Visible to the public Biblio

Filters: Keyword is Distributed databases  [Clear All Filters]
2020-08-03
Moradi, Ashkan, Venkategowda, Naveen K. D., Werner, Stefan.  2019.  Coordinated Data-Falsification Attacks in Consensus-based Distributed Kalman Filtering. 2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP). :495–499.
This paper considers consensus-based distributed Kalman filtering subject to data-falsification attack, where Byzantine agents share manipulated data with their neighboring agents. The attack is assumed to be coordinated among the Byzantine agents and follows a linear model. The goal of the Byzantine agents is to maximize the network-wide estimation error while evading false-data detectors at honest agents. To that end, we propose a joint selection of Byzantine agents and covariance matrices of attack sequences to maximize the network-wide estimation error subject to constraints on stealthiness and the number of Byzantine agents. The attack strategy is then obtained by employing block-coordinate descent method via Boolean relaxation and backward stepwise based subset selection method. Numerical results show the efficiency of the proposed attack strategy in comparison with other naive and uncoordinated attacks.
2020-07-30
Showkatramani, Girish J., Khatri, Nidhi, Landicho, Arlene, Layog, Darwin.  2019.  A Secure Permissioned Blockchain Based System for Trademarks. 2019 IEEE International Conference on Decentralized Applications and Infrastructures (DAPPCON). :135—139.
A trademark may be a word, phrase, symbol, sound, color, scent or design, or combination of these, that identifies and distinguishes the products or services of a particular source from those of others. Obtaining a trademark is a complex, time intensive and costly process that involves varied steps before the trademark can be registered including searching prior trademarks, filing of the trademark application, review of the trademark application and final publication for opposition by the public. Currently, the process of trademark registration, renewal and validation faces numerous challenges such as the requirement for registration in different jurisdictions, maintenance of centralized databases in different jurisdictions, proving the authenticity of the physical trademark documents, identifying the violation and abuse of the intellectual property etc. to name a few. Recently, blockchain technology has shown great potential in a variety of industries such as finance, education, energy and resource management, healthcare, due to its decentralization and non-tampering features. Furthermore, in the recent years, smart contracts have attracted increased attention due to the popularity of blockchains. In this study, we have utilized Hyperledger fabric as the permissioned blockchain framework along with smart contracts to provide solution to the financial, procedural, enforcement and protection related challenges of the current trademark system. Our blockchain based application seeks to provide a secure, decentralized, immutable trademark system that can be utilized by the intellectual property organizations across different jurisdictions for easily and effectively registering, renewing, validating and distributing digital trademark certificates.
Yang, Fan, Shi, Yue, Wu, Qingqing, Li, Fei, Zhou, Wei, Hu, Zhiyan, Xiong, Naixue, Zhang, Yong.  2019.  The Survey on Intellectual Property Based on Blockchain Technology. 2019 IEEE International Conference on Industrial Cyber Physical Systems (ICPS). :743—748.
The characteristics of decentralization, tamper-resistance and transaction anonymity of blockchain can resolve effectively the problems in traditional intellectual property such as the difficulty of electronic obtaining for evidence, the high cost and low compensation when safeguarding the copyrights. Blockchain records the information through encryption algorithm, removes the third party, and stores the information in all nodes to prevent the information from being tampered with, so as to realize the protection of intellectual property. Starting from the bottom layer of blockchain, this paper expounds in detail the characteristics and the technical framework of blockchain. At the same time, according to the existing problems in transaction throughput, time delay and resource consumption of blockchain system, optimization mechanisms such as cross-chain and proof of stake are analyzed. Finally, combined with the characteristics of blockchain technology and existing application framework, this paper summarizes the existing problems in the industry and forecasts the development trend of intellectual property based on blockchain technology.
2020-07-24
Rotondi, Domenico, Saltarella, Marco.  2019.  Facing parallel market and counterfeit issues by the combined use of blockchain and CP-ABE encryption technologies. 2019 Global IoT Summit (GIoTS). :1—6.

