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S.U. Malik
Cybernetica AS, 12618 Tallinn, Estonia

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Journal article
Published: 20 July 2021 in Sensors
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With the advent of smart health, smart cities, and smart grids, the amount of data has grown swiftly. When the collected data is published for valuable information mining, privacy turns out to be a key matter due to the presence of sensitive information. Such sensitive information comprises either a single sensitive attribute (an individual has only one sensitive attribute) or multiple sensitive attributes (an individual can have multiple sensitive attributes). Anonymization of data sets with multiple sensitive attributes presents some unique problems due to the correlation among these attributes. Artificial intelligence techniques can help the data publishers in anonymizing such data. To the best of our knowledge, no fuzzy logic-based privacy model has been proposed until now for privacy preservation of multiple sensitive attributes. In this paper, we propose a novel privacy preserving model F-Classify that uses fuzzy logic for the classification of quasi-identifier and multiple sensitive attributes. Classes are defined based on defined rules, and every tuple is assigned to its class according to attribute value. The working of the F-Classify Algorithm is also verified using HLPN. A wide range of experiments on healthcare data sets acknowledged that F-Classify surpasses its counterparts in terms of privacy and utility. Being based on artificial intelligence, it has a lower execution time than other approaches.

ACS Style

Hasina Attaullah; Adeel Anjum; Tehsin Kanwal; Saif Malik; Alia Asheralieva; Hassan Malik; Ahmed Zoha; Kamran Arshad; Muhammad Imran. F-Classify: Fuzzy Rule Based Classification Method for Privacy Preservation of Multiple Sensitive Attributes. Sensors 2021, 21, 4933 .

AMA Style

Hasina Attaullah, Adeel Anjum, Tehsin Kanwal, Saif Malik, Alia Asheralieva, Hassan Malik, Ahmed Zoha, Kamran Arshad, Muhammad Imran. F-Classify: Fuzzy Rule Based Classification Method for Privacy Preservation of Multiple Sensitive Attributes. Sensors. 2021; 21 (14):4933.

Chicago/Turabian Style

Hasina Attaullah; Adeel Anjum; Tehsin Kanwal; Saif Malik; Alia Asheralieva; Hassan Malik; Ahmed Zoha; Kamran Arshad; Muhammad Imran. 2021. "F-Classify: Fuzzy Rule Based Classification Method for Privacy Preservation of Multiple Sensitive Attributes." Sensors 21, no. 14: 4933.

Journal article
Published: 11 May 2020 in IEEE Consumer Electronics Magazine
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We witness an explosive growth in the volume, velocity, and variety of the data available on the Internet. Such ‘Data Explosion’ is mostly caused by the mobile devices, sensors, actuators, and social networks. Despite significant technological advancements, the users quality of experience are barely met. The ever-increasing demands of users related to high storage, fast computation, and processing has led towards the innovation of 5G technology. In this article, we conducted a study to highlight the significance of 5G (compared to the existing standards) and its effect on the user perceived quality of experience attributes. We have constructed a comprehensive taxonomy of quality of experience attributes, discussed their importance and how they ultimately lead towards the good quality of service. Moreover, a small experiment is conducted to demonstrate the effect of 5G on certain quality of experience attributes. Results revealed positive impact of 5G on certain experimented quality of experience attributes.

ACS Style

Saif Ur Rehman Malik. Moving Toward 5G: Significance, Differences, and Impact on Quality of Experience. IEEE Consumer Electronics Magazine 2020, 9, 9 -14.

AMA Style

Saif Ur Rehman Malik. Moving Toward 5G: Significance, Differences, and Impact on Quality of Experience. IEEE Consumer Electronics Magazine. 2020; 9 (6):9-14.

Chicago/Turabian Style

Saif Ur Rehman Malik. 2020. "Moving Toward 5G: Significance, Differences, and Impact on Quality of Experience." IEEE Consumer Electronics Magazine 9, no. 6: 9-14.

Special issue paper
Published: 12 April 2020 in Software: Practice and Experience
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Fog computing is a promising technique to reduce the latency and power consumption issues of the Internet of Things (IoT) ecosystem by enabling storage and computational resource close to the end‐user devices with additional benefits such as improved execution time and processing. However, with an increase in IoT devices, the resource allocation and job scheduling became a complicated and cumbersome task due to limited and heterogeneous resources along with the locality restriction in such computing environment. Therefore, this paper proposes a cache‐based approach for efficient resource allocation in fog computing environment, while maintaining the quality of service. The proposed algorithm is realized using iFogSim simulator and a comprehensive comparison is presented with the traditional First Come First Served and Shortest Job First policies. The performance evaluation revealed that with the proposed scheme the execution time, latency, processing delays and power consumption decreased by 38%, 11.1%, 6%, and 17.8%, respectively, as compared to those of the traditional schemes.

ACS Style

Osama Amir Khan; Saif U. R. Malik; Faizan M. Baig; Saif Ul Islam; Haris Pervaiz; Hassan Malik; Syed Hassan Ahmed. A cache-based approach toward improved scheduling in fog computing. Software: Practice and Experience 2020, 1 .

