Pub Date : 2015-06-08DOI: 10.1109/CyberSA.2015.7166138
K. Dahri, Shakeel Rajput, S. Memon, L. D. Dhomeja
In this paper, an android based SAMS (Smart Activities Monitoring System) application for smart phone is proposed. This application is developed with the aim of increasing the national security in Pakistan. In last decade, various incidents including militant attacks and ransom-demands have been reported in which cell phones played a central role in communication between the culprits. The tracking of these criminals is very important and the government needs to adopt technologies to track mobile phones if they are being used for dangerous activities. In this paper, an android based application is presented which is designed and tested to track a suspect without his/her attention. This application tracks a smartphone by obtaining its current location and monitors a suspect remotely by retrieving information such as call logs, message logs etc. It also detects the face of the suspect and covertly captures the picture using cell phone camera and then sends it via multiple messages. Moreover, the monitoring user can also make calls to the phone which the culprit is using in stealth mode to hear the conversation happening in surroundings of the user without the knowledge of suspect.
{"title":"Smart Activities Monitoring System (SAMS) for security applications","authors":"K. Dahri, Shakeel Rajput, S. Memon, L. D. Dhomeja","doi":"10.1109/CyberSA.2015.7166138","DOIUrl":"https://doi.org/10.1109/CyberSA.2015.7166138","url":null,"abstract":"In this paper, an android based SAMS (Smart Activities Monitoring System) application for smart phone is proposed. This application is developed with the aim of increasing the national security in Pakistan. In last decade, various incidents including militant attacks and ransom-demands have been reported in which cell phones played a central role in communication between the culprits. The tracking of these criminals is very important and the government needs to adopt technologies to track mobile phones if they are being used for dangerous activities. In this paper, an android based application is presented which is designed and tested to track a suspect without his/her attention. This application tracks a smartphone by obtaining its current location and monitors a suspect remotely by retrieving information such as call logs, message logs etc. It also detects the face of the suspect and covertly captures the picture using cell phone camera and then sends it via multiple messages. Moreover, the monitoring user can also make calls to the phone which the culprit is using in stealth mode to hear the conversation happening in surroundings of the user without the knowledge of suspect.","PeriodicalId":432356,"journal":{"name":"2015 International Conference on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123885835","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}
Pub Date : 2015-06-08DOI: 10.1109/CyberSA.2015.7166114
Ruhul Amin, S. H. Islam, G. P. Biswas, M. Khan
To establish a secure connection between a mobile user and a remote server, this paper presents a session key agreement scheme through remote mutual authentication protocol by using mobile application software(MAS). We analyzed the security of our protocol informally, which confirms that the protocol is secure against all the relevant security attacks including off-line identity-password guessing attacks, user-server impersonation attacks, and insider attack. In addition, the widely accepted simulator tool AVISPA simulates the proposed protocol and confirms that the protocol is SAFE under the OFMC and CL-AtSe back-ends. Our protocol not only provide strong security against the relevant attacks, but it also achieves proper mutual authentication, user anonymity, known key secrecy and efficient password change operation. The performance comparison is also performed, which ensures that the protocol is efficient in terms of computation and communication costs.
