Ashish sonal_banglore


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  • Need of the hour is to converge the existing resources of HUMINT as well as technology to enhance real time intelligence and be able to predict the unforessen by understanding patterns - which is humanly not possible and not achiavable
  • Warfare and intelligence is becoming very complexed and just having HUMINT is not enough and therefore needs more network based approach which collates as well as demistifies the intelligence from unstructured data bases to structured analyses to derive the intelligence – Helpful in 9/11 and 26/11 kind of investigations
  • Ashish sonal_banglore

    2. 2. About Orkash <ul><li>Orkash is an India headquartered, international management-consulting and high-technology R&D company operating in the following areas: </li></ul><ul><ul><li>Investment & Transaction Advisory Support </li></ul></ul><ul><ul><li>Operational Risk and Security Risk Management </li></ul></ul><ul><ul><li>Strategic Business & Market Intelligence </li></ul></ul><ul><ul><li>Battlefield Management, Intelligence, Decision Support & Homeland Security Platforms </li></ul></ul><ul><li>On the technology side, ORKASH is focused on creating new technology applications (and the highly-scalable back-end infrastructure) to plug the gap between i n formation access (search engines, etc.) and i n formation analysis (human-intelligence). These are designed to support decision makers in the business, the government and the security agencies. The company has cutting edge technology and R&D expertise across: </li></ul><ul><ul><li>AI systems, NLP and Expert Engines </li></ul></ul><ul><ul><li>Massively large and parallel data-mining systems </li></ul></ul><ul><ul><li>Automated Intelligence Analysis, Business Intelligence & Decision Support Analytics </li></ul></ul><ul><ul><li>Geographical Information Systems </li></ul></ul><ul><ul><li>Parallel computing, clusters & cloud computing </li></ul></ul>
    3. 3. Agenda Part -1 Indian Security Scenario Overview Part -2 Automating Intelligence creation - Intelligence creation - Correlating the 'concept of operations' Part-3 Tackling unconventional conflicts in India - UCIMS
    4. 4. The previous wave .. Date of attack Location (Scope of the attack) LEGEND KEY 21 October 2008 Imphal, Manipur (One device) 13 May 2008 Jaipur, Rajasthan (Eight devices) 25 July 2008 Bengaluru, Karnataka (Eight Devices) 26 July 2008 Ahmedabad, Gujarat (21 devices) 29-30 July 2008 Surat, Gujarat (18 devices) 13 September 2008 New Delhi (Six devices) 29 September 2008 Modasa, Gujarat (One device) 29 September 2008 Malegaon, Maharashtra (Two devices) 01 October 2008 Tripura, Agartala (Five devices) 30 October 2008 Guwahati, Assam (18 devices) 26-29 November 2008 Mumbai, Maharashtra (Multiple Attacks & Blasts) 27 September 2008 New Delhi (One device) 01January 2008 Rampur, U.P (Two devices)
    5. 5. Major Naxalites Areas
    6. 6. Circa 2010: Transition Patterns - Naxalism Discontent among the 'strategic' arm of Naxals differences between groups supporting armed struggle and other, ready for negotiations Military arm of Naxals becoming aggressive Religion and caste becoming an issues Leveraging the political forces Ambiguous leadership Discontent among members Clash in recruitment and funding sources Naxalism in Transition Naxal Organization Indian government actions and 'reactions' Absence of constructive and 'crowd pulling' ideology
    7. 7. Transition of terrorism in India (post 26/11) Transition of terrorism in India (post 26/11) Organised Crime Linkages (local & international) Meticulous operational and strategic planning Recruitment is becoming local focusing on those working in factories and computer literates from big cities Emergence of India as a target of transnational terrorism Expanding logistical homebase Still 'waiting' to carry out mass large scale attacks Impacted by neighborhood Geo-strategic forces
