregation and retrieval Privacy in different big-data contexts such as online social networks, healthcare, IoT and e-government Privacy issues in blockchains and cryptocurrencies Interaction between technologies and data protection / privacy law such as the EU GDPR Interactions between privacy computing and psychology and wider social sciences such as privacy concerns, privacy paradox, privacy calculus, and privacy decision making Interactions between privacy computing and business research such as privacy management and data protection impact assessment
Last updated by Dou Sun in 2019-10-14
Special Issue on A Multidisciplinary Approach to Internet of Things Cybersecurity and Risk Management
Submission Date: 2020-01-03

Internet of Things (IoT) links physical and virtual objects by leveraging data capture and communication capabilities. Increasingly, IoT can be found in a broad range of commercial (e.g., smart and connected cities, and industry 4.0) and national security applications (e.g., critical infrastructure and Internet of Battlefield and Military Things). Due to the interconnectivity of IoT and the broader society, it is important to ensure the security of IoT and the underpinning systems. While there is no foolproof solution, we need to take a transdisciplinary approach to understand the cybersecurity risk and threat landscape, in order to formulate appropriate risk mitigation strategies. For example, How do we design more effective solutions that mitigate existing and emerging threats to IoT and the underpinning systems, such as physics attacks, sliding channels attacks, environmental attacks, cryptanalysis attacks, software attacks, and network attacks, without affecting users’ quality of experience and quality? How do we take a transdisciplinary approach to understanding the cybersecurity risk and threat landscape, and take into consideration the imperfection of cybersecurity and physical security management system in the design of the next generation cybersecurity and risk management solutions? How do we balance the need for higher level of security (and user privacy) with legitimate surveillance and lawful data access (e.g., in law enforcement investigations)? In this special issue, we will focus on cutting edge research from both academia and industry to address the above research questions, with a particular focus on multidisciplinary research. Topics of interest include, but are not limited to the below categories (however, crypto-oriented topics are beyond the scope of this journal and special issue): Cybersecurity and risk management IoT cybersecurity incident response and management Cybercrime prevention strategies, relating to IoT systems Data protection in cloud-enhanced IoT systems Physical security management of IoT systems Secure network access in IoT systems Identity management and authentication of IoT Secure edge-powered IoT design IoT trust and governance IoT secure middleware design IoT mobility security and risk management Blockchain-enabled risk management method Emerging threats to IoT Secure information integrity of IoT Other security and privacy-related issues in connected critical infrastructure Privacy Enhancing and/or preserving IoT data privacy IoT surveillance Legal issues relating to surveillance and user privacy, relating to IoT systems Transparency and accountability of IoT systems IoT forensics and anti-forensics Secure data provenance in IoT High quality survey papers on the above topics are welcome.
Last updated by Dou Sun in 2019-09-07
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