Qualification: 
Ph.D, MS, B-Tech
Email: 
srirams@am.amrita.edu

Dr. Sriram Sankaran currently serves as an Associate Professor at the Center for Cybersecurity Systems and Networks at Amrita Vishwa Vidyapeetham, India. He obtained M. S and Ph. D degrees in Computer Science and Engineering at the University at Buffalo, The State University of New York, USA. Previously, he received B. Tech (Hons) in Computer Science and Engineering from Malaviya National Institute of Technology, Jaipur formerly known as Regional Engineering College

 

 

Publications

Publication Type: Journal Article

Year of Publication Title

2021

J. Jithish and Sriram Sankaran, “A game-theoretic approach for ensuring trustworthiness in cyber-physical systems with applications to multiloop UAV control”, Transactions on Emerging Telecommunications Technologies, vol. 32, p. e4042, 2021.[Abstract]


Abstract Advancements in computing and communication technologies, coupled with the ubiquitous availability of low-cost embedded devices, have enabled the vision of cyber-physical systems (CPSs). With the advent of advanced persistent threats, CPSs are more vulnerable to sophisticated cyber-attacks that cause catastrophic damages, thereby necessitating the development of novel defence architectures for CPS security. This work presents an analytical framework based on noncooperative game theory to evaluate the trustworthiness of individual nodes that constitute CPSs. The proposed approach uses the Nash equilibrium solution to derive a minimum trust threshold score for the CPS nodes. The game-theoretic framework is evaluated on a supervisory control and data acquisition system prototype to model the evolution of the trust scores its sensors. Furthermore, we apply the model on a simulated unmanned aerial vehicle (UAV) system and derive the trust threshold. The trust threshold represents the minimum trust score required to be maintained by individual UAV nodes. Nodes with trust scores below the threshold are potentially malicious and may be removed or isolated to ensure the secure operation of the system. The proposed approach is successfully implemented to detect malicious behavior in a simulated multiloop UAV control system with a fewer number of false-positives, achieving a maximum accuracy of 98.85% across different scenarios.

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2021

Sriram Sankaran, K., N., and Achuthan, K., “A Novel Lightweight PUF based Authentication Protocol for IoT without Explicit CRPs in Verifier Database”, Journal of Ambient Intelligence and Humanized Computing, 2021.

2020

Sriram Sankaran, Jithish J., and Achuthan, K., “A Decision-centric approach for secure and energy-efficient cyber-physical systems”, Journal of Ambient Intelligence and Humanized Computing, 2020.[Abstract]


Cyber-Physical Systems (CPSs) integrate the interdisciplinary fields of computing, networking and control to perform tasks in the real world. CPSs have recently found applications in many battery-powered devices with stringent energy consumption requirements. To ensure secure operation, CPS necessitates sufficient security mechanisms to be incorporated against cyber attacks. However, maximizing energy efficiency and improving security are desirable but contrasting requirements. Towards reducing energy consumption, the optimal strategy for CPS is to initialize the security mechanism dynamically, at the onset of cyberattacks. In the absence of attacks, CPS can deactivate the security mechanism to minimize energy consumption. In the case of CPS, this approach is novel and contrary to the traditional approach of long-term, continual operation of the security mechanism. Towards this goal, we use a decision-centric approach based on Markov Decision Process (MDP) to estimate a threshold upon which the system initiates its security mechanism. We evaluate our proposed mechanism using MATLAB based TrueTime simulator. Evaluation shows that our proposed MDP-based approach achieves maximum energy-savings of 8.26 and 11.05% in defending against Denial-of-Service and Deception attacks, respectively. Further, our approach can be used to develop sustainable CPS designs that balance the trade-off between energy-efficiency and security.

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2020

Sriram Sankaran and NB, G., “Modeling and Defending against Resource Depletion Attacks in 5G Networks”, Proceedings of IEEE INDICON, 2020.

2019

J. Pathak, Sriram Sankaran, and Achuthan, K., “A Framework for Digital Forensics and Investigations”, In Proceedings of International Symposium on Embedded Computing and System Design (ISED) 2019, 2019.

2018

H. Min, Kim, T., Heo, J., Cerny, T., Sriram Sankaran, Ahmed, B. S., and Jung, J., “Pattern matching based sensor identification layer for an android platform”, Wireless Communications and Mobile Computing, vol. 2018, p. 11, 2018.[Abstract]


As sensor-related technologies have been developed, smartphones obtain more information from internal and external sensors. This interaction accelerates the development of applications in the Internet of Things environment. Due to many attributes that may vary the quality of the IoT system, sensor manufacturers provide their own data format and application even if there is a well-defined standard, such as ISO/IEEE 11073 for personal health devices. In this paper, we propose a client-server-based sensor adaptation layer for an Android platform to improve interoperability among nonstandard sensors. Interoperability is an important quality aspect for the IoT that may have a strong impact on the system especially when the sensors are coming from different sources. Here, the server compares profiles that have clues to identify the sensor device with a data packet stream based on a modified Boyer-Moore-Horspool algorithm. Our matching model considers features of the sensor data packet. To verify the operability, we have implemented a prototype of this proposed system. The evaluation results show that the start and end pattern of the data packet are more efficient when the length of the data packet is longer.