    8. 8. Information Asymmetry - Mining for real time intelligence <ul><li>Requirement for massive high-performance parallel-processing clusters/cloud computing - consisting of hundreds of servers </li></ul><ul><li>Network centric data mining platforms </li></ul><ul><li>Massive databases - very specialized database architecture </li></ul>Historical data analysis would train expert engines to raise triggers and red flags. Real time data mining will generate trends and patterns in the usage Multiple Sims Multiple Handsets Internet account Account: Hazi Al Password: Hazi_123 Location [email_address] [email_address] [email_address] IP address MAC address Metadata Email tracing Telephone Banking and Card Usage
    9. 9. Challenges for the security forces Terrain & Demographic Information Intelligence collation from diverse sources Network centric operations & comd & control Technology Platforms Evolution of Organized crime Development of the Concept of Operations Strategic Challenges
    10. 10. Challenges for the security forces (Intelligence & Ops) Information availability in multi agency envt Leveraging on predictive patterns Managing short term and long term op activities Planning and monitoring Information asymmetry Command and Control The single largest challenge is the creation of actionable intelligence for actual op execution
    11. 11. The Intelligence Stack Strategic Intelligence Operational Intelligence Tactical Intelligence Tactical Intelligence Operational Intelligence Strategic Intelligence Intelligence Consumption Intelligence Creation
    12. 12. Technical Intelligence + Human Intelligence Predictive and Investigative Intelligence Intelligence Needs Granularity - Data Cubes WHY WHAT WHERE WHO WHEN
    13. 13. Convergence – Human Int and Tech Int Intelligence Agencies - Databases Administrative - Databases Tech Intelligence Datamining Processing Raw Data into Usable form Better Information Collection Internet based information collection and investigation (Track Back) Enhanced Prevent-Prepare-Respond-Recover Structure Identifying Triggers & Patterns Automated analysis of structured & unstructured data Human Intelligence © 2010 - Orkash Services Pvt. Ltd. … ensuring Assurance in complexity and uncertainty
    14. 14. The FOUR Pillars of Automated Intelligence Creation Information Extraction and Monitoring Semantic Analysis Geospatial Analysis Data Mining & Forensics <ul><li>Extraction of data </li></ul><ul><li>from various </li></ul><ul><li>sources including </li></ul><ul><li>websites, blogs, </li></ul><ul><li>mobile phone, </li></ul><ul><li>emails and courier records </li></ul><ul><li>Banking </li></ul><ul><li>transactions, credit </li></ul><ul><li>card usage, travel </li></ul><ul><li>records </li></ul><ul><li>Monitoring of web </li></ul><ul><li>for any unusual </li></ul><ul><li>communication and </li></ul><ul><li>red flags </li></ul>Use of semantics to decipher the content Unstructured to structured data Using domain specific ontologies Network analysis Tools and analytics Analysis of the geospatial context and better data visualization Geospatial intelligence for effective decision making Location intelligence for better interpretation of networks & activities Data Mining on real time basis Analysis of trends and patterns of activities Internet & Cyber Forensics Target Centric Social Network Analysis Pattern Tracing and Tracking
    15. 15. Automating Intelligence Creation - The Process Layers © 2010 - Orkash Services Pvt. Ltd . Information generation/extraction Semantic analysis Geospatial analysis Leverage ‘ collective int’ <ul><li>Where is the Intelligence Gap </li></ul><ul><ul><ul><li>access and extraction of information </li></ul></ul></ul><ul><ul><ul><ul><li>language interpretation for the context, and removal of NOISE </li></ul></ul></ul></ul><ul><ul><ul><ul><ul><li>search vs scan . </li></ul></ul></ul></ul></ul><ul><ul><ul><ul><li>pattern tracking, granularity & visualization </li></ul></ul></ul></ul>Data mining
    16. 16. Target Centric Intelligence Model
    17. 17. Unconventional Conflict & Intelligence Management System (UCIMS)
    18. 18. Intelligence collaboration process Intelligence sources Socio political events Demographics Sat images, maps Technical inputs Data repository - Raw data - Analysis of data - Intelligence creation - Intelligence distribution Actionable intelligence Tactical decision making Intelligence collaboration process