Blockchains are emerging technologies that propose new business models and value propositions. Besides their application for cryptocurrency purposes, as distributed ledgers of transactions, they enable new ways to provision trusted information in a distributed fashion. In this paper, we present our product tagging solution designed to help Small & Medium Enterprises (SMEs) protect their brands against counterfeit products and parallel markets, as well as to enhance UX (User Experience) and promote the brand and product.Our solution combines the use of DLT to assure, in a verifiable and permanent way, the trustworthiness and confidentiality of the information associated to the goods and the innovative CP-ABE encryption technique to differentiate accessibility to the product's information.

2020-07-13
Manaka, Keisuke, Chen, Liyuan, Habuchi, Hiromasa, Kozawa, Yusuke.  2019.  Proposal of Equal-Weight (2, 2) Visual Secret Sharing Scheme on VN-CSK Illumination Light Communication. 2019 IEEE VTS Asia Pacific Wireless Communications Symposium (APWCS). :1–5.
Variable N-parallel code-shift-keying (VN-CSK) system has been proposed for solving the dimming control problem and the adjacent illumination light interference in illumination light communication. VN-CSK system only focuses on separating the light signal in the illumination light overlapping area. While, it is considerable to transmit a new data using the light overlapping. Visual secret sharing (VSS) scheme is a kind of secret sharing scheme, which distributes the secret data for security and restore by overlapping. It has high affinity to visible light communication. In this paper, a system combined with visible light communication and (2,2)-VSS scheme is proposed. In the proposed system, a modified pseudo orthogonal M-sequence is used that the occurrence probability of 0 and 1 of share is one-half in order to achieve a constant illuminance. In addition, this system use Modified Pseudo-Orthogonal M-sequence(MPOM) for ensuring the lighting function. The bit error rate performance of the proposed system is evaluated under the indoor visible light communication channel by simulation.
Oleshchuk, Vladimir.  2019.  Secure and Privacy Preserving Pattern Matching in Distributed Cloud-based Data Storage. 2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS). 2:820–823.
Given two strings: pattern p of length m and text t of length n. The string matching problem is to find all (or some) occurrences of the pattern p in the text t. We introduce a new simple data structure, called index arrays, and design fast privacy-preserving matching algorithm for string matching. The motivation behind introducing index arrays is determined by the need for pattern matching on distributed cloud-based datasets with semi-trusted cloud providers. It is intended to use encrypted index arrays both to improve performance and protect confidentiality and privacy of user data.
2020-07-10
Muñoz, Jordi Zayuelas i, Suárez-Varela, José, Barlet-Ros, Pere.  2019.  Detecting cryptocurrency miners with NetFlow/IPFIX network measurements. 2019 IEEE International Symposium on Measurements Networking (M N). :1—6.

In the last few years, cryptocurrency mining has become more and more important on the Internet activity and nowadays is even having a noticeable impact on the global economy. This has motivated the emergence of a new malicious activity called cryptojacking, which consists of compromising other machines connected to the Internet and leverage their resources to mine cryptocurrencies. In this context, it is of particular interest for network administrators to detect possible cryptocurrency miners using network resources without permission. Currently, it is possible to detect them using IP address lists from known mining pools, processing information from DNS traffic, or directly performing Deep Packet Inspection (DPI) over all the traffic. However, all these methods are still ineffective to detect miners using unknown mining servers or result too expensive to be deployed in real-world networks with large traffic volume. In this paper, we present a machine learning-based method able to detect cryptocurrency miners using NetFlow/IPFIX network measurements. Our method does not require to inspect the packets' payload; as a result, it achieves cost-efficient miner detection with similar accuracy than DPI-based techniques.

Yang, Ying, Yu, Huanhuan, Yang, Lina, Yang, Ming, Chen, Lijuan, Zhu, Guichun, Wen, Liqiang.  2019.  Hadoop-based Dark Web Threat Intelligence Analysis Framework. 2019 IEEE 3rd Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC). :1088—1091.