AMA Style

Osama Amir Khan, Saif U. R. Malik, Faizan M. Baig, Saif Ul Islam, Haris Pervaiz, Hassan Malik, Syed Hassan Ahmed. A cache-based approach toward improved scheduling in fog computing. Software: Practice and Experience. 2020; ():1.

Chicago/Turabian Style

Osama Amir Khan; Saif U. R. Malik; Faizan M. Baig; Saif Ul Islam; Haris Pervaiz; Hassan Malik; Syed Hassan Ahmed. 2020. "A cache-based approach toward improved scheduling in fog computing." Software: Practice and Experience , no. : 1.

Journal article
Published: 28 January 2020 in Wireless Communications and Mobile Computing
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Privacy preserving data publishing (PPDP) refers to the releasing of anonymized data for the purpose of research and analysis. A considerable amount of research work exists for the publication of data, having a single sensitive attribute. The practical scenarios in PPDP with multiple sensitive attributes (MSAs) have not yet attracted much attention of researchers. Although a recently proposed technique (p, k)-Angelization provided a novel solution, in this regard, where one-to-one correspondence between the buckets in the generalized table (GT) and the sensitive table (ST) has been used. However, we have investigated a possibility of privacy leakage through MSA correlation among linkable sensitive buckets and named it as “fingerprint correlation fcorr attack.” Mitigating that in this paper, we propose an improved solution “c,k-anonymization” algorithm. The proposed solution thwarts the fcorr attack using some privacy measures and improves the one-to-one correspondence to one-to-many correspondence between the buckets in GT and ST which further reduces the privacy risk with increased utility in GT. We have formally modelled and analysed the attack and the proposed solution. Experiments on the real-world datasets prove the outperformance of the proposed solution as compared to its counterpart.

ACS Style

Razaullah Khan; Xiaofeng Tao; Adeel Anjum; Haider Sajjad; Saif Ur Rehman Malik; Abid Khan; Fatemeh Amiri. Privacy Preserving for Multiple Sensitive Attributes against Fingerprint Correlation Attack Satisfying c-Diversity. Wireless Communications and Mobile Computing 2020, 2020, 1 -18.

AMA Style

Razaullah Khan, Xiaofeng Tao, Adeel Anjum, Haider Sajjad, Saif Ur Rehman Malik, Abid Khan, Fatemeh Amiri. Privacy Preserving for Multiple Sensitive Attributes against Fingerprint Correlation Attack Satisfying c-Diversity. Wireless Communications and Mobile Computing. 2020; 2020 ():1-18.

Chicago/Turabian Style

Razaullah Khan; Xiaofeng Tao; Adeel Anjum; Haider Sajjad; Saif Ur Rehman Malik; Abid Khan; Fatemeh Amiri. 2020. "Privacy Preserving for Multiple Sensitive Attributes against Fingerprint Correlation Attack Satisfying c-Diversity." Wireless Communications and Mobile Computing 2020, no. : 1-18.

Earlycite article
Published: 16 October 2019 in Business Process Management Journal
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Purpose Business process (BP) reengineering is defined as reinventing BPs either structurally or technically to achieve dramatic improvements in performance. In any business process reengineering (BPR) project, process modeling is used to reason about problems found in existing (as-is) process and helps to design target (to-be) process. BP model notation is a widely accepted standard for process modeling. “Expressiveness” and “missing formal semantics” are two problems reported to its modeling practices. In existing studies, solutions to these problems are also proposed but still have certain limitations. The paper aims to discuss this issue. Design/methodology/approach In proposed methodology, a meta-model is formally defined that is composed of commonly used modeling elements and their well-formedness rules to check for syntactic and structural correctness of process models. Proposed solution also check semantics of process models and allows to compare as-is and to-be process models for gap identification which is another important aspect of BPR. To achieve the first goal, Z specification is used to provide formal specifications of modeling constructs and their rules and Z3 (an SMT solver) is used for comparisons and verifying properties. Findings Proposed method addresses both “expressiveness” and “missing formal semantics” of BPR models. The results of its evaluation clearly indicate that using formally specified meta-model, BPR model is syntactically and structurally correct. Moreover, formal modeling of BPs in Z3 helped to compare processes and to check control flow properties. Research limitations/implications Although the proposed method is tested on an example that is widely used in BPR literature, the example is only covering modeling elements which are part of the proposed subset and are reported in literature as frequently used modeling elements. A separate detailed study is required to test it on more complex systems. Practical implications Specifying process models using Z specification and Z3 solver requires certain expertise. Originality/value The proposed method adds value to BPR body of knowledge as it proposes a method to ensure structural and syntactic correctness of models, highlighting the importance of verifying run time properties and providing a direction toward comparing process models for gap analysis.

ACS Style

Junaid Haseeb; Naveed Ahmad; Saif Ur Rehman Malik; Adeel Anjum. Application of formal methods to modelling and analysis aspects of business process reengineering. Business Process Management Journal 2019, 26, 548 -569.