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2018

Jithish J. and Sriram Sankaran, “A Bio-Inspired approach to secure Networked Control Systems against Adversarial Delays”, Intelligent and Fuzzy Systems, 2018.

Publication Type: Conference Proceedings

Year of Publication Title

2021

Sriram Sankaran, Vamshi, S. Mohan, Mukund, S., Chandra, G. Krushna, Himesh, S., and Krishnashree, A., “Predictive Modeling of the Spread of COVID-19: The Case of India”, Proceedings of 4th EAI International Conference on Ubiquitous Communications and Network Computing (UBICNET). Springer International Publishing, Cham, 2021.[Abstract]


COVID-19 has been the most notorious pandemic affecting the entire world resulting in numerous deaths thus crippling the world economy. While vaccines are in the process of being developed for protection, countries are implementing measures such as social distancing to prevent the spread of the virus. Also, there exists a need for developing mathematical models to predict the rate of spread of COVID-19 and quantify its impact on countries such as India. Towards this goal, we developed a realistic COVID-19 dataset consisting of state-wide distribution of number of cases in India from March-July 2020. Further, we conduct exploratory data analysis on the dataset to understand the states and their corresponding growth rates. This enables us to cluster states with exponential and non-exponential growth rates as well as assess the effectiveness of lockdown imposed to curb the spread of virus. Finally, we develop predictive models using Auto-Regressive Integrated Moving Average (ARIMA) and Long Short-Term Memory Networks (LSTM) on time-series data for top-10 affected states in India to predict the rate of spread and validate their accuracy. Finally, our models can be used to guide the development of mechanisms for optimal resource allocation of healthcare systems and response

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2021

N. Hegde and Sriram Sankaran, “Towards an Adversarial Model for Keystroke Authentication in Embedded Devices”, Proceedings of International Symposium on Embedded Computing and System Design (ISED). 2021.

2020

Jithish J., Sriram Sankaran, and Achuthan, K., “Towards Ensuring Trustworthiness in Cyber-Physical Systems: A Game-Theoretic Approach”, 2020 International Conference on COMmunication Systems NETworkS (COMSNETS). 2020.[Abstract]


The following topics are dealt with: learning (artificial intelligence); Internet of Things; cloud computing; mobile computing; optimisation; 5G mobile communication; cellular radio; cryptography; telecommunication traffic; telecommunication computing.

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2020

S. Jerin, Sriram Sankaran, and Saraswat, V., “Towards a Lightweight Blockchain Platform for Critical Infrastructure Protection”, 2020 IEEE 40th International Conference on Distributed Computing Systems (ICDCS). 2020.

2020

A. J. Suresh and Sriram Sankaran, “Power Profiling and Analysis of Code Obfuscation for Embedded Devices”, 2020 IEEE 17th India Council International Conference (INDICON). 2020.[Abstract]


Obfuscation is a popular software transformation to protect intellectual property and avoid reverse engineering. It relies on introducing additional instructions and changing control-flow without affecting program semantics. Invariably, this introduces overheads in terms of memory, execution time and energy consumption for resource-constrained environments. In this work, we show that these overheads are dependent on three factors: the transformations and their combinations selected, the tool used to effect these transformations and the program workload. Our experiments using two popular obfuscation tools, Obfuscation Low-Level Virtual Machine (OLLVM) and Tigress, show that obfuscation could potentially lead to a 5-fold increase in execution time and energy consumption depending on these factors. Consequently, our results are profitable for security engineers to choose appropriate transformations for each application for resource-constrained environments.

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2020

A. J. Suresh and Sriram Sankaran, “A Framework for Evaluation of Software Obfuscation Tools for Embedded Devices”, Applications and Techniques in Information Security. Springer Singapore, Singapore, 2020.[Abstract]


Obfuscation is a popular software transformation to protect intellectual property and avoid reverse engineering. It relies on introducing additional instructions and changing control-flow without affecting program semantics. This introduces overheads in terms of memory, execution time and energy consumption for resource-constrained embedded devices. In this work, we show that these overheads are dependent on three factors: the transformations and their combinations selected, the tool used to effect these transformations and the program workload. In addition, there exists a need for measuring the security of obfuscated code. In this work, we develop a framework for evaluating software obfuscation tools potentially highlighting costs and benefits associated with obfuscation and analyze energy-performance-security trade offs for embedded devices. Our experiments using two popular obfuscation tools, Obfuscation Low-Level Virtual Machine (OLLVM) and Tigress, show that obfuscation could potentially lead to a 5-fold increase in execution time and energy consumption depending on these factors. In addition, Tigress provides more security and simultaneously incurs significant energy consumption compared to OLLVM. Our cost-benefit analysis with respect to energy, performance and security can be used to determine the optimal choice of security measures for resource-constrained environments.