With the development of network services and people's privacy requirements continue to increase. On the basis of providing anonymous user communication, it is necessary to protect the anonymity of the server. At the same time, there are many threatening crime messages in the dark network. However, many scholars lack the ability or expertise to conduct research on dark-net threat intelligence. Therefore, this paper designs a framework based on Hadoop is hidden threat intelligence. The framework uses HDFS as the underlying storage system to build a HBase-based distributed database to store and manage threat intelligence information. According to the heterogeneous type of the forum, the web crawler is used to collect data through the anonymous TOR tool. The framework is used to identify the characteristics of key dark network criminal networks, which is the basis for the later dark network research.

Ra, Gyeong-Jin, Lee, Im-Yeong.  2019.  A Study on Hybrid Blockchain-based XGS (XOR Global State) Injection Technology for Efficient Contents Modification and Deletion. 2019 Sixth International Conference on Software Defined Systems (SDS). :300—305.

Blockchain is a database technology that provides the integrity and trust of the system can't make arbitrary modifications and deletions by being an append-only distributed ledger. That is, the blockchain is not a modification or deletion but a CRAB (Create-Retrieve-Append-Burn) method in which data can be read and written according to a legitimate user's access right(For example, owner private key). However, this can not delete the created data once, which causes problems such as privacy breach. In this paper, we propose an on-off block-chained Hybrid Blockchain system to separate the data and save the connection history to the blockchain. In addition, the state is changed to the distributed database separately from the ledger record, and the state is changed by generating the arbitrary injection in the XOR form, so that the history of modification / deletion of the Off Blockchain can be efficiently retrieved.

Podlesny, Nikolai J., Kayem, Anne V.D.M., Meinel, Christoph.  2019.  Identifying Data Exposure Across Distributed High-Dimensional Health Data Silos through Bayesian Networks Optimised by Multigrid and Manifold. 2019 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech). :556—563.

We present a novel, and use case agnostic method of identifying and circumventing private data exposure across distributed and high-dimensional data repositories. Examples of distributed high-dimensional data repositories include medical research and treatment data, where oftentimes more than 300 describing attributes appear. As such, providing strong guarantees of data anonymity in these repositories is a hard constraint in adhering to privacy legislation. Yet, when applied to distributed high-dimensional data, existing anonymisation algorithms incur high levels of information loss and do not guarantee privacy defeating the purpose of anonymisation. In this paper, we address this issue by using Bayesian networks to handle data transformation for anonymisation. By evaluating every attribute combination to determine the privacy exposure risk, the conditional probability linking attribute pairs is computed. Pairs with a high conditional probability expose the risk of deanonymisation similar to quasi-identifiers and can be separated instead of deleted, as in previous algorithms. Attribute separation removes the risk of privacy exposure, and deletion avoidance results in a significant reduction in information loss. In other words, assimilating the conditional probability of outliers directly in the adjacency matrix in a greedy fashion is quick and thwarts de-anonymisation. Since identifying every privacy violating attribute combination is a W[2]-complete problem, we optimise the procedure with a multigrid solver method by evaluating the conditional probabilities between attribute pairs, and aggregating state space explosion of attribute pairs through manifold learning. Finally, incremental processing of new data is achieved through inexpensive, continuous (delta) learning.

Zhang, Mengyu, Zhang, Hecan, Yang, Yahui, Shen, Qingni.  2019.  PTAD:Provable and Traceable Assured Deletion in Cloud Storage. 2019 IEEE Symposium on Computers and Communications (ISCC). :1—6.

As an efficient deletion method, unlinking is widely used in cloud storage. While unlinking is a kind of incomplete deletion, `deleted data' remains on cloud and can be recovered. To make `deleted data' unrecoverable, overwriting is an effective method on cloud. Users lose control over their data on cloud once deleted, so it is difficult for them to confirm overwriting. In face of such a crucial problem, we propose a Provable and Traceable Assured Deletion (PTAD) scheme in cloud storage based on blockchain. PTAD scheme relies on overwriting to achieve assured deletion. We reference the idea of data integrity checking and design algorithms to verify if cloud overwrites original blocks properly as specific patterns. We utilize technique of smart contract in blockchain to automatically execute verification and keep transaction in ledger for tracking. The whole scheme can be divided into three stages-unlinking, overwriting and verification-and we design one specific algorithm for each stage. For evaluation, we implement PTAD scheme on cloud and construct a consortium chain with Hyperledger Fabric. The performance shows that PTAD scheme is effective and feasible.