{"title":"An efficient remote mutual authentication scheme using smart mobile phone over insecure networks","authors":"Ruhul Amin, S. H. Islam, G. P. Biswas, M. Khan","doi":"10.1109/CyberSA.2015.7166114","DOIUrl":"https://doi.org/10.1109/CyberSA.2015.7166114","url":null,"abstract":"To establish a secure connection between a mobile user and a remote server, this paper presents a session key agreement scheme through remote mutual authentication protocol by using mobile application software(MAS). We analyzed the security of our protocol informally, which confirms that the protocol is secure against all the relevant security attacks including off-line identity-password guessing attacks, user-server impersonation attacks, and insider attack. In addition, the widely accepted simulator tool AVISPA simulates the proposed protocol and confirms that the protocol is SAFE under the OFMC and CL-AtSe back-ends. Our protocol not only provide strong security against the relevant attacks, but it also achieves proper mutual authentication, user anonymity, known key secrecy and efficient password change operation. The performance comparison is also performed, which ensures that the protocol is efficient in terms of computation and communication costs.","PeriodicalId":432356,"journal":{"name":"2015 International Conference on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124443355","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}
Pub Date : 2015-06-08DOI: 10.1109/CyberSA.2015.7166136
C. Laing, Paul Vickers
In this multi-disciplinary project, we intend to explore the advantages of an information fusion system in which the infrastructure finds new ways to reflect upon its own state and new ways to express this state that provides a good fit to human communication and cognition processes. This interplay should then generate a better and more responsive humancomputer symbiosis. The outcomes of this project will help to develop context and content aware networks that are better able to extract meaning and understanding from network data and behaviour.
{"title":"Context informed intelligent information infrastructures for better situational awareness","authors":"C. Laing, Paul Vickers","doi":"10.1109/CyberSA.2015.7166136","DOIUrl":"https://doi.org/10.1109/CyberSA.2015.7166136","url":null,"abstract":"In this multi-disciplinary project, we intend to explore the advantages of an information fusion system in which the infrastructure finds new ways to reflect upon its own state and new ways to express this state that provides a good fit to human communication and cognition processes. This interplay should then generate a better and more responsive humancomputer symbiosis. The outcomes of this project will help to develop context and content aware networks that are better able to extract meaning and understanding from network data and behaviour.","PeriodicalId":432356,"journal":{"name":"2015 International Conference on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130437287","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}
Pub Date : 2015-06-08DOI: 10.1109/CyberSA.2015.7166133
Yegor Shovgenya, Florian Skopik, K. Theuerkauf
Renewable energy sources and widespread small-scale power generators change the structure of the power grid, where actual power consumers also temporarily become suppliers. Smart grids require continuous management of complex operations through utility providers, which leads to increasing interconnections and usage of ICT-enabled industrial control systems. Yet, often insufficiently implemented security mechanisms and the lack of appropriate monitoring solutions will make the smart grid vulnerable to malicious manipulations that may possibly result in severe power outages. Having a thorough understanding about the operational characteristics of smart grids, supported by clearly defined policies and processes, will be essential to establishing situational awareness, and thus, the first step for ensuring security and safety of the power supply.
{"title":"On demand for situational awareness for preventing attacks on the smart grid","authors":"Yegor Shovgenya, Florian Skopik, K. Theuerkauf","doi":"10.1109/CyberSA.2015.7166133","DOIUrl":"https://doi.org/10.1109/CyberSA.2015.7166133","url":null,"abstract":"Renewable energy sources and widespread small-scale power generators change the structure of the power grid, where actual power consumers also temporarily become suppliers. Smart grids require continuous management of complex operations through utility providers, which leads to increasing interconnections and usage of ICT-enabled industrial control systems. Yet, often insufficiently implemented security mechanisms and the lack of appropriate monitoring solutions will make the smart grid vulnerable to malicious manipulations that may possibly result in severe power outages. Having a thorough understanding about the operational characteristics of smart grids, supported by clearly defined policies and processes, will be essential to establishing situational awareness, and thus, the first step for ensuring security and safety of the power supply.","PeriodicalId":432356,"journal":{"name":"2015 International Conference on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127420868","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}
Pub Date : 2015-06-08DOI: 10.1109/CyberSA.2015.7166135
Dauda Adenusi, B. K. Alese, B. Kuboye, A. Thompson
This study designed and simulated cyber situation awareness model for gaining experience of cyberspace condition. This was with a view to timely detecting anomalous activities and taking proactive decision safeguard the cyberspace. The situation awareness model was modelled using Artificial Intelligence (AI) technique. The cyber situation perception sub-model of the situation awareness model was modelled using Artificial Neural Networks (ANN). The comprehension and projection submodels of the situation awareness model were modelled using Rule-Based Reasoning (RBR) techniques. The cyber situation perception sub-model was simulated in MATLAB 7.0 using standard intrusion dataset of KDD'99. The cyber situation perception sub-model was evaluated for threats detection accuracy using precision, recall and overall accuracy metrics. The simulation result obtained for the performance metrics showed that the cyber-situation sub-model of the cybersituation model better with increase in number of training data records. The cyber situation model designed was able to meet its overall goal of assisting network administrators to gain experience of cyberspace condition. The model was capable of sensing the cyberspace condition, perform analysis based on the sensed condition and predicting the near future condition of the cyberspace.