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2020

A. Rajan and Sriram Sankaran, “Lightweight and Attack-resilient PUF for Internet of Things”, 2020 IEEE International Symposium on Smart Electronic Systems (iSES) (Formerly iNiS). 2020.[Abstract]


IoT security is of paramount concern due to poorly configured devices that can often serve as entry points for cyber attacks. Developing Physically Unclonable Functions (PUFs) and making them resilient can enhance hardware security. In this work, we propose a XOR-mesh based PUF composed of network of XOR-gates and multiplexers. The proposed PUF was implemented on an Artix-7 FPGA and evaluated in terms of hardware and power consumption. The Challenge-Response Pairs (CRPs) were extracted and used to evaluate the PUF quality and attack resilience against two machine learning algorithms such as Logistic Regression (LR) and Support Vector Machine (SVM). Evaluation shows that our PUF is power efficient, utilises only 16.35% of total available slices on the FPGA and resilient to linear modeling attacks irrespective of response sequence length. This makes it suitable for lightweight and secure applications in IoT security.

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2020

G. Surya, Maistri, P., and Sriram Sankaran, “Local Clock Glitching Fault Injection with Application to the ASCON Cipher”, 2020 IEEE International Symposium on Smart Electronic Systems (iSES) (Formerly iNiS). 2020.[Abstract]


Lightweight ciphers such as ASCON facilitate ease of implementation as well as provide better performance over conventional ciphers, thus making it suitable for resource-constrained devices. However, hardware implementations of these ciphers are vulnerable to a multitude of physical attacks (such as fault injections) requiring dedicated countermeasures thus causing a negative impact on security, performance and power consumption. Modeling and understanding the impact of these attacks on cipher operations and end users is mandatory. Further, detection and mitigation of such fault injection attacks is challenging due to the interconnected nature of cipher design, coupled with the varying number of possible design choices and with the forced trade-offs that need to be done in order to implement expensive countermeasures at the lowest possible cost. In this work, we aim to model a fault injection attack on ASCON and analyze its impact on FPGA. In particular, we implement the ASCON cipher and propose a methodology for fault injection attacks using synchronous clock glitching by Digital Clock Manager (DCM) introducing a novel approach of locality, which can be exploited to emulate general delay faults on focused parts of the design, such those induced by pulsed EM injections.

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2020

N. B. Gokul and Sriram Sankaran, “Identity Based Security Framework For Smart Cities”, 2020 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS). 2020.[Abstract]


A Smart City is a next generation city where it uses information and communication technologies(ICT) to provide numerous services and amenities with improved efficiency and reliability in a hierarchical manner. Despite the benefits, securing smart cities is of paramount importance for safeguarding communications from malicious entities and preserving user privacy. Thus a need for developing a security framework for smart cities becomes necessary for integrating smart city services and platforms in a hierarchical manner. In this paper, we develop an identity based security framework for smart cities. The proposed framework leverages the hierarchical nature of smart cities and builds a pseudonym-based key management scheme that uses identities as public keys. Our approach replaces the traditional Public Key Infrastructure in smart cities thus providing improved benefits in terms of security, reliability and efficiency. Evaluation of the proposed scheme shows that our approach is lightweight compared to traditional public key infrastructure and that it eliminates the problem of single point of failure in Private Key Generators (PKG).

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2020

J. Sunny, Sriram Sankaran, and Saraswat, V., “A Hybrid Approach for Fast Anomaly Detection in Controller Area Networks”, 2020 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS). 2020.[Abstract]


Recent advancements in the field of in-vehicle network and wireless communication, has been steadily progressing. Also, the advent of technologies such as Vehicular Adhoc Networks (VANET) and Intelligent Transportation System (ITS), has transformed modern automobiles into a sophisticated cyber-physical system rather than just a isolated mechanical device. Modern automobiles rely on many electronic control units communicating over the Controller Area Network (CAN) bus. Although protecting the car's external interfaces is an vital part of preventing attacks, detecting malicious activity on the CAN bus is an effective second line of defense against attacks. This paper proposes a hybrid anomaly detection system for CAN bus based on patterns of recurring messages and time interval of messages. The proposed method does not require modifications in CAN bus. The proposed system is evaluated on real CAN bus traffic with simulated attack scenarios. Results obtained show that our proposed system achieved a good detection rate with fast response times.