    19. 19. Semantic Enrichment <ul><li>Semantic enrichmen t is the process of creating or associating semantic tags in unstructured data or text, usually involving concepts, entities, relationships, events and properties described in an ontology or rule based </li></ul><ul><li>Benefits : </li></ul><ul><ul><li>Adding semantic metadata tags to the original unstructured data enables advanced correlation and data fusion capabilities. </li></ul></ul><ul><ul><li>Enables concept , event and relationship extraction and automated metadata tagging. </li></ul></ul>(XML) D1 D2 D3 . . Dn Document Classification Classification Results Commonsense Engine Concepts Engine Concepts Tagged Documents + Entities Semantic Enrichment Semantically Enriched Documents Documents
    20. 22. Combining Data Mining and Link Analysis
    21. 23. Inferenced Information Representation
    22. 24. Deeper relations between entities
    23. 25. Association between events
    24. 26. Network Analysis and Data visualization (1) Manually creation of association matrix by identifying the relations through raw data (2) Helpful in investigation, becomes ineffective where datasets are very large (1) Graphically representation of insurgent networks using tools such as Link Analysis (2) Helpful in visualization of large amount of relationship data but without analytical functionality. (1)Advanced analytical capabilities to assist investigation (2) It can help in identifying networks to mining of large volumes of data to discover useful knowledge and create intelligence about the structure and organization of criminal networks - Data Mining - Social Network Analysis - Pattern Tracing and interactions © 2010 - Orkash Services Pvt. Ltd. … ensuring Assurance in complexity and uncertainty Manual Graphics-based Manual Structured
    25. 27. Past historical factual information
    26. 28. Visualizing Semantic Data Analysis in GIS Context <ul><li>Visualization of the meta-data and the content – Creation of 'Visual' layers </li></ul><ul><li>Role of contextual scan -semantic </li></ul><ul><li>and geospatial </li></ul><ul><li>User created content and collective intelligence </li></ul>
    27. 29. OLAP analysis
    28. 30. Naxal Emerging Fault lines Castes and tribes Within tribes Inter-state leadership CPI (Maoist) and frontal organizations Splinter groups The direction these splits take as the government action on all fronts intensifies will have a major bearing on the future of Naxal movement and strategy in India Naxal Movement
    29. 31. Interaction with socio-political environment <ul><li>CORELATION BETWEEN NAXAL EXPANSION AND LOCAL COMMUNITY MOVEMENTS </li></ul>
    30. 32. ‘ GO’ Areas—Risk Profiles (Case Study) Durg Kanker East Baster East <ul><li>Trends </li></ul><ul><li>Risk is spread more equitably among factors </li></ul><ul><li>5 out of the 10 factors each contribute less than 10% </li></ul><ul><li>Low crime risk, less adverse geography, and low political risk are common </li></ul><ul><li>Naxalism and Street Crime are low as well </li></ul><ul><li>Despite high socio-economic risk, the better profile in the parameters above make these areas safe to travel </li></ul><ul><li>Disruption from the tribal population is high </li></ul>8% 8% 5% 5% 15% 16% 13% 11% 6% 13% Extremism Crime Geography Political Socio-Econ Population Land Politics Business Natural Hazard Local Sentiments 9% 6% 6% 7% 17% 16% 11% 9% 4% 15% Extremism Crime Geography Political Socio-Econ Population Land Politics Business Natural Hazard Local Sentiments 11% 8% 4% 6% 13% 11% 15% 8% 7% 17% Extremism Crime Geography Political Socio-Econ Population Land Politics Business Natural Hazard Local Sentiments
    31. 33. ‘ Borderline Go’ Areas—Risk Profiles (Case Study) Dantewada Central Kanker West Baster West <ul><li>Trends </li></ul><ul><li>Risk is spread more equitably among factors </li></ul><ul><li>4 out of the 10 factors each contribute less than 10% </li></ul><ul><li>However extremism and geography related risks are high and Local Sentiment is a moderate risk </li></ul><ul><li>Businesses are in operations and socio-economic factors are healthier and Go and No Go areas </li></ul><ul><li>Land politics related disruptions are low in these areas </li></ul>16% 10% 18% 10% 8% 11% 8% 2% 5% 12% Extremism Crime Geography Political Socio-Econ Population Land Politics Business Natural Hazard Local Sentiments 15% 11% 17% 6% 13% 10% 9% 4% 2% 13% Extremism Crime Geography Political Socio-Econ Population Land Politics Business Natural Hazard Local Sentiments 14% 10% 15% 9% 11% 10% 11% 5% 3% 12% Extremism Crime Geoography Political Socio-Econ Population Land Politics Business Natural Hazard Local Sentiments