AMA Style

Junaid Haseeb, Naveed Ahmad, Saif Ur Rehman Malik, Adeel Anjum. Application of formal methods to modelling and analysis aspects of business process reengineering. Business Process Management Journal. 2019; 26 (2):548-569.

Chicago/Turabian Style

Junaid Haseeb; Naveed Ahmad; Saif Ur Rehman Malik; Adeel Anjum. 2019. "Application of formal methods to modelling and analysis aspects of business process reengineering." Business Process Management Journal 26, no. 2: 548-569.

Journal article
Published: 05 July 2019 in Computers & Security
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Past and ongoing decades have witnessed significant uplift in data generation due to ever growing sources of data. Collection and aggradation of such huge data have triggered serious concerns on privacy of data-owners’ sensitive information. Catering this, several existing anonymization models proffer privacy-preserving data collection. However, the models put-forth either strict or unrealistic assumptions regarding leaders’ selection (the concept of first and last leaders in data collection process). In this paper, we have identified and formally defined a privacy attack, Leader Collusion Attack (LCA); where first and second leaders may collude to breech individuals’ privacy during data collection process. In this regard, we have proposed a novel k-anonymity based dynamic data collection protocol (presented single leader election) to mitigate LCA. Moreover, we have formally modelled and analysed the proposed protocol through HLPNs and demonstrated the mitigation of LCA. Experimentations on real-world datasets advocate the outperformance of our protocol over existing model in terms of better utility and privacy levels.

ACS Style

Haider Sajjad; Tehsin Kanwal; Adeel Anjum; Saif Ur Rehman Malik; Ahmed Khan; Abid Khan; Umar Manzoor. An efficient privacy preserving protocol for dynamic continuous data collection. Computers & Security 2019, 86, 358 -371.

AMA Style

Haider Sajjad, Tehsin Kanwal, Adeel Anjum, Saif Ur Rehman Malik, Ahmed Khan, Abid Khan, Umar Manzoor. An efficient privacy preserving protocol for dynamic continuous data collection. Computers & Security. 2019; 86 ():358-371.

Chicago/Turabian Style

Haider Sajjad; Tehsin Kanwal; Adeel Anjum; Saif Ur Rehman Malik; Ahmed Khan; Abid Khan; Umar Manzoor. 2019. "An efficient privacy preserving protocol for dynamic continuous data collection." Computers & Security 86, no. : 358-371.

Research article
Published: 21 June 2019 in International Journal of Distributed Sensor Networks
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State-of-the-art progress in cloud computing encouraged the healthcare organizations to outsource the management of electronic health records to cloud service providers using hybrid cloud. A hybrid cloud is an infrastructure consisting of a private cloud (managed by the organization) and a public cloud (managed by the cloud service provider). The use of hybrid cloud enables electronic health records to be exchanged between medical institutions and supports multipurpose usage of electronic health records. Along with the benefits, cloud-based electronic health records also raise the problems of security and privacy specifically in terms of electronic health records access. A comprehensive and exploratory analysis of privacy-preserving solutions revealed that most current systems do not support fine-grained access control or consider additional factors such as privacy preservation and relationship semantics. In this article, we investigated the need of a privacy-aware fine-grained access control model for the hybrid cloud. We propose a privacy-aware relationship semantics–based XACML access control model that performs hybrid relationship and attribute-based access control using extensible access control markup language. The proposed approach supports fine-grained relation-based access control with state-of-the-art privacy mechanism named Anatomy for enhanced multipurpose electronic health records usage. The proposed (privacy-aware relationship semantics–based XACML access control model) model provides and maintains an efficient privacy versus utility trade-off. We formally verify the proposed model (privacy-aware relationship semantics–based XACML access control model) and implemented to check its effectiveness in terms of privacy-aware electronic health records access and multipurpose utilization. Experimental results show that in the proposed (privacy-aware relationship semantics–based XACML access control model) model, access policies based on relationships and electronic health records anonymization can perform well in terms of access policy response time and space storage.

ACS Style

Tehsin Kanwal; Ather Abdul Jabbar; Adeel Anjum; Saif Ur Malik; Abid Khan; Naveed Ahmad; Umar Manzoor; Muhammad Naeem Shahzad; Muhammad A Balubaid. Privacy-aware relationship semantics–based XACML access control model for electronic health records in hybrid cloud. International Journal of Distributed Sensor Networks 2019, 15, 1 .

AMA Style

Tehsin Kanwal, Ather Abdul Jabbar, Adeel Anjum, Saif Ur Malik, Abid Khan, Naveed Ahmad, Umar Manzoor, Muhammad Naeem Shahzad, Muhammad A Balubaid. Privacy-aware relationship semantics–based XACML access control model for electronic health records in hybrid cloud. International Journal of Distributed Sensor Networks. 2019; 15 (6):1.