2020-07-09
Duan, Huayi, Zheng, Yifeng, Du, Yuefeng, Zhou, Anxin, Wang, Cong, Au, Man Ho.  2019.  Aggregating Crowd Wisdom via Blockchain: A Private, Correct, and Robust Realization. 2019 IEEE International Conference on Pervasive Computing and Communications (PerCom. :1—10.

Crowdsensing, driven by the proliferation of sensor-rich mobile devices, has emerged as a promising data sensing and aggregation paradigm. Despite useful, traditional crowdsensing systems typically rely on a centralized third-party platform for data collection and processing, which leads to concerns like single point of failure and lack of operation transparency. Such centralization hinders the wide adoption of crowdsensing by wary participants. We therefore explore an alternative design space of building crowdsensing systems atop the emerging decentralized blockchain technology. While enjoying the benefits brought by the public blockchain, we endeavor to achieve a consolidated set of desirable security properties with a proper choreography of latest techniques and our customized designs. We allow data providers to safely contribute data to the transparent blockchain with the confidentiality guarantee on individual data and differential privacy on the aggregation result. Meanwhile, we ensure the service correctness of data aggregation and sanitization by delicately employing hardware-assisted transparent enclave. Furthermore, we maintain the robustness of our system against faulty data providers that submit invalid data, with a customized zero-knowledge range proof scheme. The experiment results demonstrate the high efficiency of our designs on both mobile client and SGX-enabled server, as well as reasonable on-chain monetary cost of running our task contract on Ethereum.

2020-07-03
Fitwi, Alem, Chen, Yu, Zhu, Sencun.  2019.  A Lightweight Blockchain-Based Privacy Protection for Smart Surveillance at the Edge. 2019 IEEE International Conference on Blockchain (Blockchain). :552—555.

Witnessing the increasingly pervasive deployment of security video surveillance systems(VSS), more and more individuals have become concerned with the issues of privacy violations. While the majority of the public have a favorable view of surveillance in terms of crime deterrence, individuals do not accept the invasive monitoring of their private life. To date, however, there is not a lightweight and secure privacy-preserving solution for video surveillance systems. The recent success of blockchain (BC) technologies and their applications in the Internet of Things (IoT) shed a light on this challenging issue. In this paper, we propose a Lightweight, Blockchain-based Privacy protection (Lib-Pri) scheme for surveillance cameras at the edge. It enables the VSS to perform surveillance without compromising the privacy of people captured in the videos. The Lib-Pri system transforms the deployed VSS into a system that functions as a federated blockchain network capable of carrying out integrity checking, blurring keys management, feature sharing, and video access sanctioning. The policy-based enforcement of privacy measures is carried out at the edge devices for real-time video analytics without cluttering the network.

