As we delve into the Internet of Things (IoT), we are witnessing the intensive interaction and heterogeneous communication among different devices over the Internet. Consequently, these devices generate a massive volume of Big Data. The potential of these data has been analyzed by the complex network theory, describing a specialized branch, known as 'Human Dynamics.' The potential of these data has been analyzed by the complex network theory, describing a specialized branch, known as 'Human Dynamics.' In this extension, the goal is to describe human behavior in the social area at real-time. These objectives are starting to be practicable through the quantity of data provided by smartphones, social network, and smart cities. These make the environment more intelligent and offer an intelligent space to sense our activities or actions, and the evolution of the ecosystem. To address the aforementioned needs, this paper presents the concept of 'defining human behavior' using Big Data in SIoT by proposing system architecture that processes and analyzes big data in real-time. The proposed architecture consists of three operational domains, i.e., object, SIoT server, application domain. Data from object domain is aggregated at SIoT server domain, where the data is efficiently store and process and intelligently respond to the outer stimuli. The proposed system architecture focuses on the analysis the ecosystem provided by Smart Cities, wearable devices (e.g., body area network) and Big Data to determine the human behaviors as well as human dynamics. Furthermore, the feasibility and efficiency of the proposed system are implemented on Hadoop single node setup on UBUNTU 14.04 LTS coreTMi5 machine with 3.2 GHz processor and 4 GB memory.
{"title":"Defining Human Behaviors Using Big Data Analytics in Social Internet of Things","authors":"Awais Ahmad, M. Rathore, Anand Paul, Su-Ryun Rho","doi":"10.1109/AINA.2016.104","DOIUrl":"https://doi.org/10.1109/AINA.2016.104","url":null,"abstract":"As we delve into the Internet of Things (IoT), we are witnessing the intensive interaction and heterogeneous communication among different devices over the Internet. Consequently, these devices generate a massive volume of Big Data. The potential of these data has been analyzed by the complex network theory, describing a specialized branch, known as 'Human Dynamics.' The potential of these data has been analyzed by the complex network theory, describing a specialized branch, known as 'Human Dynamics.' In this extension, the goal is to describe human behavior in the social area at real-time. These objectives are starting to be practicable through the quantity of data provided by smartphones, social network, and smart cities. These make the environment more intelligent and offer an intelligent space to sense our activities or actions, and the evolution of the ecosystem. To address the aforementioned needs, this paper presents the concept of 'defining human behavior' using Big Data in SIoT by proposing system architecture that processes and analyzes big data in real-time. The proposed architecture consists of three operational domains, i.e., object, SIoT server, application domain. Data from object domain is aggregated at SIoT server domain, where the data is efficiently store and process and intelligently respond to the outer stimuli. The proposed system architecture focuses on the analysis the ecosystem provided by Smart Cities, wearable devices (e.g., body area network) and Big Data to determine the human behaviors as well as human dynamics. Furthermore, the feasibility and efficiency of the proposed system are implemented on Hadoop single node setup on UBUNTU 14.04 LTS coreTMi5 machine with 3.2 GHz processor and 4 GB memory.","PeriodicalId":438655,"journal":{"name":"2016 IEEE 30th International Conference on Advanced Information Networking and Applications (AINA)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114746852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Seiji Matsuyama, Takatomo Yamabe, Yuki Nakayama, Yukari Okuwaki, R. Kiyohara
Recently, smartphones have become widely used as vehicle information devices. As a result, several advantages have appeared. First, a smartphone can log driving data such as location, vehicle status information, and so on. The logs do not depend on the car, but on the smartphone user. Second, a smartphone can gather driving-related information via the Internet. We believe that the advantages enable us to recognize several contexts. Therefore, we proposed a system that supports the user in changing provided services based on the context. We have discussed context recognition in order to create the system. One of the discussion outcomes is that the location context holds a very important role in guessing which function is required by a driver. However, it is difficult to recognize the location context using only latitude-longitude logs. In this paper, we propose a method for recognizing location context. The method is separated into three steps. First, values are recorded in a travel history such as a meshed map. The values represent driving experience points in a travelling area. Second, the method searches the travel history for a given driving area. Then, the value of the searched area is compared with a specified threshold. As a result, the location context is recognized. We implemented a prototype system and evaluated the proposed method. The results of the evaluation confirm the effectiveness of both the proposed method and expected future work.
