Cryptanalysis of LU Decomposition-based Key Pre-distribution Scheme for Wireless Sensor Networks

S. J. Choi and H. Y. Youn proposed a key pre-distribution scheme for Wireless Sensor Networks based on LU decomposition of symmetric matrix, and later many researchers did works based on this scheme. Nevertheless, we find a mathematical relationship of L and U matrixes decomposed from symmetric matrix, by using which we can calculate one matrix from another regardless of their product -- the key matrix K. This relationship would profoundly harm the secure implementation of this decomposition scheme in the real world. In this paper, we first present and prove the mathematical theorem. Next we give samples to illustrate how to break the networks by using this theorem. Finally, we state the conclusion and some directions for improving the security of the key pre-distribution scheme

Symmetry-Adapted Machine Learning for Information Security

Symmetry-adapted machine learning has shown encouraging ability to mitigate the security risks in information and communication technology (ICT) systems. It is a subset of artificial intelligence (AI) that relies on the principles of processing future events by learning past events or historical data. The autonomous nature of symmetry-adapted machine learning supports effective data processing and analysis for security detection in ICT systems without the interference of human authorities. Many industries are developing machine-learning-adapted solutions to support security for smart hardware, distributed computing, and the cloud. In our Special Issue book, we focus on the deployment of symmetry-adapted machine learning for information security in various application areas. This security approach can support effective methods to handle the dynamic nature of security attacks by extraction and analysis of data to identify hidden patterns of data. The main topics of this Issue include malware classification, an intrusion detection system, image watermarking, color image watermarking, battlefield target aggregation behavior recognition model, IP camera, Internet of Things (IoT) security, service function chain, indoor positioning system, and crypto-analysis

Security and Privacy for Modern Wireless Communication Systems

The aim of this reprint focuses on the latest protocol research, software/hardware development and implementation, and system architecture design in addressing emerging security and privacy issues for modern wireless communication networks. Relevant topics include, but are not limited to, the following: deep-learning-based security and privacy design; covert communications; information-theoretical foundations for advanced security and privacy techniques; lightweight cryptography for power constrained networks; physical layer key generation; prototypes and testbeds for security and privacy solutions; encryption and decryption algorithm for low-latency constrained networks; security protocols for modern wireless communication networks; network intrusion detection; physical layer design with security consideration; anonymity in data transmission; vulnerabilities in security and privacy in modern wireless communication networks; challenges of security and privacy in node–edge–cloud computation; security and privacy design for low-power wide-area IoT networks; security and privacy design for vehicle networks; security and privacy design for underwater communications networks

Exploitation of Unintentional Information Leakage from Integrated Circuits

Unintentional electromagnetic emissions are used to recognize or verify the identity of a unique integrated circuit (IC) based on fabrication process-induced variations in a manner analogous to biometric human identification. The effectiveness of the technique is demonstrated through an extensive empirical study, with results presented indicating correct device identification success rates of greater than 99:5%, and average verification equal error rates (EERs) of less than 0:05% for 40 near-identical devices. The proposed approach is suitable for security applications involving commodity commercial ICs, with substantial cost and scalability advantages over existing approaches. A systematic leakage mapping methodology is also proposed to comprehensively assess the information leakage of arbitrary block cipher implementations, and to quantitatively bound an arbitrary implementation\u27s resistance to the general class of differential side channel analysis techniques. The framework is demonstrated using the well-known Hamming Weight and Hamming Distance leakage models, and approach\u27s effectiveness is demonstrated through the empirical assessment of two typical unprotected implementations of the Advanced Encryption Standard. The assessment results are empirically validated against correlation-based differential power and electromagnetic analysis attacks

Recent Developments in Smart Healthcare

Medicine is undergoing a sector-wide transformation thanks to the advances in computing and networking technologies. Healthcare is changing from reactive and hospital-centered to preventive and personalized, from disease focused to well-being centered. In essence, the healthcare systems, as well as fundamental medicine research, are becoming smarter. We anticipate significant improvements in areas ranging from molecular genomics and proteomics to decision support for healthcare professionals through big data analytics, to support behavior changes through technology-enabled self-management, and social and motivational support. Furthermore, with smart technologies, healthcare delivery could also be made more efficient, higher quality, and lower cost. In this special issue, we received a total 45 submissions and accepted 19 outstanding papers that roughly span across several interesting topics on smart healthcare, including public health, health information technology (Health IT), and smart medicine

Efficient and secure business model for content centric network using elliptic curve cryptography

https://onlinelibrary.wiley.com/doi/full/10.1002/dac.3839Initially, Internet has evolved as a resource sharing model where resources are identified by IP addresses. However, with rapid technological advancement, resources/hardware has become cheap and thus, the need of sharing hardware over Internet is reduced. Moreover, people are using Internet mainly for information exchange and hence, Internet has gradually shifted from resource sharing to information sharing model. To meet the recent growing demand of information exchange, Content Centric Network (CCN) is envisaged as a clean‐slate future network architecture which is specially destined for smooth content distribution over Internet. In CCN, content is easily made available using network caching mechanism which is misaligned with the existing business policy of content providers/publishers in IP‐based Internet. Hence, the transition from contemporary IP‐based Internet to CCN demands attention for redesigning the business policy of the content publishers/providers. In this paper, we have proposed efficient and secure communication protocols for flexible CCN business model to protect the existing business policies of the content publisher while maintaining the salient CCN features like in‐network content caching and Interest packet aggregation. To enhance the efficiency and security, the Elliptic Curve Cryptography (ECC) is used. The proposed ECC‐based scheme is analyzed to show that it is resilient to relevant existing cryptographic attacks. The performance analysis in terms of less computation and communication overheads and increased efficiency is given. Moreover, a formal security verification of the proposed scheme is done using widely used AVISPA simulator and BAN logic that shows our scheme is well secured