Chicago/Turabian Style

Tehsin Kanwal; Ather Abdul Jabbar; Adeel Anjum; Saif Ur Malik; Abid Khan; Naveed Ahmad; Umar Manzoor; Muhammad Naeem Shahzad; Muhammad A Balubaid. 2019. "Privacy-aware relationship semantics–based XACML access control model for electronic health records in hybrid cloud." International Journal of Distributed Sensor Networks 15, no. 6: 1.

Journal article
Published: 06 March 2019 in Information Sciences
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Preserved privacy and enhanced utility are two competing requirements in data publishing. For maintaining a trade-off between the two; a plethora of research work exist in 1:1 scenario (each individual has a single record) with a single sensitive attribute (SA). However, some practical scenarios i.e., data having 1:M records (an individual can have multiple records) with multiple sensitive attributes (MSAs), have been relatively understudied. In our current interconnected and digitalized society, the capability to deal with such scenarios is increasingly important due to the ever-increasing sources of data that could be drawn together and infer one's information (e.g. profile and lifestyle) and consequently, compromising one's privacy. In this paper, we present a new type of attack on 1:M records with MSAs, coined as MSAs generalization correlation attacks and perform formal modeling and analysis of these attacks. Then, we propose a privacy-preserving technique “(p, l)-Angelization” for 1:M–MSAs data publication. Extensive experiments over real-world datasets advocate the outperformance of our technique over its counterparts.

ACS Style

Tehsin Kanwal; Sayed Ali Asjad Shaukat; Adeel Anjum; Saif Ur Rehman Malik; Kim-Kwang Raymond Choo; Abid Khan; Naveed Ahmad; Mansoor Ahmad; Samee U. Khan. Privacy-preserving model and generalization correlation attacks for 1:M data with multiple sensitive attributes. Information Sciences 2019, 488, 238 -256.

AMA Style

Tehsin Kanwal, Sayed Ali Asjad Shaukat, Adeel Anjum, Saif Ur Rehman Malik, Kim-Kwang Raymond Choo, Abid Khan, Naveed Ahmad, Mansoor Ahmad, Samee U. Khan. Privacy-preserving model and generalization correlation attacks for 1:M data with multiple sensitive attributes. Information Sciences. 2019; 488 ():238-256.

Chicago/Turabian Style

Tehsin Kanwal; Sayed Ali Asjad Shaukat; Adeel Anjum; Saif Ur Rehman Malik; Kim-Kwang Raymond Choo; Abid Khan; Naveed Ahmad; Mansoor Ahmad; Samee U. Khan. 2019. "Privacy-preserving model and generalization correlation attacks for 1:M data with multiple sensitive attributes." Information Sciences 488, no. : 238-256.

Journal article
Published: 04 March 2019 in EURASIP Journal on Wireless Communications and Networking
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Recent years have seen a significant growth in Internet of Things (IoT) technology consisting of a large number of devices embedded with sensors and deployed to perform monitoring and actuation tasks. The IoT devices collect large volumes of data that is usually uploaded to cloud to perform analytics and predictions. One of the main challenges in IoT is the transportation of large-scale data collected over a period of time at a remote site. Cellular networks are already facing explosive growth of mobile data traffic due to the proliferation of smart devices and traffic-intensive applications. An alternate solution is to perform the data offloading, where a portion of data can be offloaded from primary links and transferred using opportunistic terminal-to-terminal (T2T) network that relies on direct communication between mobile users, without any need for an infrastructure backbone. However, such approach may lead to data loss and delay if dynamics of time-varying topology and mobility of nodes is not taken care of. To address this challenge, we propose three prediction-based offloading schemes that exploit the mobility patterns and temporal contacts of nodes to predict future data transfer opportunities. We have utilized the High-level Petri Nets to model and formally analyzed the communication processes of the proposed schemes. The new symbolic model verifier (NuSMV) has been employed for the verification of the three schemes against the identified constraints. The verification results affirm the correctness and scalability of the models. The protocols are evaluated with performance metrics, such as the delivery ratio, latency, and overhead. Our results indicate significant improvement in performance compared to existing approaches.

ACS Style

Ankan Ghosh; Osman Khalid; Rao Naveed Bin Rais; Amjad Rehman; Saif Ur Rehman Malik; Imran A. Khan. Data offloading in IoT environments: modeling, analysis, and verification. EURASIP Journal on Wireless Communications and Networking 2019, 2019, 53 .

AMA Style

Ankan Ghosh, Osman Khalid, Rao Naveed Bin Rais, Amjad Rehman, Saif Ur Rehman Malik, Imran A. Khan. Data offloading in IoT environments: modeling, analysis, and verification. EURASIP Journal on Wireless Communications and Networking. 2019; 2019 (1):53.

Chicago/Turabian Style

Ankan Ghosh; Osman Khalid; Rao Naveed Bin Rais; Amjad Rehman; Saif Ur Rehman Malik; Imran A. Khan. 2019. "Data offloading in IoT environments: modeling, analysis, and verification." EURASIP Journal on Wireless Communications and Networking 2019, no. 1: 53.