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2019

J. Pathak, Sriram Sankaran, and Achuthan, K., “A SMART Goal-based Framework for Privacy Preserving Embedded Forensic Investigations”, In Proceedings of International Symposium on Embedded Computing and System Design (ISED) 2019. 2019.

2019

D. M. Chevayoor, K, N., and Sriram Sankaran, “Towards Behavioral Profiling Based Anomaly Detection for Smart Homes”, In Proceedings of IEEE Region 10 Conference (TENCON), 2019. 2019.

2019

J. Prakash and Sriram Sankaran, “Attack Detection based on Statistical Analysis of Smartphone Resource Utilization”, In Proceedings of IEEE INDICON, 2019. 2019.

2019

N. Pramod PS and Sriram Sankaran, “Blockchain based framework for Driver Profiling in Smart Cities”, In Proceedings of IEEE Advanced Networks and Telecommunications Systems (ANTS), 2019. 2019.[Abstract]


Background

The notion of smart city has grown popular over the past few years. It embraces several dimensions depending on the meaning of the word “smart” and benefits from innovative applications of new kinds of information and communications technology to support communal sharing.

Methods

By relying on prior literature, this paper proposes a conceptual framework with three dimensions: (1) human, (2) technology, and (3) organization, and explores a set of fundamental factors that make a city smart from a sharing economy perspective.

Results

Using this triangle framework, we discuss what emerging blockchain technology may contribute to these factors and how its elements can help smart cities develop sharing services.

Conclusions

This study discusses how blockchain-based sharing services can contribute to smart cities based on a conceptual framework. We hope it can stimulate interest in theory and practice to foster discussions in this area.

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2019

J. Santhosh and Sriram Sankaran, “Defending against Sybil Attacks in Vehicular Platoons”, In Proceedings of IEEE Advanced Networks and Telecommunications Systems (ANTS), 2019. 2019.

2019

P. M.R and Sriram Sankaran, “An Experimental Framework for Security of Cyber Physical Systems”, In Proceedings of IEEE International Symposium on Smart Electronic Systems (iSES) 2019. 2019.

2019

Sriram Sankaran, Pramod, N., and Achuthan, K., “Energy and Performance Comparison of Cryptocurrency Mining for Embedded Devices”, In Proceedings of International Symposium on Embedded Computing and System Design (ISED) 2019. 2019.

2019

Sriram Sankaran and R, P. M., “Security over Voice Controlled Android Application for Home IoT Systems”, In Proceedings of International Symposium on Embedded Computing and System Design (ISED) 2019. 2019.

2018

N. K, Sriram Sankaran, and Achuthan, K., “A Novel Multi-factor Authentication Protocol for Smart Home Environments”, International Conference on Information Systems Security (ICISS), vol. 11281. Springer, Cham, 2018.[Abstract]


User authentication plays an important role in smart home environments in which devices are interconnected through the Internet and security risks are high. Most of the existing research works for remote user authentication in smart homes fail in one way or the other in combating common attacks specifically smartphone capture attack. Robust authentication method which can uniquely identify the smartphones of users can thwart unauthorized access through the physical capture of smartphones. Existing studies demonstrate that Photo Response Non-Uniformity (PRNU) of a smartphone can be used to uniquely identify the device with an error rate less than 0.5%. Based on these results, we propose a multi-factor user authentication protocol based on Elliptic Curve Cryptography (ECC) and secret sharing for smart home environments. We leverage face biometric and PRNU to make it resilient to common attacks. Moreover, the proposed protocol achieves mutual authentication among all participating entities and thereby ensures the legitimacy of all the participating entities. Subsequently, a session key is established for secure communication between the users and the devices. Our analysis of the proposed protocol shows that it provides significantly better security than the existing schemes with a reasonable overhead. In addition, it provides better usability by alleviating the burden of users from memorizing passwords and carrying additional mechanisms such as smart cards.

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2018

S. Sanju, Sriram Sankaran, and Achuthan, K., “Energy Comparison of Blockchain Platforms for Internet of Things”, IEEE International Symposium on Smart Electronic Systems (iSES). 2018.

2018

Sriram Sankaran, Sivamohan, S., and K, N., “LHPUF: Lightweight Hybrid PUF for Enhanced Security in Internet of Things”, IEEE International Symposium on Smart Electronic Systems (iSES). 2018.

2018

Sriram Sankaran and Gupta, M., “Game Theoretic Modeling of Power-Performance trade-offs for Mobile Devices”, Proceedings of International Symposium on Embedded Computing and System Design (ISED). 2018.

2018

S. Roy, Sriram Sankaran, Singh, P., Sridhar, R., and , “CONTEXT-SEC: Balancing Energy Consumption and Security of Mobile Devices (Accepted) ”, 2018 Ninth International Green and Sustainable Computing (IGSC) Workshops. 2018.