{"title":"A Method for Recognizing Driver's Location Context with a Vehicle Information Device","authors":"Seiji Matsuyama, Takatomo Yamabe, Yuki Nakayama, Yukari Okuwaki, R. Kiyohara","doi":"10.1109/AINA.2016.16","DOIUrl":"https://doi.org/10.1109/AINA.2016.16","url":null,"abstract":"Recently, smartphones have become widely used as vehicle information devices. As a result, several advantages have appeared. First, a smartphone can log driving data such as location, vehicle status information, and so on. The logs do not depend on the car, but on the smartphone user. Second, a smartphone can gather driving-related information via the Internet. We believe that the advantages enable us to recognize several contexts. Therefore, we proposed a system that supports the user in changing provided services based on the context. We have discussed context recognition in order to create the system. One of the discussion outcomes is that the location context holds a very important role in guessing which function is required by a driver. However, it is difficult to recognize the location context using only latitude-longitude logs. In this paper, we propose a method for recognizing location context. The method is separated into three steps. First, values are recorded in a travel history such as a meshed map. The values represent driving experience points in a travelling area. Second, the method searches the travel history for a given driving area. Then, the value of the searched area is compared with a specified threshold. As a result, the location context is recognized. We implemented a prototype system and evaluated the proposed method. The results of the evaluation confirm the effectiveness of both the proposed method and expected future work.","PeriodicalId":438655,"journal":{"name":"2016 IEEE 30th International Conference on Advanced Information Networking and Applications (AINA)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126617117","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Z. Ullah, Muhammad Saleem Khan, Idrees Ahmed, N. Javaid, M. Khan
Cooperation among nodes is mandatory for smooth operation of Mobile Ad Hoc Networks (MANETs) in terms of data routing. A participating node may refuse to deplete its resources for the benefit of others because of not getting any direct advantage for its service. Nodes showing such behavior are called selfish or non-cooperative nodes. Non-cooperative nodes can severely affect the performance of MANETs. Non-cooperative behavior of nodes in the MANETs may lead to network partitioning. In this paper, we address the issue of non-cooperative behavior by incorporating the concept of fuzzy logic closely coupled with the concept of trust. Fuzzy-based analyzer is used to distinguish between the non-cooperative behavior nodes and trustworthy nodes. We propose a fuzzy-based scheme to detect and isolate non-cooperative nodes in MANETs. In the proposed scheme, every node in the network constantly monitors its one-hop neighbors for their actions. Every node computes the trust of the observed neighbors. These trust values are passed on to a fuzzy function which is mapped into different classes. The resulting classes show the trust levels of the observed nodes. On the basis of the calculated trust value, the non-cooperative nodes are detected and isolated from the active routes of the MANET. Proposed fuzzy-based scheme is robust enough in terms of detecting packet drop attack in the network. Results show that proposed scheme detects non-cooperative nodes effectively with low false positives rate. Moreover, proposed scheme increases the packet delivery ratio and throughput in the presence of non-cooperative nodes in the network.
{"title":"Fuzzy-Based Trust Model for Detection of Selfish Nodes in MANETs","authors":"Z. Ullah, Muhammad Saleem Khan, Idrees Ahmed, N. Javaid, M. Khan","doi":"10.1109/AINA.2016.142","DOIUrl":"https://doi.org/10.1109/AINA.2016.142","url":null,"abstract":"Cooperation among nodes is mandatory for smooth operation of Mobile Ad Hoc Networks (MANETs) in terms of data routing. A participating node may refuse to deplete its resources for the benefit of others because of not getting any direct advantage for its service. Nodes showing such behavior are called selfish or non-cooperative nodes. Non-cooperative nodes can severely affect the performance of MANETs. Non-cooperative behavior of nodes in the MANETs may lead to network partitioning. In this paper, we address the issue of non-cooperative behavior by incorporating the concept of fuzzy logic closely coupled with the concept of trust. Fuzzy-based analyzer is used to distinguish between the non-cooperative behavior nodes and trustworthy nodes. We propose a fuzzy-based scheme to detect and isolate non-cooperative nodes in MANETs. In the proposed scheme, every node in the network constantly monitors its one-hop neighbors for their actions. Every node computes the trust of the observed neighbors. These trust values are passed on to a fuzzy function which is mapped into different classes. The resulting classes show the trust levels of the observed nodes. On the basis of the calculated trust value, the non-cooperative nodes are detected and isolated from the active routes of the MANET. Proposed fuzzy-based scheme is robust enough in terms of detecting packet drop attack in the network. Results show that proposed scheme detects non-cooperative nodes effectively with low false positives rate. Moreover, proposed scheme increases the packet delivery ratio and throughput in the presence of non-cooperative nodes in the network.","PeriodicalId":438655,"journal":{"name":"2016 IEEE 30th International Conference on Advanced Information Networking and Applications (AINA)","volume":"2005 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125809209","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Over recent years, packet processing acceleration has become a hot topic. Indeed, several software solutions have been developed to offer the best possible performance. Recently, a new open source project has started called OpenDataPlane (ODP), this framework provides a set of APIs, configuration files, and other functions to accelerate packet processing and manage effectively the networking data plane. In this paper, we present our new Xen architecture, implemented within Metamorphic Networks "MNet" platform that integrates ODP in a privileged domain, called driver domain. This architecture allows us to associate ODP with virtual CPU cores in order to accelerate packet processing and improve the performance of our platform, without adding overhead in physical processors. The results of our experiments show that our new architecture improves packet processing performance by 15%, only using the virtual CPU resources.