Journal article
Published: 14 February 2019 in IEEE Transactions on Cloud Computing
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Data centers (DC) host a large number of servers, computing devices and computing infrastructure, and hence incur significant amount of electricity / energy. This also results in high amount of heat produced, which if not addressed can lead to overheating of computing devices in the DC. In addition, temperature mismanagement can lead to thermal imbalance within the DC environment, which may result in the creation of hotspots. The energy consumed during the life of a hotspot is greater than the energy saved during computation. Hence, the thermal imbalance impacts on the efficiency of the cooling mechanism installed inside the DC, and the consequence is high energy consumption. One popular strategy to minimize energy consumption is to optimize resource allocation within the DC. However, existing scheduling strategies do not consider the ambient effect of the surrounding nodes at the time of job allocation. Moreover, thermal-aware resource scheduling as an optimization problem is a topic that is relatively understudied in the literature. Therefore, in this research, we propose a novel Game-based Thermal-Aware Resource Allocation (GTARA) strategy to reduce the thermal imbalance within the DC. Specifically, we use cooperative game theory with a Nash-bargaining solution concept to model the resource allocation as an optimization problem, where user jobs are assigned to the computing nodes based on their thermal profiles and their potential effect on the surrounding nodes. This allows us to improve thermal balance and avoid hotspots. We then demonstrate the effectiveness of GTARA in comparison to TACS (Thermal-aware Control Strategy), TASA (Thermal-aware Scheduling Algorithm) and FCFS (First-Come First-Served), in terms of minimizing thermal imbalance and hotspots.

ACS Style

Saeed Akbar; Saif Ur Rehman Malik; Samee U. Khan; Raymond Choo; Adeel Anjum; Naveed Ahmad. A Game-based Thermal-aware Resource Allocation Strategy for Data Centers. IEEE Transactions on Cloud Computing 2019, 1 -1.

AMA Style

Saeed Akbar, Saif Ur Rehman Malik, Samee U. Khan, Raymond Choo, Adeel Anjum, Naveed Ahmad. A Game-based Thermal-aware Resource Allocation Strategy for Data Centers. IEEE Transactions on Cloud Computing. 2019; (99):1-1.

Chicago/Turabian Style

Saeed Akbar; Saif Ur Rehman Malik; Samee U. Khan; Raymond Choo; Adeel Anjum; Naveed Ahmad. 2019. "A Game-based Thermal-aware Resource Allocation Strategy for Data Centers." IEEE Transactions on Cloud Computing , no. 99: 1-1.

Journal article
Published: 30 November 2018 in Sustainable Cities and Society
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Privacy-preserving data publishing (PPDP) aims at providing an anonymized view of a private microdata to the recipients, e.g., researchers, pharmaceutical companies etc. This private data contains sensitive information about individuals that needs to be protected. In the literature, it is generally assumed that there exists a single record for one individual in any given microdata (1:1 dataset). However, more practically, there are many instances in which an individual can have multiple records in microdata (termed as 1: M datasets). Several techniques have been proposed for the 1:1 microdata but, a few researchers paid attention towards 1:M microdata problems, that perhaps led to new privacy disclosures. A novel privacy model (k, l)-diversity was proposed to cater such disclosure risks and based on this model, an algorithm named 1: M generalization was proposed. Although it was efficient than several other techniques; still has a drawback of huge information loss. In this paper, we propose a hybrid approach named as l-anatomy for 1: M microdata and prove that l-anatomy ensures the privacy of given individuals. Also, experiments performed on two real-world datasets (namely INFORMS and YOUTUBE) reveal that the proposed scheme exhibits higher efficiency and effectiveness as compared to its counterpart.

ACS Style

Adeel Anjum; Nayma Farooq; Saif Ur Rehman Malik; Abid Khan; Mansoor Ahmed; Moneeb Gohar. An effective privacy preserving mechanism for 1: M microdata with high utility. Sustainable Cities and Society 2018, 45, 213 .

AMA Style

Adeel Anjum, Nayma Farooq, Saif Ur Rehman Malik, Abid Khan, Mansoor Ahmed, Moneeb Gohar. An effective privacy preserving mechanism for 1: M microdata with high utility. Sustainable Cities and Society. 2018; 45 ():213.

Chicago/Turabian Style

Adeel Anjum; Nayma Farooq; Saif Ur Rehman Malik; Abid Khan; Mansoor Ahmed; Moneeb Gohar. 2018. "An effective privacy preserving mechanism for 1: M microdata with high utility." Sustainable Cities and Society 45, no. : 213.