2018

Sriram Sankaran and Gupta, M., “Towards a Hybrid Model for CPU Usage Prediction of Smartphone Users(Accepted)”, International Conference on Advanced Computing and Communications (ADCOM) 2018 . 2018.

2018

S. Roy, Sriram Sankaran, Singh, P., and Sridhar, R., “Modeling Context-Adaptive Energy-Aware Security in Mobile Devices (Accepted)”, 43rd Conference on Local Computer Networks Workshops (LCN Workshops). 2018.

2018

Sriram Sankaran, Sanju, S., and Dr. Krishnashree Achuthan, “Towards Realistic Energy Profiling of Blockchains for securing Internet of Things”, IEEE International Conference on Distributed Computing Systems (ICDCS) 2018. pp. 1454-1459, 2018.[Abstract]


Internet of Things (IoTs) offers a plethora of opportunities for remote monitoring and communication of everyday objects known as things with applications in numerous domains. The advent of blockchains can be a significant enabler for IoTs towards conducting and verifying transactions in a secure manner. However, applying blockchains to IoTs is challenging due to the resource constrained nature of the embedded devices coupled with significant delay incurred in processing and verifying transactions in the blockchain. Thus there exists a need for profiling the energy consumption of blockchains for securing IoTs and analyzing energy-performance trade-offs. Towards this goal, we profile the impact of workloads based on Smart Contracts and further quantify the power consumed by different operations performed by the devices on the Ethereum platform. In contrast to existing approaches that are focused on performance, we characterize performance and energy consumption for real workloads and analyse energy-performance trade-offs. Our proposed methodology is generic in that it can be applied to other platforms. The insights obtained from the study can be used to develop secure protocols for IoTs using blockchains.

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2018

Jithish J. and Sriram Sankaran, “Towards a Decision-Centric approach for securing Cyber Physical Systems”, 10th International Conference on Communication Systems and Networks (COMSNETS) 2018. p. 500‐502, 2018.[Abstract]


The emerging discipline of Cyber Physical Systems (CPS) integrate the interdisciplinary fields of computing, networking and control to offer solutions to real world problems. CPS solutions typically include security mechanisms that defend against attack attempts and initiate countermeasures to thwart the attacker objectives. To minimize the system performance overhead, the optimal decision would be to initialize the security mechanism in response to attack attempts in contrast to sustained operation. In this work, we use Markov Decision Processes (MDP) to decide the threshold upon which the system initiates the security mechanism. The system may be initialized at the threshold to minimize the overall operating costs. The proposed model can be further used to develop a decision-centric security architecture for CPS that balances the trade-off between system performance and security.

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2017

S. Anil Kumar, Jithish J., and Sriram Sankaran, “Towards efficient resource provisioning in Vehicular Networks”, IEEE Biennial International Conference on Technological Advancements in Power & Energy (TAPEnergy) 2017. 2017.[Abstract]


The growing technological advancements in the fields of computation and communication technologies has enabled a communication network of vehicles, interacting among themselves to facilitate safe and efficient traffic in urban environments, termed as Vehicular Ad Hoc Network (VANET). VANETs depend on computational units called Road Side Units (RSUs), deployed along the highway to enable connectivity to moving vehicles in the network. Developing mechanisms for efficient resource provisioning of RSUs are of significant importance for energy efficiency in Vehicular networks. Towards this goal, we develop a model to dynamically resize computational resources of RSUs based on vehicle density. The proposed model utilizes queuing theory to determine the optimum number of computational units required to handle data exchanges depending on the vehicle density. Preliminary results in MATLAB/Simulink environment show feasibility and effectiveness of the proposed solution for achieving energy efficient operation in VANETs.

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2017

Sriram Sankaran and Gupta, M., “Towards Modeling Vehicular Networks with Power-Performance trade-offs”, IEEE International Conference on Advanced Networks and Telecommunication Systems (ANTS) . 2017.[Abstract]


Vehicular networks are gaining increasing significance due to real-time communication and decision-making capabilities of vehicles and their interaction with road-side units. Power Management is critical for roadside units since they are typically powered on for servicing requests from vehicles. In this work, we envision low-power proxy servers to act on behalf of roadside units during periods of minimal activity to enable roadside units to be powered down resulting in power savings. However there exists a need for modeling of vehicular networks with roadside units and proxy servers for analyzing power-performance trade-offs. Towards this goal, we develop a queueing model to understand the impact of highway traffic on the power consumed by roadside units and proxy servers and further propose a threshold based approach for power savings. Our experiments conducted using real traces demonstrate that the proposed approach is traffic-aware in that it balances the trade-off between power consumption and delay.