    32. 34. ‘ NO GO’ Areas—Risk Profiles (Case Study) Dantewada West Dantewada East <ul><li>Trends </li></ul><ul><li>Other than three factors, these areas have a predominantly high risk profile </li></ul><ul><li>High risk from extremism (low crime rates), socio-economic risk, geography-related risk, local sentiments make these areas unsafe to travel in </li></ul><ul><li>Very high naxalite presence with a number of reported incidents from police clashes, Extortion, Arson and Robbery </li></ul><ul><li>There is also a politician-bureaucrat nexus and a lack of local administration or effective panchayats </li></ul><ul><li>Communal tensions are also high with some parts displaying a clear anti-foreigner sentiment </li></ul>
    33. 35. Basis for Risk Mitigation - (Case Study) Low Risks They do not require the formulation of a risk mitigation strategy at this stage of exploration work Moderate Risks Awareness about factors and influences that drive these parameters, and regular monitoring are required. The threats from these risks however will not have a direct impact at this stage Extreme & High Risks Those areas that register a 15+ total on freq * severity require active risk mitigations strategies to be in place
    34. 36. Sample KRI Parameters & Triggers for Risk Intelligence Framework (a large mining project in India) - (Case Study)   Common Borders   Topography   Forest Cover that indicates Naxalite hideout zones   Rivers — that could potentially lead to crime and water politics in the future. Seasonal floods, as well as shortage of irrigation water in certain seasons lead to incidents of violence, crime and clashes amongst villagers   Location of a particular district   Population   Incidents in the district   Nature of criminal groups   State of police and governance   Presence of Naxalism (The number, strength and method indicate the pos sibility of Naxalite Attacks)   Ammunition recovery and Arrests within a district (Reflects the strength of the network) Crime/Extremism Geography Local Political Situation   Constituency representative   Opposition parties   Influence of Naxalite political groups   Local support for Naxalites/ political party A constituency with high profile candidates and major political parties attract Naxalite attacks and the crime - politics connection Socio - Economic   Economic Profile   Literacy   Occupation   Youth — education and employment   Percentage of SC/ST * in total population -- A high risk socio - economic profile can provide flashpoints for the future -- The youth form a substant ial part of the “new criminals” * SC/ST – Scheduled Cast e s / Scheduled Tribes Land Politics   Type of Land   Yield   Size of holdings   Land Clashes Caste - based attacks and crimes result in human loss and psyc hological fear in an area Road + Rail   Presence of NH/SH in the district   Condition of roads and rail network   I ncidents on both   Accidents   Closest railway stations and alternative ways of access Infrastructure   Hospitals   Banks   Electricity/Power sup ply   Telecom Circle   Water Local Sentiment   Attitude towards foreigners   Attitude towards Mining   Protests   Mobilizers — NGOs, Pradhans   L ocal media Businesses   No . of Businesses in the area   Year of start and closure   Nature of Business   Ratio of Businesses closed to open Natural Hazard   Earthquakes   Floods   Monsoon   Drought
    35. 37. Risk Visualization / Risk Map – Mining Project - (Case Study) Disruptions Methods of Stalling High Risk Medium Risk Low Risk R I S K I N T E L L I G E N C E Vulnerabilities Associated with Legal, Regulatory, & Policy Issues Demonstrations, Strikes Security/Loss/ Sabotage Instruments which can make this happen Extremism/ Crime Political Dynamics People’s Right Activists Local Social & Community Issues Local Contracts Resettlements Pollution Environment Local Employment Socio - Economic Reasons
    36. 38. ORKASH-UCIMS on a geospatial platform
    37. 40. Intelligence & Operations Management
    38. 41. Connecting the Dots..