2020-06-29
Jamader, Asik Rahaman, Das, Puja, Acharya, Biswa Ranjan.  2019.  BcIoT: Blockchain based DDos Prevention Architecture for IoT. 2019 International Conference on Intelligent Computing and Control Systems (ICCS). :377–382.
The Internet of Things (IoT) visualizes a massive network with billions of interaction among smart things which are capable of contributing all sorts of services. Self-configuring things (nodes) are connected dynamically with a global network in IoT scenario. The small things are widely spread in a real world paradigm with minimal processing capacity and limited storage. The recent IoT technologies have more concerns about the security, privacy and reliability. Sharing personal data over the centralized system still remains as a challenging task. If the infrastructure is able to provide the assurance for transferring the data but for now it requires special attention on security and data consistency. Because, centralized system and infrastructure is viewed as a more attractive point for hacker or cyber-attacker. To solve this we present a secured smart contract based on Blockchain to develop a secured communicative network. A Hash based secret key is used for encryption and decryption purposes. A demo attack is done for developing a better understanding on blockchain technology in terms of their comparison and calculation.
Giri, Nupur, Jaisinghani, Rahul, Kriplani, Rohit, Ramrakhyani, Tarun, Bhatia, Vinay.  2019.  Distributed Denial Of Service(DDoS) Mitigation in Software Defined Network using Blockchain. 2019 Third International conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC). :673–678.
A DDoS attack is a spiteful attempt to disrupt legitimate traffic to a server by overwhelming the target with a flood of requests from geographically dispersed systems. Today attackers prefer DDoS attack methods to disrupt target services as they generate GBs to TBs of random data to flood the target. In existing mitigation strategies, because of lack of resources and not having the flexibility to cope with attacks by themselves, they are not considered to be that effective. So effective DDoS mitigation techniques can be provided using emerging technologies such as blockchain and SDN(Software-Defined Networking). We propose an architecture where a smart contract is deployed in a private blockchain, which facilitates a collaborative DDoS mitigation architecture across multiple network domains. Blockchain application is used as an additional security service. With Blockchain, shared protection is enabled among all hosts. With help of smart contracts, rules are distributed among all hosts. In addition, SDN can effectively enable services and security policies dynamically. This mechanism provides ASes(Autonomous Systems) the possibility to deploy their own DPS(DDoS Prevention Service) and there is no need to transfer control of the network to the third party. This paper focuses on the challenges of protecting a hybridized enterprise from the ravages of rapidly evolving Distributed Denial of Service(DDoS) attack.
2020-06-19
Chen, Yanping, Ma, Long, Xia, Hong, Gao, Cong, Wang, Zhongmin, Yu, Zhong.  2019.  Trust-Based Distributed Kalman Filter Estimation Fusion under Malicious Cyber Attacks. 2019 IEEE 21st International Conference on High Performance Computing and Communications; IEEE 17th International Conference on Smart City; IEEE 5th International Conference on Data Science and Systems (HPCC/SmartCity/DSS). :2255—2260.

We consider distributed Kalman filter for dynamic state estimation over wireless sensor networks. It is promising but challenging when network is under cyber attacks. Since the information exchange between nodes, the malicious attacks quickly spread across the entire network, which causing large measurement errors and even to the collapse of sensor networks. Aiming at the malicious network attack, a trust-based distributed processing frame is proposed. Which allows neighbor nodes to exchange information, and a series of trusted nodes are found using truth discovery. As a demonstration, distributed Cooperative Localization is considered, and numerical results are provided to evaluate the performance of the proposed approach by considering random, false data injection and replay attacks.

2020-06-03
Chopade, Mrunali, Khan, Sana, Shaikh, Uzma, Pawar, Renuka.  2019.  Digital Forensics: Maintaining Chain of Custody Using Blockchain. 2019 Third International conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC). :744—747.

The fundamental aim of digital forensics is to discover, investigate and protect an evidence, increasing cybercrime enforces digital forensics team to have more accurate evidence handling. This makes digital evidence as an important factor to link individual with criminal activity. In this procedure of forensics investigation, maintaining integrity of the evidence plays an important role. A chain of custody refers to a process of recording and preserving details of digital evidence from collection to presenting in court of law. It becomes a necessary objective to ensure that the evidence provided to the court remains original and authentic without tampering. Aim is to transfer these digital evidences securely using encryption techniques.

2020-06-02
Aliasgari, Malihe, Simeone, Osvaldo, Kliewer, Jörg.  2019.  Distributed and Private Coded Matrix Computation with Flexible Communication Load. 2019 IEEE International Symposium on Information Theory (ISIT). :1092—1096.

Tensor operations, such as matrix multiplication, are central to large-scale machine learning applications. These operations can be carried out on a distributed computing platform with a master server at the user side and multiple workers in the cloud operating in parallel. For distributed platforms, it has been recently shown that coding over the input data matrices can reduce the computational delay, yielding a tradeoff between recovery threshold and communication load. In this work, we impose an additional security constraint on the data matrices and assume that workers can collude to eavesdrop on the content of these data matrices. Specifically, we introduce a novel class of secure codes, referred to as secure generalized PolyDot codes, that generalizes previously published non-secure versions of these codes for matrix multiplication. These codes extend the state-of-the-art by allowing a flexible trade-off between recovery threshold and communication load for a fixed maximum number of colluding workers.