{"title":"Development of cyber situation awareness model","authors":"Dauda Adenusi, B. K. Alese, B. Kuboye, A. Thompson","doi":"10.1109/CyberSA.2015.7166135","DOIUrl":"https://doi.org/10.1109/CyberSA.2015.7166135","url":null,"abstract":"This study designed and simulated cyber situation awareness model for gaining experience of cyberspace condition. This was with a view to timely detecting anomalous activities and taking proactive decision safeguard the cyberspace. The situation awareness model was modelled using Artificial Intelligence (AI) technique. The cyber situation perception sub-model of the situation awareness model was modelled using Artificial Neural Networks (ANN). The comprehension and projection submodels of the situation awareness model were modelled using Rule-Based Reasoning (RBR) techniques. The cyber situation perception sub-model was simulated in MATLAB 7.0 using standard intrusion dataset of KDD'99. The cyber situation perception sub-model was evaluated for threats detection accuracy using precision, recall and overall accuracy metrics. The simulation result obtained for the performance metrics showed that the cyber-situation sub-model of the cybersituation model better with increase in number of training data records. The cyber situation model designed was able to meet its overall goal of assisting network administrators to gain experience of cyberspace condition. The model was capable of sensing the cyberspace condition, perform analysis based on the sensed condition and predicting the near future condition of the cyberspace.","PeriodicalId":432356,"journal":{"name":"2015 International Conference on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121606860","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}
Pub Date : 2015-06-08DOI: 10.1109/CyberSA.2015.7166122
Marcelo Paiva Fontenele, Lily Sun
The impact of cyber threats in society has led to a joint effort between public and private sector. Some of the major claims in cyber security initiatives involve attracting talented people and leveraging required skills. Thus, talent and knowledge management play a key role in selecting and maintaining the required expertise. However, a novel approach is required to integrate talent management across organisational partnerships in the dynamic cyber security domain. This work entails viewing cyber security as an information system in order to better understand the challenges of talent discovery and managing skills within its complex environment.
{"title":"Talent discovery for cyber security: An organisational perspective","authors":"Marcelo Paiva Fontenele, Lily Sun","doi":"10.1109/CyberSA.2015.7166122","DOIUrl":"https://doi.org/10.1109/CyberSA.2015.7166122","url":null,"abstract":"The impact of cyber threats in society has led to a joint effort between public and private sector. Some of the major claims in cyber security initiatives involve attracting talented people and leveraging required skills. Thus, talent and knowledge management play a key role in selecting and maintaining the required expertise. However, a novel approach is required to integrate talent management across organisational partnerships in the dynamic cyber security domain. This work entails viewing cyber security as an information system in order to better understand the challenges of talent discovery and managing skills within its complex environment.","PeriodicalId":432356,"journal":{"name":"2015 International Conference on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA)","volume":"8 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121016813","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}
Pub Date : 2015-06-08DOI: 10.1109/CyberSA.2015.7166117
Markus Wurzenberger, Florian Skopik, Giuseppe Settanni, Roman Fiedler
Today ICT networks are the economy's vital backbone. While their complexity continuously evolves, sophisticated and targeted cyber attacks such as Advanced Persistent Threats (APTs) become increasingly fatal for organizations. Numerous highly developed Intrusion Detection Systems (IDSs) promise to detect certain characteristics of APTs, but no mechanism which allows to rate, compare and evaluate them with respect to specific customer infrastructures is currently available. In this paper, we present BAESE, a system which enables vendor independent and objective rating and comparison of IDSs based on small sets of customer network data.