Journal article
Published: 14 November 2018 in Future Generation Computer Systems
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The design philosophy of Open Shortest Path First, which is a widely deployed adaptive link state routing protocol, is to limit bandwidth requirements and attain quick recovery from failure (speed of convergence). The placement of the designated router has significant importance in convergence time. In literature, researchers have proposed approaches to improve convergence time. However, existing approaches reported hardware overhead and network congestion. Therefore, in this paper, the effect of the designated router’s placement on overall convergence time of an area is analysed. In the said perspective, the use of network centrality metrics for an optimal placement of designated router is proposed, which in return will reduce convergence time. The commonly used centrality metrics are betweenness centrality, closeness centrality, and degree centrality. This study employs the aforesaid centrality metrics for optimal placement of designated router. To demonstrate the effectiveness of using centrality metrics towards reducing convergence time, a tool named “Topology Analyzer” is developed to simulate the OSPF convergence process. After simulation, the results revealed a convergence time reduction of 19% by selecting a designated router using centrality metrics. Furthermore, this work is evaluated by comparing the convergence time of traditional priority based designated router election process of the OSPF routing protocol.

ACS Style

Muhammad Waqas; Saif Ur Rehman Malik; Saeed Akbar; Adeel Anjum; Naveed Ahmad. Convergence time analysis of OSPF routing protocol using social network metrics. Future Generation Computer Systems 2018, 94, 62 -71.

AMA Style

Muhammad Waqas, Saif Ur Rehman Malik, Saeed Akbar, Adeel Anjum, Naveed Ahmad. Convergence time analysis of OSPF routing protocol using social network metrics. Future Generation Computer Systems. 2018; 94 ():62-71.

Chicago/Turabian Style

Muhammad Waqas; Saif Ur Rehman Malik; Saeed Akbar; Adeel Anjum; Naveed Ahmad. 2018. "Convergence time analysis of OSPF routing protocol using social network metrics." Future Generation Computer Systems 94, no. : 62-71.

Journal article
Published: 01 September 2018 in Sustainable Computing: Informatics and Systems
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ACS Style

Rahmat Ullah; Naveed Ahmad; Saif Ur Rehman Malik; Saeed Akbar; Adeel Anjum. Simulator for modeling, analysis, and visualizations of thermal status in data centers. Sustainable Computing: Informatics and Systems 2018, 19, 324 -340.

AMA Style

Rahmat Ullah, Naveed Ahmad, Saif Ur Rehman Malik, Saeed Akbar, Adeel Anjum. Simulator for modeling, analysis, and visualizations of thermal status in data centers. Sustainable Computing: Informatics and Systems. 2018; 19 ():324-340.

Chicago/Turabian Style

Rahmat Ullah; Naveed Ahmad; Saif Ur Rehman Malik; Saeed Akbar; Adeel Anjum. 2018. "Simulator for modeling, analysis, and visualizations of thermal status in data centers." Sustainable Computing: Informatics and Systems 19, no. : 324-340.

Journal article
Published: 07 May 2018 in IEEE Access
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In data publishing, privacy and utility are essential for data owners and users respectively, which cannot coexist well. This incompatibility puts the data privacy researchers under an obligation to find newer and reliable privacy preserving tradeofftechniques. Data providers like many public and private organizations (e.g. hospitals and banks) publish microdata of individuals for various research purposes. Publishing microdata may compromise the privacy of individuals. To prevent the privacy of individuals, data must be published after removing personal identifiers like name and social security numbers. Removal of the personal identifiers appears as not enough to protect the privacy of individuals. Κ-anonymity model is used to publish microdata by preserving the individual’s privacy through generalization. There exist many state-of-the-arts generalizationbased techniques, which deal with pre-defined attacks like background knowledge attack, similarity attack, probability attack and so on. However, existing generalization-based techniques compromise the data utility while ensuring privacy. It is an open question to find an efficient technique that is able to set a trade-off between privacy and utility. In this paper, we discussed existing generalization hierarchies and their limitations in detail. We have also proposed three new generalization techniques including Conventional Generalization Hierarchies (CGH), Divisors Based Generalization Hierarchies (DBGH) and Cardinality-Based Generalization Hierarchies (CBGH). Extensive experiments on the real-world dataset acknowledges that our technique outperforms among the existing techniques in terms of better utility.

ACS Style

Saba Yaseen; Syed M. Ali Abbas; Adeel Anjum; Tanzila Saba; Abid Khan; Saif Ur Rehman Malik; Naveed Ahmad; Basit Shahzad; Ali Kashif Bashir. Improved Generalization for Secure Data Publishing. IEEE Access 2018, 6, 27156 -27165.

AMA Style

Saba Yaseen, Syed M. Ali Abbas, Adeel Anjum, Tanzila Saba, Abid Khan, Saif Ur Rehman Malik, Naveed Ahmad, Basit Shahzad, Ali Kashif Bashir. Improved Generalization for Secure Data Publishing. IEEE Access. 2018; 6 (99):27156-27165.

Chicago/Turabian Style

Saba Yaseen; Syed M. Ali Abbas; Adeel Anjum; Tanzila Saba; Abid Khan; Saif Ur Rehman Malik; Naveed Ahmad; Basit Shahzad; Ali Kashif Bashir. 2018. "Improved Generalization for Secure Data Publishing." IEEE Access 6, no. 99: 27156-27165.