    39. 42. Location Intelligence
    40. 43. Tracking events news with location based search
    41. 44. Advanced Search Techniques for Location Intelligence
    42. 46. Monitoring Movement of Tactical Assets
    43. 47. Air Surveillance
    44. 48. UCIMS Features <ul><li>An integrated and networked information system to process and identify patterns and trends in intelligence, socio-political events etc </li></ul><ul><li>Advanced intelligence analysis and intelligence management capabilities </li></ul><ul><li>Tactical operations planning modules in a 3-D terrain based geographic information system
 </li></ul><ul><li>A fully capable and customizable network-centric command and control system </li></ul><ul><li>Integration with the ground and air surveillance systems
 </li></ul><ul><li>Capable of automated visualization of operational and situational updates
 on maps and satellite imagery </li></ul><ul><li>Enables collaborative exchange of operational information amongst multiple teams operating from different locations
 </li></ul><ul><li>Seamless pattern analysis, data-mining, OLAP, network-graphs and link-analysis </li></ul><ul><li>A customizable network-centric command and control platform
    45. 49. Network Centric Command and Control System <ul><li>Translates information advantage to competitive advantage through robust networking of well-informed geographically dispersed forces through a centralized Command and Control System </li></ul>Network diverse entities Allow information Sharing Enhance Situational Awareness Enable - C4I Increase mission effectiveness
    46. 50. THANK YOU Orkash Services Pvt Ltd 75 C, Sector 18 Gurgaon 122 015 Haryana, India Phone: +91 124 4033773 +91 98102 36020 [email_address] .com
    47. 51. Impetus on intelligence creation - why? <ul><li>Develop and promote 'all source' information collection and analysis </li></ul><ul><li>Create operational integration </li></ul><ul><li>Improve counterintelligence support </li></ul><ul><li>Automation of information collection to provide the necessary cue to strategists for future action </li></ul><ul><li>Facilitate the effective processing of large volumes of data, information tagging, archival and also retrieval </li></ul><ul><li>Identify and reduce collection of information redundancies, analysis of information etc </li></ul>
    48. 52. Changing security landscape of India India has experienced a continued and an almost consistent security problem pertaining to: -Naxalism - Insurgency -Extremism -Organized crime Drivers of Transition: -Operational Sophistication -Ideological Evolution India's internal security scenario is in a very 'delicate' and a 'vulnerable' stage Unconventional conflicts and deteriorating security mechanisms have forced us to think beyond the routine 'guard and police' protection Essentially non existent, it is high time that India focuses on homeland security protection Long history of terrorism Terrorism Transition Internal Security Security Evolution Homeland Security
    49. 53. Homeland security in India Increased focus on HLS post 26/11 Fragmented structure of HLS sector Technology Modernization New Technology Introduction Information Synthesis
    50. 54. Intelligence Challenges and Connecting the Dots.. <ul><li>Intelligence is generated at multiple levels and </li></ul><ul><li>consumed at operational level </li></ul><ul><li>Manual analysis of large data is difficult - with automation it can be quickly sorted and interpreted through link analysis </li></ul><ul><li>Linkages of historical data essential for better interpretation </li></ul><ul><li>GIS and 3 D imagery linked to database systems are powerful tools to interpret in real time </li></ul><ul><li>Pull Model of Intelligence is not efficient, it needs to be pushed down as a consumable commodity </li></ul>© 2010 - Orkash Services Pvt. Ltd. … ensuring Assurance in complexity and uncertainty