{"title":"Beyond gut instincts: Understanding, rating and comparing self-learning IDSs","authors":"Markus Wurzenberger, Florian Skopik, Giuseppe Settanni, Roman Fiedler","doi":"10.1109/CyberSA.2015.7166117","DOIUrl":"https://doi.org/10.1109/CyberSA.2015.7166117","url":null,"abstract":"Today ICT networks are the economy's vital backbone. While their complexity continuously evolves, sophisticated and targeted cyber attacks such as Advanced Persistent Threats (APTs) become increasingly fatal for organizations. Numerous highly developed Intrusion Detection Systems (IDSs) promise to detect certain characteristics of APTs, but no mechanism which allows to rate, compare and evaluate them with respect to specific customer infrastructures is currently available. In this paper, we present BAESE, a system which enables vendor independent and objective rating and comparison of IDSs based on small sets of customer network data.","PeriodicalId":432356,"journal":{"name":"2015 International Conference on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115473140","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}
Pub Date : 2015-06-08DOI: 10.1109/CyberSA.2015.7166115
Radu S. Pirscoveanu, Steven S. Hansen, Thor M. T. Larsen, Matija Stevanovic, J. Pedersen, A. Czech
Malicious software has become a major threat to modern society, not only due to the increased complexity of the malware itself but also due to the exponential increase of new malware each day. This study tackles the problem of analyzing and classifying a high amount of malware in a scalable and automatized manner. We have developed a distributed malware testing environment by extending Cuckoo Sandbox that was used to test an extensive number of malware samples and trace their behavioral data. The extracted data was used for the development of a novel type classification approach based on supervised machine learning. The proposed classification approach employs a novel combination of features that achieves a high classification rate with a weighted average AUC value of 0.98 using Random Forests classifier. The approach has been extensively tested on a total of 42,000 malware samples. Based on the above results it is believed that the developed system can be used to pre-filter novel from known malware in a future malware analysis system.
{"title":"Analysis of Malware behavior: Type classification using machine learning","authors":"Radu S. Pirscoveanu, Steven S. Hansen, Thor M. T. Larsen, Matija Stevanovic, J. Pedersen, A. Czech","doi":"10.1109/CyberSA.2015.7166115","DOIUrl":"https://doi.org/10.1109/CyberSA.2015.7166115","url":null,"abstract":"Malicious software has become a major threat to modern society, not only due to the increased complexity of the malware itself but also due to the exponential increase of new malware each day. This study tackles the problem of analyzing and classifying a high amount of malware in a scalable and automatized manner. We have developed a distributed malware testing environment by extending Cuckoo Sandbox that was used to test an extensive number of malware samples and trace their behavioral data. The extracted data was used for the development of a novel type classification approach based on supervised machine learning. The proposed classification approach employs a novel combination of features that achieves a high classification rate with a weighted average AUC value of 0.98 using Random Forests classifier. The approach has been extensively tested on a total of 42,000 malware samples. Based on the above results it is believed that the developed system can be used to pre-filter novel from known malware in a future malware analysis system.","PeriodicalId":432356,"journal":{"name":"2015 International Conference on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129614130","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}
Pub Date : 2015-06-08DOI: 10.1109/CyberSA.2015.7166129
Therese Bjerkestrand, D. Tsaptsinos, E. Pfluegel
Intrusion detection is concerned with monitoring and analysing events occurring in a computer system in order to discover potential malicious activity. Data mining, which is part of the procedure of knowledge discovery in databases, is the process of analysing the collected data to find patterns or correlations. As the amount of data collected, store and processed only increases, so does the significance and importance of intrusion detection and data mining. A dataset that has been particularly exposed to research is the dataset used for the Third International Knowledge Discovery and Data Mining Tools competition, KDD99. The KDD99 dataset has been used to identify what data mining techniques relate to certain attack and employed to demonstrate that decision trees are more efficient than the Naïve Bayes model when it comes to detecting new attacks. When it comes to detecting network intrusions, the C4.5 algorithm performs better than SVM. The aim of our research is to evaluate and compare the usage of various feature selection and reduction algorithms against publicly available datasets. In this contribution, the focus is on feature selection and reduction algorithms. Three feature selection algorithms, consisting of an attribute evaluator and a test method, have been used. Initial results indicate that the performance of the classifier is unaffected by reducing the number of attributes.