{"title":"Accelerating Packet Processing in a Xen Environment with OpenDataPlane","authors":"Tarek Rabia, Othmen Braham, G. Pujolle","doi":"10.1109/AINA.2016.27","DOIUrl":"https://doi.org/10.1109/AINA.2016.27","url":null,"abstract":"Over recent years, packet processing acceleration has become a hot topic. Indeed, several software solutions have been developed to offer the best possible performance. Recently, a new open source project has started called OpenDataPlane (ODP), this framework provides a set of APIs, configuration files, and other functions to accelerate packet processing and manage effectively the networking data plane. In this paper, we present our new Xen architecture, implemented within Metamorphic Networks \"MNet\" platform that integrates ODP in a privileged domain, called driver domain. This architecture allows us to associate ODP with virtual CPU cores in order to accelerate packet processing and improve the performance of our platform, without adding overhead in physical processors. The results of our experiments show that our new architecture improves packet processing performance by 15%, only using the virtual CPU resources.","PeriodicalId":438655,"journal":{"name":"2016 IEEE 30th International Conference on Advanced Information Networking and Applications (AINA)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126841822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. Treboux, Fabian Cretton, Florian Evéquoz, A. Calvé, D. Genoud
Most of today's commercial companies heavily rely on social media and community management tools to interact with their clients and analyze their online behaviour. Nonetheless, these tools still lack evolved data mining and visualization features to tailor the analysis in order to support useful marketing decisions. We present an original methodology that aims at formalizing the marketing need of the company and develop a tool that can support it. The methodology is derived from the Cross-Industry Standard Process for Data Mining (CRISP-DM) and includes additional steps dedicated to the design and development of visualizations of mined data. We followed the methodology in two use cases with Swiss companies. First, we developed a prototype that aims at understanding the needs of tourists based on Flickr and Instagram data. In that use case, we extend the existing literature by enriching hashtags analysis methods with a semantic network based on Linked Data. Second, we analyzed internal customer data of an online discount retailer to help them define guerilla marketing measures. We report on the challenges of integrating Facebook data in the process. Informal feedback from domain experts confirms the strong potential of such advanced analytic features based on social data to inform marketing decisions.
{"title":"Mining and Visualizing Social Data to Inform Marketing Decisions","authors":"J. Treboux, Fabian Cretton, Florian Evéquoz, A. Calvé, D. Genoud","doi":"10.1109/AINA.2016.130","DOIUrl":"https://doi.org/10.1109/AINA.2016.130","url":null,"abstract":"Most of today's commercial companies heavily rely on social media and community management tools to interact with their clients and analyze their online behaviour. Nonetheless, these tools still lack evolved data mining and visualization features to tailor the analysis in order to support useful marketing decisions. We present an original methodology that aims at formalizing the marketing need of the company and develop a tool that can support it. The methodology is derived from the Cross-Industry Standard Process for Data Mining (CRISP-DM) and includes additional steps dedicated to the design and development of visualizations of mined data. We followed the methodology in two use cases with Swiss companies. First, we developed a prototype that aims at understanding the needs of tourists based on Flickr and Instagram data. In that use case, we extend the existing literature by enriching hashtags analysis methods with a semantic network based on Linked Data. Second, we analyzed internal customer data of an online discount retailer to help them define guerilla marketing measures. We report on the challenges of integrating Facebook data in the process. Informal feedback from domain experts confirms the strong potential of such advanced analytic features based on social data to inform marketing decisions.","PeriodicalId":438655,"journal":{"name":"2016 IEEE 30th International Conference on Advanced Information Networking and Applications (AINA)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123533278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Many approaches have been proposed to detect stepping-stone intrusion, but few of them can effectively be resistant to intruders' manipulation, such as chaff perturbation, and time-jittering evasion techniques. In this paper, we propose a new approach to not only detect stepping-stone intrusion, but also resist intruders' chaff attack evasion through TCP/IP packet cross-matching and random walk. Unlike other approaches which can just resist intruders' chaff attack to a certain degree, this approach can be immune to any number packets injected. The theory analysis and simulation results show that more injection packets, the higher the probability that the chaff attack is detected.
