Also called ubiquitous computing, pervasive computing is the concept that all man-made and some natural products will have embedded hardware and software technology and connectivity. This evolution has been proceeding exponentially as computing devices become progressively smaller and more powerful. The goal of pervasive computing, which combines current network technologies with wireless computing, voice recognition, Internet capability and artificial intelligence, is to create an environment where the connectivity of devices is embedded in such a way that the connectivity is unobtrusive and always available. Such an approach offers security challenges. The articles cited here were published in the first half of 2014.

• Chopra, A; Tokas, S.; Sinha, S.; Panchal, V.K., "Integration of Semantic Search Technique And Pervasive Computing," Computing for Sustainable Global Development (INDIACom), 2014 International Conference on ,pp.283,285, 5-7 March 2014. doi: 10.1109/IndiaCom.2014.6828144 The main goal of pervasive computing is to provide services that can be used by the user in the given context with minimal user intervention. To support such an environment services or the applications in the environment should be able to interact seamlessly, with the other devices or applications present in the environment, to gather relevant information in current context. Main challenge is devices are resource constrained. To support such systems, so that they can utilize resources of other sensor nodes/mobile devices, I propose a system that integrates semantic search in pervasive computing. Information associated with mobile devices and sensor nodes is used in a way that results in minimal inexact matching, efficient and improved service discovery. Keywords: information retrieval; ubiquitous computing; information gathering; mobile devices; pervasive computing; resource utilization; semantic search technique; sensor nodes; service discovery; user intervention; Context; Decision support systems; Mobile handsets; Pervasive computing; Resource description framework; Semantics; Wireless sensor networks; RDF; pervasive computing ;semantic search; service discovery (ID#:14-2452) URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6828144&isnumber=6827395

• Kiljander, J.; D'Elia, A; Morandi, F.; Hyttinen, P.; Takalo-Mattila, J.; Ylisaukko-oja, A; Soininen, J.; Salmon Cinotti, T., "Semantic interoperability architecture for pervasive computing and Internet of Things," Access, IEEE, vol. PP, no.99, pp.1, 1, August 2014. doi: 10.1109/ACCESS.2014.2347992 Pervasive computing and Internet of Things (IoT) paradigms have created a huge potential for new business. To fully realize this potential, there is a need for a common way to abstract the heterogeneity of devices so that their functionality can be represented as a virtual computing platform. To this end, we present novel semantic-level interoperability architecture for pervasive computing and Internet of Things (IoT). There are two main principles in the proposed architecture. First, information and capabilities of devices are represented with Semantic Web knowledge representation technologies and interaction with devices and the physical world is achieved by accessing and modifying their virtual representations. Second, global IoT is divided into numerous local smart spaces managed by a Semantic Information Broker (SIB) that provides a means to monitor and update the virtual representation of the physical world. An integral part of the architecture is a Resolution Infrastructure that provides a means to resolve the network address of a SIB either by using a physical object identifier as a pointer to information or by searching SIBs matching a specification represented with SPARQL. We present several reference implementations and applications that we have developed to evaluate the architecture in practice. The evaluation also includes performance studies that, together with the applications, demonstrate the suitability of the architecture to real-life IoT scenarios. Additionally, to validate that the proposed architecture conforms to the common IoT-A Architecture Reference Model (ARM), we map the central components of the architecture to the IoT-ARM. Keywords: Computer architecture; Context awareness; Interoperability; Pervasive computing; Resource description framework; Semantics; Sensors (ID#:14-2453) URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6879461&isnumber=6514899

