# Information and Future Internet Security, Trust and Privacy
## 2 Contributions  
The first paper [4] introduces a phishing detection engine based on machine learning algorithms and URL features. Specifically, the authors used the Levenshtein distance as a similarity index feature to train a range of machine learning algorithms. The evaluation of a dataset with 305,737 benign URLs and 74,436 phishing URLs indicated that an averaged accuracy of 94% could be achieved.  
The second paper [5] introduces IoTSRM2, an IoT security risk management strategy reference model with the purpose of supporting practitioners in formulating the relevant IoT security risk management strategies. The authors started with the key cybersecurity drivers and then introduced a taxonomic hierarchy that can classify IoT security best practices based on the group and type of target audience.  
The third paper [6] discusses the challenges in APSIA (automated privacy and security impact assessment) and introduced a systematic approach for assessing the privacy impact levels of organizations according to the demanded security status and threat vectors. They then detailed the prototype implementation of APSIA and demonstrated its applicability through a case study in the healthcare domain. The authors believe that their approach could complement existing security-based risk assessment tools by enhancing the privacy aspect of all the involved partners.  
The fourth paper [7] reviews the existing standardization advancements in relation to blockchain and digital ledger techniques and introduces a set of criteria for comparing these standards and recommendations for blockchain systems/networks, which can be useful in the design of future networks. The authors also discussed the value of these techniques and criteria by analyzing the dependencies of the selected publications in relation to other standardization work.  
The fifth paper [8] focuses on IndexedDB, which is a NoSQL (not only SQL) transactional database system that enables swift access to persistent data through JSON (JavaScript object notation) objects, and explores whether it can be used as a source of digital evidence, i.e., providing hints to the traditional investigation methods. The authors took WhatsApp Messenger and Web Application as a case study in order to populate and investigate artifacts in the IndexedDB storage of Google Chrome. They found that the WhatsApp Web IndexedDB storage could be used for timeline analysis.  
The sixth paper [9] focuses on name data networking (NDN), a subtype of information centric networking (ICN), and proposed a strategy (PEKS-based NDN strategy) for protecting the names in NDN based on the best route strategy and multicast strategy. The proposed strategy can achieve higher privacy preservation without the need for a master secret key, which can be used to derive private keys. The authors also attempted to reduce the number of PEKS operations by loading several components at one time.  
The guest editors would like to thank all the contributing authors, the professional reviewers, and the excellent editorial support from the Future Internet editorial office during the publication process of this Special Issue.  
The authors declare no conflict of interest.