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2017

T. V. Ram and Sriram Sankaran, “Towards policy-driven power management for cloud computing”, 2017 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS). IEEE, Bhubaneswar, India, 2017.[Abstract]


Cloud computing enables users to rent computing resources on-demand towards meeting the needs of diverse applications. However, scaling of resources may incur significant impact on performance and power consumption which are the two key concerns for cloud service providers. The major goal of cloud providers is to develop policies for balancing the conflicting objectives of maximizing performance and minimizing energy consumption. Towards this goal, we analyze the impact of scale-up and scale-out techniques for varying cloud workloads through an OpenStack implementation. Our analysis reveals that these techniques vary with the nature of applications that run on the cloud as a result of which policies need to be developed on a per-application basis. We develop a threshold-based policy which determines the optimal trade-off depending on the application profile. Our proposed policy is generic and can be applied to other workloads thus facilitating efficient management of resources.

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2017

A. Rajan, Jithish, J., and Sriram Sankaran, “Sybil attack in IOT: Modelling and defenses”, 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI). IEEE, Udupi, India, 2017.[Abstract]


Internet of Things (IoT) is an emerging paradigm in information technology (IT) that integrates advancements in sensing, computing and communication to offer enhanced services in everyday life. IoTs are vulnerable to sybil attacks wherein an adversary fabricates fictitious identities or steals the identities of legitimate nodes. In this paper, we model sybil attacks in IoT and evaluate its impact on performance. We also develop a defense mechanism based on behavioural profiling of nodes. We develop an enhanced AODV (EAODV) protocol by using the behaviour approach to obtain the optimal routes. In EAODV, the routes are selected based on the trust value and hop count. Sybil nodes are identified and discarded based on the feedback from neighbouring nodes. Evaluation of our protocol in ns-2 simulator demonstrates the effectiveness of our approach in identifying and detecting sybil nodes in IoT network.

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2017

J. Jithish and Sriram Sankaran, “Securing networked control systems: Modeling attacks and defenses”, 2017 IEEE International Conference on Consumer Electronics-Asia (ICCE-Asia). IEEE, Bangalore, India, 2017.[Abstract]


Networked Control Systems (NCS) have emerged as a viable solution to effectively manage critical infrastructures in smart cities and modern industrial settings. The networked architecture of NCS that facilitates the communication between its distributed components makes them vulnerable to cyber attacks. The vulnerabilities in the communication network coupled with safety critical nature of data necessitates the need to develop models to analyze the impact of cyber attacks on system stability and performance. In this work, we develop an analytical model for Denial of Service (DoS) and Deception attacks in NCS. Based on the insights from the model, we propose a mechanism based on symmetric key encryption to secure NCS from such attacks. The comparison of our security mechanism with the standard reference signal demonstrates that our approach is successful in securing the NCS with minimal performance overhead.

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2017

J. Jithish and Sriram Sankaran, “A Rule-Based System for Smart Home Energy Prediction”, Development Aspects of Intelligent Systems (DIAS) co-located with Innovations in Software Engineering 2017. 2017.

2017

Jithish J. and Sriram Sankaran, “A Neuro-Fuzzy Approach for Domestic Water Usage Prediction”, Proceedings of IEEE Region 10 Symposium (TENSYMP). 2017.[Abstract]


The unconstrained rise in water usage as a result of population growth, rapid urbanization and climate change has become an issue of paramount concern for policy makers across the globe. Consequently, fresh water as a renewable but finite resource must be managed efficiently to sustain domestic and productive activities. Efficient water management strategies must be developed to address the challenges of increased demand without undermining long term sustainability. Developing such strategies necessitates a multidisciplinary approach incorporating policy planning and applied technology to efficiently manage water resources for maximizing economic growth and promoting social welfare. Towards this goal, we develop a hybrid intelligent system for domestic water usage prediction based on Adaptive Neuro-Fuzzy Inference System (ANFIS). The proposed system is trained in a supervised manner to model the relationship between environmental factors and domestic water consumption. The system forecasts domestic water usage based on environmental factors particularly atmospheric pressure, temperature, relative humidity and wind speed. Evaluation of the system on a real smart home dataset demonstrates that the system predicts domestic water consumption with higher accuracy.