Article
Published: 25 April 2018 in The Journal of Supercomputing
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The publication of microdata is pivotal for medical research purposes, data analysis and data mining. These published data contain a substantial amount of sensitive information, for example, a hospital may publish many sensitive attributes such as diseases, treatments and symptoms. The release of multiple sensitive attributes is not desirable because it puts the privacy of individuals at risk. The main vulnerability of such approach while releasing data is that if an adversary is successful in identifying a single sensitive attribute, then other sensitive attributes can be identified by co-relation. A whole variety of techniques such as SLOMS, SLAMSA and others already exist for the anonymization of multiple sensitive attributes; however, these techniques have their drawbacks when it comes to preserving privacy and ensuring data utility. The extant framework lacks in terms of preserving privacy for multiple sensitive attributes and ensuring data utility. We propose an efficient approach (p, k)-Angelization for the anonymization of multiple sensitive attributes. Our proposed approach protects the privacy of the individuals and yields promising results compared with currently used techniques in terms of utility. The (p, k)-Angelization approach not only preserves the privacy by eliminating the threat of background join and non-membership attacks but also reduces the information loss thus improving the utility of the released information.

ACS Style

Adeel Anjum; Naveed Ahmad; Saif U. R. Malik; Samiya Zubair; Basit Shahzad. An efficient approach for publishing microdata for multiple sensitive attributes. The Journal of Supercomputing 2018, 74, 5127 -5155.

AMA Style

Adeel Anjum, Naveed Ahmad, Saif U. R. Malik, Samiya Zubair, Basit Shahzad. An efficient approach for publishing microdata for multiple sensitive attributes. The Journal of Supercomputing. 2018; 74 (10):5127-5155.

Chicago/Turabian Style

Adeel Anjum; Naveed Ahmad; Saif U. R. Malik; Samiya Zubair; Basit Shahzad. 2018. "An efficient approach for publishing microdata for multiple sensitive attributes." The Journal of Supercomputing 74, no. 10: 5127-5155.

Research article
Published: 12 April 2018 in PLoS ONE
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In health sector, trust is considered important because it indirectly influences the quality of health care through patient satisfaction, adherence and the continuity of its relationship with health care professionals and the promotion of accurate and timely diagnoses. One of the important requirements of TRSs in the health sector is rating secrecy, which mandates that the identification information about the service consumer should be kept secret to prevent any privacy violation. Anonymity and trust are two imperative objectives, and no significant explicit efforts have been made to achieve both of them at the same time. In this paper, we present a framework for solving the problem of reconciling trust with anonymity in the health sector. Our solution comprises Anonymous Reputation Management (ARM) protocol and Context-aware Trustworthiness Assessment (CTA) protocol. ARM protocol ensures that only those service consumers who received a service from a specific service provider provide a recommendation score anonymously with in the specified time limit. The CTA protocol computes the reputation of a user as a service provider and as a recommender. To determine the correctness of the proposed ARM protocol, formal modelling and verification are performed using High Level Petri Nets (HLPN) and Z3 Solver. Our simulation results verify the accuracy of the proposed context-aware trust assessment scheme.

ACS Style

Farhana Jabeen; Zara Hamid; Wadood Abdul; Sanaa Ghouzali; Abid Khan; Saif Ur Rehman Malik; Mansoor Shaukat Khan; Sarfraz Nawaz. Anonymity-preserving Reputation Management System for health sector. PLoS ONE 2018, 13, e0195021 .

AMA Style

Farhana Jabeen, Zara Hamid, Wadood Abdul, Sanaa Ghouzali, Abid Khan, Saif Ur Rehman Malik, Mansoor Shaukat Khan, Sarfraz Nawaz. Anonymity-preserving Reputation Management System for health sector. PLoS ONE. 2018; 13 (4):e0195021.

Chicago/Turabian Style

Farhana Jabeen; Zara Hamid; Wadood Abdul; Sanaa Ghouzali; Abid Khan; Saif Ur Rehman Malik; Mansoor Shaukat Khan; Sarfraz Nawaz. 2018. "Anonymity-preserving Reputation Management System for health sector." PLoS ONE 13, no. 4: e0195021.

Journal article
Published: 02 March 2018 in IEEE Access
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Cloud computing provides online services to customers using pay as you go model. Cloud computing enables customers to outsource the large and complex tasks to the cloud data centers for the execution and result generations. Cloud data centers host the incoming tasks by providing resources, such as CPU, RAM, storage, and bandwidth. As the large data centers provide the basic resources to hosted tasks, they also consume a huge amount of energy, that leads to higher operating cost and CO2 traces. Therefore, research community felt the need to provide energy-efficient solutions that reduce the impact of the aforementioned issues. Consequently, researchers proposed many solutions, and majority of them are based upon the concept of consolidation. Consolidation techniques place the incoming tasks on minimum possible servers, thus increasing the resource utilization and decreasing energy consumption. In this paper, we use the same workload consolidation concept and present two techniques that reduce energy consumption while ensuring the negotiated quality of service (QoS). Moreover, we enhanced two existing techniques by improving the energy efficiency and introducing service level agreement (SLA) awareness to minimize the overall SLA violations. Performance evaluation of the proposed techniques is done based on fluctuating workloads, and results show that our techniques outperform existing techniques in terms of energy efficiency, SLA compliance, and performance assurance at the network level. Moreover, correctness of the proposed techniques is demonstrated by modeling and verifying them with the help of High-level Petri Nets, SMT-Lib, and Z3 Solver.