2020-05-22
Jemal, Jay, Kornegay, Kevin T..  2019.  Security Assessment of Blockchains in Heterogenous IoT Networks : Invited Presentation. 2019 53rd Annual Conference on Information Sciences and Systems (CISS). :1—4.

As Blockchain technology become more understood in recent years and its capability to solve enterprise business use cases become evident, technologist have been exploring Blockchain technology to solve use cases that have been daunting industries for years. Unlike existing technologies, one of the key features of blockchain technology is its unparalleled capability to provide, traceability, accountability and immutable records that can be accessed at any point in time. One application area of interest for blockchain is securing heterogenous networks. This paper explores the security challenges in a heterogonous network of IoT devices and whether blockchain can be a viable solution. Using an experimental approach, we explore the possibility of using blockchain technology to secure IoT devices, validate IoT device transactions, and establish a chain of trust to secure an IoT device mesh network, as well as investigate the plausibility of using immutable transactions for forensic analysis.

2020-04-13
Agostino Ardagna, Claudio, Asal, Rasool, Damiani, Ernesto, El Ioini, Nabil, Pahl, Claus.  2019.  Trustworthy IoT: An Evidence Collection Approach Based on Smart Contracts. 2019 IEEE International Conference on Services Computing (SCC). :46–50.
Today, Internet of Things (IoT) implements an ecosystem where a panoply of interconnected devices collect data from physical environments and supply them to processing services, on top of which cloud-based applications are built and provided to mobile end users. The undebatable advantages of smart IoT systems clash with the need of a secure and trustworthy environment. In this paper, we propose a service-based methodology based on blockchain and smart contracts for trustworthy evidence collection at the basis of a trustworthy IoT assurance evaluation. The methodology balances the provided level of trustworthiness and its performance, and is experimentally evaluated using Hyperledger fabric blockchain.
2020-04-06
Chen, Yuxiang, Dong, Guishan, Bai, Jian, Hao, Yao, Li, Feng, Peng, Haiyang.  2019.  Trust Enhancement Scheme for Cross Domain Authentication of PKI System. 2019 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC). :103–110.
Public Key Infrastructure (PKI) has been popularized in many scenarios such as e-government applications, enterprises, etc. Due to the construction of PKI system of various regions and departments, there formed a lot of isolated PKI management domains, cross-domain authentication has become a problem that cannot ignored, which also has some traditional solutions such as cross-authentication, trust list, etc. However, some issues still exist, which hinder the popularity of unified trust services. For example, lack of unified cross domain standard, the update period of Certificate Revocation List (CRL) is too long, which affects the security of cross-domain authentication. In this paper, we proposed a trust transferring model by using blockchain consensus instead of traditional trusted third party for e-government applications. We exploit how to solve the unified trust service problem of PKI at the national level through consensus and transfer some CA management functions to the blockchain. And we prove the scheme's feasibility from engineering perspective. Besides, the scheme has enough scalability to satisfy trust transfer requirements of multiple PKI systems. Meanwhile, the security and efficiency are also guaranteed compared with traditional solutions.
Wu, Yichang, Qiao, Yuansong, Ye, Yuhang, Lee, Brian.  2019.  Towards Improved Trust in Threat Intelligence Sharing using Blockchain and Trusted Computing. 2019 Sixth International Conference on Internet of Things: Systems, Management and Security (IOTSMS). :474–481.
Threat intelligence sharing is posited as an important aid to help counter cybersecurity attacks and a number of threat intelligence sharing communities exist. There is a general consensus that many challenges remain to be overcome to achieve fully effective sharing, including concerns about privacy, negative publicity, policy/legal issues and expense of sharing, amongst others. One recent trend undertaken to address this is the use of decentralized blockchain based sharing architectures. However while these platforms can help increase sharing effectiveness they do not fully address all of the above challenges. In particular, issues around trust are not satisfactorily solved by current approaches. In this paper, we describe a novel trust enhancement framework -TITAN- for decentralized sharing based on the use of P2P reputation systems to address open trust issues. Our design uses blockchain and Trusted Execution Environment technologies to ensure security, integrity and privacy in the operation of the threat intelligence sharing reputation system.