• Strobel, D.; Oswald, D.; Richter, B.; Schellenberg, F.; Paar, C., "Microcontrollers as (In)Security Devices for Pervasive Computing Applications," Proceedings of the IEEE , vol.102, no.8, pp.1157,1173, Aug. 2014. doi: 10.1109/JPROC.2014.2325397 Often overlooked, microcontrollers are the central component in embedded systems which drive the evolution toward the Internet of Things (IoT). They are small, easy to handle, low cost, and with myriads of pervasive applications. An increasing number of microcontroller-equipped systems are security and safety critical. In this tutorial, we take a critical look at the security aspects of today's microcontrollers. We demonstrate why the implementation of sensitive applications on a standard microcontroller can lead to severe security problems. To this end, we summarize various threats to microcontroller-based systems, including side-channel analysis and different methods for extracting embedded code. In two case studies, we demonstrate the relevance of these techniques in real-world applications: Both analyzed systems, a widely used digital locking system and the YubiKey 2 onetime password generator, turned out to be susceptible to attacks against the actual implementations, allowing an adversary to extract the cryptographic keys which, in turn, leads to a total collapse of the system security. Keywords: Internet of Things; cryptography; embedded systems; microcontrollers; ubiquitous computing; Internet of Things; IoT; YubiKey 2 onetime password generator; cryptographic key extraction; digital locking system; embedded code extraction; embedded systems; microcontroller-equipped systems; pervasive computing applications; security devices; side-channel analysis; Algorithm design and analysis; Cryptography; Embedded systems; Field programmable gate arrays; Integrated circuit modeling; Microcontrollers; Pervasive computing; Security; Code extraction; microcontroller; real-world attacks; reverse engineering; side-channel analysis (ID#:14-2455) URL:http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6826474&isnumber=6860340

• Alomair, B.; Poovendran, R., "Efficient Authentication for Mobile and Pervasive Computing," Mobile Computing, IEEE Transactions on, vol.13, no.3, pp. 469,481, March 2014. doi: 10.1109/TMC.2012.252 With today's technology, many applications rely on the existence of small devices that can exchange information and form communication networks. In a significant portion of such applications, the confidentiality and integrity of the communicated messages are of particular interest. In this work, we propose two novel techniques for authenticating short encrypted messages that are directed to meet the requirements of mobile and pervasive applications. By taking advantage of the fact that the message to be authenticated must also be encrypted, we propose provably secure authentication codes that are more efficient than any message authentication code in the literature. The key idea behind the proposed techniques is to utilize the security that the encryption algorithm can provide to design more efficient authentication mechanisms, as opposed to using standalone authentication primitives. Keywords: cryptography; message authentication; mobile computing; communicated message confidentiality; communicated message integrity; communication networks; encryption algorithm; information exchange; mobile applications; mobile computing; pervasive applications; pervasive computing; provably secure authentication codes; short encrypted message authentication mechanism; Algorithm design and analysis; Authentication; Encryption; Message authentication; Authentication; computational security; pervasive computing; unconditional security; universal hash-function families (ID#:14-2456) URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6380496&isnumber=6731368

• Vihavainen, S.; Lampinen, A; Oulasvirta, A; Silfverberg, S.; Lehmuskallio, A, "The Clash between Privacy and Automation in Social Media," Pervasive Computing, IEEE, vol.13, no.1, pp.56, 63, Jan.-Mar. 2014. doi: 10.1109/MPRV.2013.25 Classic research on human factors has found that automation never fully eliminates the human operator from the loop. Instead, it shifts the operator's responsibilities to the machine and changes the operator's control demands, sometimes with adverse consequences, called the "ironies of automation." In this article, the authors revisit the problem of automation in the era of social media, focusing on privacy concerns. Present-day social media automatically discloses information, such as users' whereabouts, likings, and undertakings. This review of empirical studies exposes three recurring privacy-related issues in automated disclosure: insensitivity to situational demands, inadequate control of nuance and veracity, and inability to control disclosure with service providers and third parties. The authors claim that "all-or-nothing" automation has proven problematic and that social network services should design their user controls with all stages of the disclosure process in mind. Keywords: data privacy; human factors; social networking (online); automated disclosure; human factors; privacy-related issues; social media; social network services; Automation; Context awareness; Human factors; Media; Pervasive computing; Privacy; Social implications of technology; Social network services; automation; pervasive computing; privacy; social media (ID#:14-2457) URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6419690&isnumber=6750476