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2017

J. Jithish and Sriram Sankaran, “A Hybrid Adaptive Rule Based System For Smart Home Energy Prediction”, CEUR Workshop Proceedings, vol. 1819. CEUR-WS, 2017.[Abstract]


The increase in energy prices combined with the environmental impact of energy production has made energy efficiency a key component towards the development of smart homes. An efficient energy management strategy for smart homes results in minimized electricity consumption leading to cost savings. Towards this goal, we investigate the impact of environmental factors on home energy consumption. Home energy demand is observed to be affected by environmental factors such as temperature, wind speed and humidity which are inherently uncertain. Analyzing the impact of these factors on electricity consumption is challenging due to the unpredictability of weather conditions and non-linear relationship between environmental factors and electricity demand. For demand estimation based on these time varying factors, a hybrid intelligent system is developed that integrates the adaptability of neural networks and reasoning of fuzzy systems to predict daily electricity demand. A smart home dataset is utilized to build an unsupervised artificial neural network known as the Self-Organizing Map (SOM). We further develop a fuzzy rule based system from the SOM to predict home energy demand. Evaluation of the system shows a strong correlation between home energy demand and environmental factors and that the system predicts home energy consumption with higher accuracy. Copyright ©2017 for the individual papers by the papers' authors.

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2017

A. Raj, Jithish, J., and Sriram Sankaran, “Modelling The Impact Of Code Obfuscation On Energy Usage”, CEUR Workshop Proceedings, vol. 1819. CEUR-WS, 2017.[Abstract]


Advancements in computing and communication technologies have given rise to low-cost embedded devices with applications in diverse domains such as Smarthome, industrial automation, healthcare, transportation etc. These devices are power-constrained which emphasizes the need for lightweight security solutions. Code obfuscation has been demonstrated to provide time-limited protection of source code from inference or tampering attacks. However, size of the obfuscated code increases with increase in code size which can have a negative impact on energy consumption. In particular, different transformations of the source code result in varying amounts of energy consumption for embedded devices. In this work, we model the impact of algorithms for code obfuscation on energy usage for embedded devices and analyze the energy-security-performance trade-offs. The insights from our analysis can be used to develop techniques depending on the needs of the applications thus facilitating efficient energy usage. Copyright ©2017 for the individual papers by the papers' authors.

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PDF iconModeling-the-Impact-of-Code-Obfuscation-on-Energy-Usage.pdf

2016

Sriram Sankaran, “Modeling the Performance of IoT Networks”, IEEE International Conference on Advanced Networks and Telecommunication Systems (ANTS). IEEE, Bangalore, India, 2016.[Abstract]


Internet of Things (IoTs) is gaining increasing significance due to real-time communication and decision making capabilities of sensors integrated into everyday objects. Predicting performance in IoTs is critical for detecting performance bottlenecks, designing optimal sleep/wake-up schedules and application-aware performance tuning. However, performance prediction becomes a significant challenge in IoTs due to varying needs of applications coupled with the resource constrained nature of sensors. In this work, we analyze the impact of factors affecting performance in IoT networks using simulation based models. Further, an analytical framework is developed to model the impact of individual node behavior on overall performance using Markov chains. In particular, we derive steady state transition probabilities of transmit and receive states using protocol execution traces and further utilize them towards predicting per-flow throughput. Our proposed model is generic in that it can be applied across domains. Accuracy of the model is evaluated by comparing the predictions with the actual estimates obtained using simulations.

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PDF iconModeling-the-Performance-of-IoT-Networks.pdf

2016

Sriram Sankaran, “Lightweight Security Framework For IoTs Using Identity Based Cryptography”, International Conference on Advances in Computing, Communications and Informatics (ICACCI). IEEE, Jaipur, India, 2016.[Abstract]


Internet of Things (IoTs) is gaining increasing significance due to real-time communication and decision making capabilities of sensors integrated into everyday objects. Securing IoTs is one of the foremost concerns due to the ubiquitous nature of the sensors coupled with the increasing sensitivity of user data. Further, power-constrained nature of the IoTs emphasizes the need for lightweight security that can tailor to the stringent resource requirements of the sensors. In this work, we propose a lighweight security framework for IoTs using Identity based Cryptography. In particular, we develop a hierarchical security architecture for IoTs and further develop protocols for secure communication in IoTs using identity based cryptography. Our proposed mechanism has been evaluated using simulations conducted using Contiki and RELIC. Evaluation shows that our proposed mechanism is lightweight incurring lesser overhead and thus can be applied in IoTs.

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PDF iconLightweight-Security-Framework-For-IoTs-Using-Identity-Based-Cryptography.pdf

2016

Sriram Sankaran, “Predictive Modeling based Power Estimation for Embedded Multicore Systems”, ACM International Conference on Computing Frontiers (CF). ACM Digital Library, Como, Italy, pp. 370-375, 2016.[Abstract]


The increasing number of cores in embedded devices results in improved performance compared to single-core systems. Further, the unique characteristics of these systems provide numerous opportunities for power management which require models for power estimation. In this work, a statistical approach that models the impact of the individual cores and memory hierarchy on overall power consumed by Chip Multiprocessors is developed using Performance Counters. In particular, we construct a per-core based power model using SPLASH2 benchmarks by leveraging concurrency for multicore systems. Our model is simple and technology independent and as a result executes faster incurring lesser overhead. Evaluation of the model shows a strong correlation between core-level activity and power consumption and that the model predicts power consumption for newer observations with minimal errors. In addition, we discuss a few applications where the model can be utilized towards estimating power consumption.