Huang, Wei-Chiao, Yeh, Lo-Yao, Huang, Jiun-Long.  2019.  A Monitorable Peer-to-Peer File Sharing Mechanism. 2019 20th Asia-Pacific Network Operations and Management Symposium (APNOMS). :1–4.
With the rise of blockchain technology, peer-to-peer network system has once again caught people's attention. Peer-to-peer (P2P) is currently being implemented on various kind of decentralized systems such as InterPlanetary File System (IPFS). However, P2P file sharing network systems is not without its flaws. Data stored in the other nodes cannot be deleted by the owner and can only be deleted by other nodes themselves. Ensuring that personal data can be completely removed is an important issue to comply with the European Union's General Data Protection Regulation (GDPR) criteria. To improve P2Ps privacy and security, we propose a monitorable peer-to-peer file sharing mechanism that synchronizes with other nodes to perform file deletion and to generate the File Authentication Code (FAC) of each IPFS nodes in order to make sure the system synchronized correctly. The proposed mechanism can integrate with a consortium Blockchain to comply with GDPR.
2020-03-30
Scherzinger, Stefanie, Seifert, Christin, Wiese, Lena.  2019.  The Best of Both Worlds: Challenges in Linking Provenance and Explainability in Distributed Machine Learning. 2019 IEEE 39th International Conference on Distributed Computing Systems (ICDCS). :1620–1629.
Machine learning experts prefer to think of their input as a single, homogeneous, and consistent data set. However, when analyzing large volumes of data, the entire data set may not be manageable on a single server, but must be stored on a distributed file system instead. Moreover, with the pressing demand to deliver explainable models, the experts may no longer focus on the machine learning algorithms in isolation, but must take into account the distributed nature of the data stored, as well as the impact of any data pre-processing steps upstream in their data analysis pipeline. In this paper, we make the point that even basic transformations during data preparation can impact the model learned, and that this is exacerbated in a distributed setting. We then sketch our vision of end-to-end explainability of the model learned, taking the pre-processing into account. In particular, we point out the potentials of linking the contributions of research on data provenance with the efforts on explainability in machine learning. In doing so, we highlight pitfalls we may experience in a distributed system on the way to generating more holistic explanations for our machine learning models.
2020-03-23
Li, Min, Tang, Helen, Wang, Xianbin.  2019.  Mitigating Routing Misbehavior using Blockchain-Based Distributed Reputation Management System for IoT Networks. 2019 IEEE International Conference on Communications Workshops (ICC Workshops). :1–6.
With the rapid proliferation of Internet of Thing (IoT) devices, many security challenges could be introduced at low-end routers. Misbehaving routers affect the availability of the networks by dropping packets selectively and rejecting data forwarding services. Although existing Reputation Management (RM) systems are useful in identifying misbehaving routers, the centralized nature of the RM center has the risk of one-point failure. The emerging blockchain techniques, with the inherent decentralized consensus mechanism, provide a promising method to reduce this one-point failure risk. By adopting the distributed consensus mechanism, we propose a blockchain-based reputation management system in IoT networks to overcome the limitation of centralized router RM systems. The proposed solution utilizes the blockchain technique as a decentralized database to store router reports for calculating reputation of each router. With the proposed reputation calculation mechanism, the reliability of each router would be evaluated, and the malicious misbehaving routers with low reputations will be blacklisted and get isolated. More importantly, we develop an optimized group mining process for blockchain technique in order to improve the efficiency of block generation and reduce the resource consumption. The simulation results validate the distributed blockchain-based RM system in terms of attacks detection and system convergence performance, and the comparison result of the proposed group mining process with existing blockchain models illustrates the applicability and feasibility of the proposed works.