• Arbit, A; Oren, Y.; Wool, A, "A Secure Supply-Chain RFID System that Respects Your Privacy," Pervasive Computing, IEEE , vol.13, no.2, pp.52,60, Apr.-June. 2014. doi: 10.1109/MPRV.2014.22 Supply-chain RFID systems introduce significant privacy issues to consumers, making it necessary to encrypt communications. Because the resources available on tags are very small, it is generally assumed that only symmetric-key cryptography can be used in such systems. Unfortunately, symmetric-key cryptography imposes negative trust issues between the various stake-holders, and risks compromising the security of the whole system if even a single tag is reverse engineered. This work presents a working prototype implementation of a secure RFID system which uses public-key cryptography to simplify deployment, reduce trust issues between the supply-chain owner and tag manufacturer, and protect user privacy. The authors' prototype system consists of a UHF tag running custom firmware, a standard off-the-shelf reader and custom point-of-sale terminal software. No modifications were made to the reader or the air interface, proving that high-security EPC tags and standard EPC tags can coexist and share the same infrastructure. Keywords: data privacy; manufacturing data processing; public key cryptography; radiofrequency identification; supply chain management; UHF tag; custom point-of-sale terminal software; data privacy; high-security EPC tags; off-the-shelf reader; privacy issues; public key cryptography; radiofrequency identification; reverse engineering; secure supply-chain RFID system; supply-chain owner; symmetric-key cryptography; system security; tag manufacturer; trust issues user privacy; Encryption; Payloads; Protocols; Public key; Radiofrequency identification; Supply chain management; RFID; pervasive computing; security; supply chain (ID#:14-2458) URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6818503&isnumber=6818495

• Abas, K.; Porto, C.; Obraczka, K., "Wireless Smart Camera Networks for the Surveillance of Public Spaces," Computer, vol.47, no.5, pp.37,44, May 2014. doi: 10.1109/MC.2014.140 A taxonomy of wireless visual sensor networks for surveillance offers design goals that try to balance energy efficiency and application performance requirements. SWEETcam, a wireless smart camera network platform, tries to address the challenges raised by achieving adequate energy-performance tradeoffs. Keywords: cameras; video surveillance; wireless sensor networks; SWEETcam; energy-performance tradeoffs; public space surveillance; wireless smart camera networks; Bandwidth; Cameras; Data visualization; Energy efficiency; Smart cameras; Surveillance; Wireless communication; Wireless sensor networks; computer vision; distributed systems; embedded systems; hardware; image processing; pervasive computing; surveillance systems; visualization; wireless sensor networks (ID#:14-2459) URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6818944&isnumber=6818895

• Avoine, G.; Coisel, I; Martin, T., "Untraceability Model for RFID," Mobile Computing, IEEE Transactions on, vol. PP, no.99, pp.1, 1, December 2013. doi: 10.1109/TMC.2013.161 After several years of research on cryptographic models for privacy in RFID systems, it appears that no universally model exists yet. Experience shows that security experts usually prefer using their own ad-hoc model than the existing ones. In particular, the impossibility of the models to refine the privacy assessment of different protocols has been highlighted in several studies. The paper emphasizes the necessity to define a new model capable of comparing protocols meaningfully. It introduces an untraceability model that is operational where the previous models are not. The model aims to be easily usable to design proofs or describe attacks. This spirit led to a modular model where adversary actions (oracles), capabilities (selectors and restrictions), and goals (experiment) follow an intuitive and practical approach. This design enhances the ability to formalize new adversarial assumptions and future evolutions of the technology, and provide a finest privacy evaluation of protocols. Keywords: Pervasive computing; Security; Systems and Information Theory; and protection; integrity (ID#:14-2460) URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6692838&isnumber=4358975

• Chia-Mei Chen; Peng-Yu Yang; Ya-Hui Ou; Han-Wei Hsiao, "Targeted Attack Prevention at Early Stage," Advanced Information Networking and Applications Workshops (WAINA), 2014 28th International Conference on , vol., no., pp.866,870, 13-16 May 2014. doi: 10.1109/WAINA.2014.134 Targeted cyber attacks play a critical role in disrupting network infrastructure and information privacy. Based on the incident investigation, Intelligence gathering is the first phase of such attacks. To evade detection, hacker may make use of botnet, a set of zombie machines, to gain the access of a target and the zombies send the collected results back to the hacker. Even though the zombies would be blocked by detection system, the hacker, using the access information obtained from the botnet, would login the target from another machine without being noticed by the detection system. Such information gathering tactic can evade detection and the hacker grants the initial access to the target. The proposed defense system analyzes multiple logs from the network and extracts the reconnaissance attack sequences related to targeted attacks. State-based model is adopted to model the steps of the above early phase attack performed by multiple scouts and an intruder and such attack events in a long time frame becomes significant in the state-aware model. The results show that the proposed system can identify the attacks at the early stage efficiently to prevent further damage in the networks. Keywords: authorisation; data privacy; invasive software; ubiquitous computing; botnet; cyber attack;information privacy; intelligence gathering; network infrastructure; state-based model ;targeted attack prevention; Computer hacking; Hidden Markov models; IP networks; Joints; Reconnaissance; Servers intrusion detection; pervasive computing; targeted attacks (ID#:14-2461) URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6844748&isnumber=6844560