{"title":"An evaluation of feature selection and reduction algorithms for network IDS data","authors":"Therese Bjerkestrand, D. Tsaptsinos, E. Pfluegel","doi":"10.1109/CyberSA.2015.7166129","DOIUrl":"https://doi.org/10.1109/CyberSA.2015.7166129","url":null,"abstract":"Intrusion detection is concerned with monitoring and analysing events occurring in a computer system in order to discover potential malicious activity. Data mining, which is part of the procedure of knowledge discovery in databases, is the process of analysing the collected data to find patterns or correlations. As the amount of data collected, store and processed only increases, so does the significance and importance of intrusion detection and data mining. A dataset that has been particularly exposed to research is the dataset used for the Third International Knowledge Discovery and Data Mining Tools competition, KDD99. The KDD99 dataset has been used to identify what data mining techniques relate to certain attack and employed to demonstrate that decision trees are more efficient than the Naïve Bayes model when it comes to detecting new attacks. When it comes to detecting network intrusions, the C4.5 algorithm performs better than SVM. The aim of our research is to evaluate and compare the usage of various feature selection and reduction algorithms against publicly available datasets. In this contribution, the focus is on feature selection and reduction algorithms. Three feature selection algorithms, consisting of an attribute evaluator and a test method, have been used. Initial results indicate that the performance of the classifier is unaffected by reducing the number of attributes.","PeriodicalId":432356,"journal":{"name":"2015 International Conference on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121270430","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}
Pub Date : 2015-06-08DOI: 10.1109/CyberSA.2015.7166124
S. Memon, Sorath Mahar, L. D. Dhomeja, Farman Pirzado
Advanced and rapid developments in the field of computer and wireless technologies makes easy and possible to be a direct part of electronic media. Social media is an attractive, informative, useful, and approachable way to get information. In last few years, there is an increase observed in the smartphone, smart tablet, and wireless broadband market in Pakistan. It is because of the popularity of social media, its access, and usage in most of citizens. It is a positive prospect for the country, however; there are many issues are rising with the usage of social networking sites. In this paper, the social media technologies were and reasons behind the increase in usage of social media Pakistani netizens (Internet users) is discussed. Moreover, the challenges regarding social media such as cyber-crimes, cyber blackmailing, ethics, security and identity protection in Pakistan is discussed in this Paper.
{"title":"Prospects and challenges for social media in Pakistan","authors":"S. Memon, Sorath Mahar, L. D. Dhomeja, Farman Pirzado","doi":"10.1109/CyberSA.2015.7166124","DOIUrl":"https://doi.org/10.1109/CyberSA.2015.7166124","url":null,"abstract":"Advanced and rapid developments in the field of computer and wireless technologies makes easy and possible to be a direct part of electronic media. Social media is an attractive, informative, useful, and approachable way to get information. In last few years, there is an increase observed in the smartphone, smart tablet, and wireless broadband market in Pakistan. It is because of the popularity of social media, its access, and usage in most of citizens. It is a positive prospect for the country, however; there are many issues are rising with the usage of social networking sites. In this paper, the social media technologies were and reasons behind the increase in usage of social media Pakistani netizens (Internet users) is discussed. Moreover, the challenges regarding social media such as cyber-crimes, cyber blackmailing, ethics, security and identity protection in Pakistan is discussed in this Paper.","PeriodicalId":432356,"journal":{"name":"2015 International Conference on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125238902","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：