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PDF iconPredictive-Modeling-based-Power-Estimation-for-Embedded-Multicore-Systems.pdf

2015

Sriram Sankaran and Sridhar, R., “Modeling and Analysis of Routing for IoT Networks”, International Conference on Computing and Network Communications (CoCoNet). IEEE, Trivandrum, India, 2015.[Abstract]


Internet of Things (IoTs) is gaining increasing significance due to real-time communication and decision making capabilties of sensors integrated into everyday objects. IoTs are power and bandwidth-constrained with applications in smarthome, healthcare, transportation and industrial domains. Routing bears significant importance in IoTs where sensors acting as hosts deliver data to the gateways which in turn impacts power consumption. Thus there exists a need for modeling and analysis of routing in IoT networks towards predicting power consumption. In this work, we develop an analytical model of a naive flooding based routing protocol using Markov chains. In particular, we derive steady state transition probabilities of transmit and receive states using protocol execution traces and further utilize them towards predicting power consumption. Our approach to modeling is generic in that it can be applied to routing protocols across domains. Evaluation of the model shows that the predicted values for power consumption lie closer to the actual observations obtained using ns-2 simulation thus resulting in minimal mean square errors.

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PDF iconModeling-and-Analysis-of-Routing-in-IoT-Networks.pdf

2013

Sriram Sankaran and R, S., “Energy Modeling for Mobile Devices Using Performance Counters”, 56th International Midwest Symposium on Circuits and Systems. IEEE , Columbus, OH; United States, pp. 441-444, 2013.[Abstract]


The increasing complexity of mobile applications coupled with growing user demands lead to rapid battery drain in mobile devices. However, battery technology cannot keep up with these trends thus making power management one of the foremost concerns. While system-level approaches to power management exist, the energy impact of applications on individual system components needs to be better understood for energy efficient system design. In this work, we develop energy models for mobile devices using performance counters and estimate the power consumption of system components for numerous embedded applications. Our models provide enhancements in I/O towards estimating I/O energy and cache to incorporate energy consumed during cache refill and write-back in the energy estimation process. We further compare our power estimates with existing models and demonstrate the uniqueness of our model.

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PDF iconEnergy-Modeling-of-Mobile-Devices-using-Performance-Counters.pdf

2013

Sriram Sankaran and Sridhar, R., “User-Adaptive Energy-aware Security for Mobile Devices”, IEEE Conference on Communications and Network Security (CNS). IEEE, National Harbor, MD, USA, 2013.[Abstract]


Advancements in computing and communication technologies have given rise to low-cost embedded devices with applications in diverse domains such as Smarthome, industrial automation, healthcare, transportation etc. These devices are power-constrained which emphasizes the need for lightweight security solutions. Code obfuscation has been demonstrated to provide time-limited protection of source code from inference or tampering attacks. However, size of the obfuscated code increases with increase in code size which can have a negative impact on energy consumption. In particular, different transformations of the source code result in varying amounts of energy consumption for embedded devices. In this work, we model the impact of algorithms for code obfuscation on energy usage for embedded devices and analyze the energy-security-performance trade-os. The insights from our analysis can be used to develop techniques depending on the needs of the applications thus facilitating efficient energy usage.

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PDF iconUser-Adaptive-Energy-aware-Security-for-Mobile-Devices.pdf

2009

Sriram Sankaran, Husain, M. Iftekhar, and Sridhar, R., “IDKEYMAN: An Identity-Based Key Management Scheme for Wireless Ad Hoc Body Area Networks”, Proceedings of Annual Symposium on Information Assurance (ASIA). 2009.[Abstract]


Wireless Ad hoc Body Area Networks are primarily used in health-care applications for patient monitoring purposes. Publisher-Subscriber driven Body Area Networks enable publishers (medical sensors attached to patients) to disseminate medical data to numerous mobile heterogeneous subscribers (doctors or caregivers) through a subscription mechanism. Such an environment raises serious security concerns due to the privacy critical medical data coupled with the resource constraints of individual body sensors. To address this problem, we present an identity based key management scheme using Identity-Based Encryption (IBE). IBE facilitates faster key set-up in addition to being lightweight and energy-efficient. The proposed scheme uses IBE to set up pair-wise symmetric keys to preserve data confidentiality and integrity. Our prototype and evaluation of the proposed model validate the approach.

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PDF iconIDKEYMAN-An-Identity-Based-Key-Management-Scheme-for-Wireless-Ad-Hoc-Body-Area-Networks.pdf