• Mirzadeh, S.; Cruickshank, H.; Tafazolli, R., "Secure Device Pairing: A Survey," Communications Surveys & Tutorials, IEEE , vol.16, no.1, pp.17,40, First Quarter 2014. doi: 10.1109/SURV.2013.111413.00196 In this paper, we discuss secure device pairing mechanisms in detail. We explain man-in-the-middle attack problem in unauthenticated Diffie-Hellman key agreement protocols and show how it can be solved by using out-of-band channels in the authentication procedure. We categorize out-of-band channels into three categories of weak, public, and private channels and demonstrate their properties through some familiar scenarios. A wide range of current device pairing mechanisms are studied and their design circumstances, problems, and security issues are explained. We also study group device pairing mechanisms and discuss their application in constructing authenticated group key agreement protocols. We divide the mechanisms into two categories of protocols with and without the trusted leader and show that protocols with trusted leader are more communication and computation efficient. In our study, we considered both insider and outsider adversaries and present protocols that provide secure group device pairing for uncompromised nodes even in presence of corrupted group members. Keywords: cryptographic protocols; authenticated group key agreement protocol; authentication procedure; device pairing mechanism; man-in-the-middle attack problem; out-of-band channel; private channel; public channel ;unauthenticated Diffie-Hellman key agreement protocols; Authentication; DH-HEMTs; Protocols; Public key; Wireless communication;key management; machine-to-machine communication; pervasive computing; security (ID#:14-2462) URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6687314&isnumber=6734839

• Thuong Nguyen, "Bayesian Nonparametric Extraction Of Hidden Contexts From Pervasive Honest Signals," Pervasive Computing And Communications Workshops (PERCOM Workshops), 2014 IEEE International Conference on , vol., no., pp.168,170, 24-28 March 2014. doi: 10.1109/PerComW.2014.6815190 Hidden patterns and contexts play an important part in intelligent pervasive systems. Most of the existing works have focused on simple forms of contexts derived directly from raw signals. High-level constructs and patterns have been largely neglected or remained under-explored in pervasive computing, mainly due to the growing complexity over time and the lack of efficient principal methods to extract them. Traditional parametric modeling approaches from machine learning find it difficult to discover new, unseen patterns and contexts arising from continuous growth of data streams due to its practice of training-then-prediction paradigm. In this work, we propose to apply Bayesian nonparametric models as a systematic and rigorous paradigm to continuously learn hidden patterns and contexts from raw social signals to provide basic building blocks for context-aware applications. Bayesian nonparametric models allow the model complexity to grow with data, fitting naturally to several problems encountered in pervasive computing. Under this framework, we use nonparametric prior distributions to model the data generative process, which helps towards learning the number of latent patterns automatically, adapting to changes in data and discovering never-seen-before patterns, contexts and activities. The proposed methods are agnostic to data types, however our work shall demonstrate to two types of signals: accelerometer activity data and Bluetooth proximal data. Keywords: data mining; learning (artificial intelligence); ubiquitous computing; Bayesian nonparametric extraction; Bayesian nonparametric models; Bluetooth proximal data; accelerometer activity data; context-aware applications; data streams; hidden contexts extraction; high-level constructs; high-level patterns; intelligent pervasive systems; machine learning; parametric modeling approach; pervasive computing; pervasive honest signals; social signals; training-then-prediction paradigm; Adaptation models; Context; Context modeling; Data mining; Data models; Hidden Markov models; Pervasive computing (ID#:14-2463) URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6815190&isnumber=6815123

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Articles listed on these pages have been found on publicly available internet pages and are cited with links to those pages. Some of the information included herein has been reprinted with permission from the authors or data repositories. Direct any requests via Email to SoS.Project (at) SecureDataBank.net for removal of the links or modifications to specific citations. Please include the ID# of the specific citation in your correspondence.