ACS Style

Saad Mustafa; Kashif Bilal; Saif Ur Rehman Malik; Sajjad A. Madani. SLA-Aware Energy Efficient Resource Management for Cloud Environments. IEEE Access 2018, 6, 15004 -15020.

AMA Style

Saad Mustafa, Kashif Bilal, Saif Ur Rehman Malik, Sajjad A. Madani. SLA-Aware Energy Efficient Resource Management for Cloud Environments. IEEE Access. 2018; 6 (99):15004-15020.

Chicago/Turabian Style

Saad Mustafa; Kashif Bilal; Saif Ur Rehman Malik; Sajjad A. Madani. 2018. "SLA-Aware Energy Efficient Resource Management for Cloud Environments." IEEE Access 6, no. 99: 15004-15020.

Journal article
Published: 01 March 2018 in Sustainable Computing: Informatics and Systems
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ACS Style

Basharat Mahmood; Naveed Ahmad; Saif U.R. Malik; Adeel Anjum; Saif Ul Islam. Power-efficient scheduling of parallel real-time tasks on performance asymmetric multicore processors. Sustainable Computing: Informatics and Systems 2018, 17, 81 -95.

AMA Style

Basharat Mahmood, Naveed Ahmad, Saif U.R. Malik, Adeel Anjum, Saif Ul Islam. Power-efficient scheduling of parallel real-time tasks on performance asymmetric multicore processors. Sustainable Computing: Informatics and Systems. 2018; 17 ():81-95.

Chicago/Turabian Style

Basharat Mahmood; Naveed Ahmad; Saif U.R. Malik; Adeel Anjum; Saif Ul Islam. 2018. "Power-efficient scheduling of parallel real-time tasks on performance asymmetric multicore processors." Sustainable Computing: Informatics and Systems 17, no. : 81-95.

Article
Published: 24 February 2018 in Cluster Computing
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The traditional paper-based voting is severely criticized after having found evidence of rigging in elections, leading to the uncertainty in the fairness of the election process. Traditional voting systems have severe issues in either user’s privacy or voting procedures. To counter these issues, e-voting systems have emerged as a potential solution. In this work, we proposed Internet e-voting protocol that fulfills the core properties like anonymity, verifiability, eligibility, privacy, receipt-freeness and fairness using dual signature. We prove the effectiveness and validity of our system using formal methods. A rigorous performance evaluation shows that our system clearly outperforms the existing state-of-the-art blind signature Internet e-voting protocols.

ACS Style

Malik Najmus Saqib; Junaid Kiani; Basit Shahzad; Adeel Anjum; Saif Ur Rehman Malik; Naveed Ahmad; Atta Ur Rehman Khan. Anonymous and formally verified dual signature based online e-voting protocol. Cluster Computing 2018, 22, 1703 -1716.

AMA Style

Malik Najmus Saqib, Junaid Kiani, Basit Shahzad, Adeel Anjum, Saif Ur Rehman Malik, Naveed Ahmad, Atta Ur Rehman Khan. Anonymous and formally verified dual signature based online e-voting protocol. Cluster Computing. 2018; 22 (S1):1703-1716.

Chicago/Turabian Style

Malik Najmus Saqib; Junaid Kiani; Basit Shahzad; Adeel Anjum; Saif Ur Rehman Malik; Naveed Ahmad; Atta Ur Rehman Khan. 2018. "Anonymous and formally verified dual signature based online e-voting protocol." Cluster Computing 22, no. S1: 1703-1716.

Journal article
Published: 01 January 2018 in Computers & Security
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ACS Style

Adeel Anjum; Saif Ur Rehman Malik; Kim-Kwang Raymond Choo; Abid Khan; Asma Haroon; Sangeen Khan; Samee U. Khan; Naveed Ahmad; Basit Raza. An efficient privacy mechanism for electronic health records. Computers & Security 2018, 72, 196 -211.

AMA Style

Adeel Anjum, Saif Ur Rehman Malik, Kim-Kwang Raymond Choo, Abid Khan, Asma Haroon, Sangeen Khan, Samee U. Khan, Naveed Ahmad, Basit Raza. An efficient privacy mechanism for electronic health records. Computers & Security. 2018; 72 ():196-211.

Chicago/Turabian Style

Adeel Anjum; Saif Ur Rehman Malik; Kim-Kwang Raymond Choo; Abid Khan; Asma Haroon; Sangeen Khan; Samee U. Khan; Naveed Ahmad; Basit Raza. 2018. "An efficient privacy mechanism for electronic health records." Computers & Security 72, no. : 196-211.