{"title":"Resistance to Chaff Attack through TCP/IP Packet Cross-Matching and RTT-Based Random Walk","authors":"Jianhua Yang","doi":"10.1109/AINA.2016.17","DOIUrl":"https://doi.org/10.1109/AINA.2016.17","url":null,"abstract":"Many approaches have been proposed to detect stepping-stone intrusion, but few of them can effectively be resistant to intruders' manipulation, such as chaff perturbation, and time-jittering evasion techniques. In this paper, we propose a new approach to not only detect stepping-stone intrusion, but also resist intruders' chaff attack evasion through TCP/IP packet cross-matching and random walk. Unlike other approaches which can just resist intruders' chaff attack to a certain degree, this approach can be immune to any number packets injected. The theory analysis and simulation results show that more injection packets, the higher the probability that the chaff attack is detected.","PeriodicalId":438655,"journal":{"name":"2016 IEEE 30th International Conference on Advanced Information Networking and Applications (AINA)","volume":"20 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129639354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kazuya Odagiri, Shogo Shimizu, N. Ishii, M. Takizawa
In the current Internet system, there are many problems using anonymity of the network communication such as personal information leaks and crimes using the Internet system. This is why TCP/IP protocol used in Internet system does not have the user identification information on the communication data, and it is difficult to supervise the user performing the above acts immediately. As a study for solving the above problem, there is the study of Policy Based Network Management (PBNM). This is the scheme for managing a whole Local Area Network (LAN) through communication control for every user. In this PBNM, two types of schemes exist. The first is the scheme for managing the whole LAN by locating the communication control mechanisms on the course between network servers and clients. The second is the scheme of managing the whole LAN by locating the communication control mechanisms on clients. As the second scheme, we have studied theoretically about the Destination Addressing Control System (DACS) Scheme. By applying this DACS Scheme to Internet system management, we will realize the policy-based Internet system management. As the second step of the second phase for the last goal, we examine the implementation method of the cloud type virtual PBNM which can be used by plural organizations in this paper.
{"title":"Examination of the Implementation Method of the Cloud Type Virtual Policy Based Network Management Scheme for the Common Use between Plural Organizations","authors":"Kazuya Odagiri, Shogo Shimizu, N. Ishii, M. Takizawa","doi":"10.1109/AINA.2016.13","DOIUrl":"https://doi.org/10.1109/AINA.2016.13","url":null,"abstract":"In the current Internet system, there are many problems using anonymity of the network communication such as personal information leaks and crimes using the Internet system. This is why TCP/IP protocol used in Internet system does not have the user identification information on the communication data, and it is difficult to supervise the user performing the above acts immediately. As a study for solving the above problem, there is the study of Policy Based Network Management (PBNM). This is the scheme for managing a whole Local Area Network (LAN) through communication control for every user. In this PBNM, two types of schemes exist. The first is the scheme for managing the whole LAN by locating the communication control mechanisms on the course between network servers and clients. The second is the scheme of managing the whole LAN by locating the communication control mechanisms on clients. As the second scheme, we have studied theoretically about the Destination Addressing Control System (DACS) Scheme. By applying this DACS Scheme to Internet system management, we will realize the policy-based Internet system management. As the second step of the second phase for the last goal, we examine the implementation method of the cloud type virtual PBNM which can be used by plural organizations in this paper.","PeriodicalId":438655,"journal":{"name":"2016 IEEE 30th International Conference on Advanced Information Networking and Applications (AINA)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134454233","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yi Liu, Shinji Sakamoto, Evjola Spaho, Keita Matsuo, L. Barolli, F. Xhafa
In this paper, we propose and evaluate a new fuzzy-based reliability system for Peer-to-Peer (P2P) Communications in JXTA-Overlay platform considering as a new parameter the sustained communication time. In our system, we considered four input parameters: Data Download Speed (DDS), Local Score (LS), Number of Interactions (NI) and Sustained Communication Time (SCT) to decide the Peer Reliability (PR). We evaluate the proposed system by computer simulations. The simulation results have shown that the proposed system has a good performance and can choose reliable peers to connect in JXTA-Overlay platform.
{"title":"A Fuzzy-Based Reliability System for JXTA-Overlay P2P Platform Considering as New Parameter Sustained Communication Time","authors":"Yi Liu, Shinji Sakamoto, Evjola Spaho, Keita Matsuo, L. Barolli, F. Xhafa","doi":"10.1109/AINA.2016.44","DOIUrl":"https://doi.org/10.1109/AINA.2016.44","url":null,"abstract":"In this paper, we propose and evaluate a new fuzzy-based reliability system for Peer-to-Peer (P2P) Communications in JXTA-Overlay platform considering as a new parameter the sustained communication time. In our system, we considered four input parameters: Data Download Speed (DDS), Local Score (LS), Number of Interactions (NI) and Sustained Communication Time (SCT) to decide the Peer Reliability (PR). We evaluate the proposed system by computer simulations. The simulation results have shown that the proposed system has a good performance and can choose reliable peers to connect in JXTA-Overlay platform.","PeriodicalId":438655,"journal":{"name":"2016 IEEE 30th International Conference on Advanced Information Networking and Applications (AINA)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132643336","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Healthcare data is quite rich and often contains human survival related information. Analyzing healthcare data is of prime importance particularly considering the immense potential of saving human life and improving quality of life. Furthermore, IoT revolution has redefined modern health care systems and management. IoT offers its greatest promise to deliver excellent progress in healthcare domain. In this talk, proactive healthcare analytics specifically for cardiac disease prevention will be discussed. Anomaly detection plays a prominent role in healthcare analytics. In fact, the anomalous events are to be accurately detected with low false negative alarms often under high noise (low SNR) condition. An exemplary case of smartphone based cardiac anomaly detection will be presented.
{"title":"IoT Healthcare Analytics: The Importance of Anomaly Detection","authors":"A. Ukil, S. Bandyopadhyay, Chetanya Puri, A. Pal","doi":"10.1109/AINA.2016.158","DOIUrl":"https://doi.org/10.1109/AINA.2016.158","url":null,"abstract":"Healthcare data is quite rich and often contains human survival related information. Analyzing healthcare data is of prime importance particularly considering the immense potential of saving human life and improving quality of life. Furthermore, IoT revolution has redefined modern health care systems and management. IoT offers its greatest promise to deliver excellent progress in healthcare domain. In this talk, proactive healthcare analytics specifically for cardiac disease prevention will be discussed. Anomaly detection plays a prominent role in healthcare analytics. In fact, the anomalous events are to be accurately detected with low false negative alarms often under high noise (low SNR) condition. An exemplary case of smartphone based cardiac anomaly detection will be presented.","PeriodicalId":438655,"journal":{"name":"2016 IEEE 30th International Conference on Advanced Information Networking and Applications (AINA)","volume":"107 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134467250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alexander Oberle, Pedro Larbig, R. Marx, F. Weber, D. Scheuermann, D. Fages, F. Thomas
Industrial espionage through complex cyber attacks such as Advanced Persistent Threats (APT) is an increasing risk in any business segment. Combining any available attack vector professional attackers infiltrate their targets progressively, e.g. through combining social engineering with technical hacking. The most relevant targets of APT are internal enterprise and production networks providing access to top-secret information. This work focuses on preventing Pass-the-Hash, one of the biggest and most long-standing security flaws present in enterprise domain networks. The introduced approach can be applied further to make password theft pointless for attackers in general, and is capable of extending network protocols, that are unprotected by themselves, with approved security mechanisms. The protocols do not need to be modified and already existing network services can stay untouched when integrating the solution into enterprise infrastructures.
{"title":"Preventing Pass-the-Hash and Similar Impersonation Attacks in Enterprise Infrastructures","authors":"Alexander Oberle, Pedro Larbig, R. Marx, F. Weber, D. Scheuermann, D. Fages, F. Thomas","doi":"10.1109/AINA.2016.101","DOIUrl":"https://doi.org/10.1109/AINA.2016.101","url":null,"abstract":"Industrial espionage through complex cyber attacks such as Advanced Persistent Threats (APT) is an increasing risk in any business segment. Combining any available attack vector professional attackers infiltrate their targets progressively, e.g. through combining social engineering with technical hacking. The most relevant targets of APT are internal enterprise and production networks providing access to top-secret information. This work focuses on preventing Pass-the-Hash, one of the biggest and most long-standing security flaws present in enterprise domain networks. The introduced approach can be applied further to make password theft pointless for attackers in general, and is capable of extending network protocols, that are unprotected by themselves, with approved security mechanisms. The protocols do not need to be modified and already existing network services can stay untouched when integrating the solution into enterprise infrastructures.","PeriodicalId":438655,"journal":{"name":"2016 IEEE 30th International Conference on Advanced Information Networking and Applications (AINA)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123823008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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